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WITS)","rep":"NAT.od.wits.XPRT-TRD-VL.01_05_Animal","n":29,"dims":["Groupe de produits"]}},"indicators":[{"code":"EG.CFT.ACCS.ZS","name":"Accès à des combustibles propres et à des technologies pour cuisiner ( % de la population)","description":"L’accès aux combustibles et technologies propres pour la cuisson correspond à la proportion de la population totale utilisant principalement des co...","source_link":"https://donnees.banquemondiale.org/indicateur/EG.CFT.ACCS.ZS?locations=CI","methodology":"Methodology: Data for access to clean fuels and technologies for cooking are based on the World Health Organization’s (WHO) Global Household Energy Database. They are collected among different sources: only data from nationally representative household surveys (including national censuses) were used. Survey sources include Demographic and Health Surveys (DHS) and Living Standards Measurement Surveys (LSMS), Multi-Indicator Cluster Surveys (MICS), the World Health Survey (WHS), other nationally developed and implemented surveys, and various government agencies (for example, ministries of energy and utilities). Trends in the proportion of the population using each fuel type are estimated using a single multivariate hierarchical model, with urban and rural disaggregation. Estimates for overall ‘polluting’ fuels (unprocessed biomass, charcoal, coal, and kerosene) and ‘clean’ fuels (gaseous fuels, electricity, as well as an aggregation of any other clean fuels like alcohol) are produced by aggregating estimates of relevant fuel types. The model was used to derive clean fuel use estimates for 191 countries (ref. Stoner, O., Shaddick, G., Economou, T., Gumy, S., Lewis, J., Lucio, I., Ruggeri, G. and Adair-Rohani, H. (2020), Global household energy model: a multivariate hierarchical approach to estimating trends in the use of polluting and clean fuels for cooking. J. R. Stat. Soc. C, 69: 815-839). Countries classified by the World Bank as high income (57 countries) in the 2022 fiscal year are assumed to have universal access to clean fuels and technologies for cooking.","theme":"secondary","source_group":"wb"},{"code":"EG.CFT.ACCS.RU.ZS","name":"Accès à des combustibles propres et à des technologies pour la cuisson, zones rurales ( % de la population rurale)","description":"L'accès aux combustibles et technologies propres pour la cuisson, en milieu rural, est la proportion de la population rurale utilisant principaleme...","source_link":"https://donnees.banquemondiale.org/indicateur/EG.CFT.ACCS.RU.ZS?locations=CI","methodology":"Methodology: Data for access to clean fuels and technologies for cooking are based on the World Health Organization’s (WHO) Global Household Energy Database. They are collected among different sources: only data from nationally representative household surveys (including national censuses) were used. Survey sources include Demographic and Health Surveys (DHS) and Living Standards Measurement Surveys (LSMS), Multi-Indicator Cluster Surveys (MICS), the World Health Survey (WHS), other nationally developed and implemented surveys, and various government agencies (for example, ministries of energy and utilities). Trends in the proportion of the population using each fuel type are estimated using a single multivariate hierarchical model, with urban and rural disaggregation. Estimates for overall ‘polluting’ fuels (unprocessed biomass, charcoal, coal, and kerosene) and ‘clean’ fuels (gaseous fuels, electricity, as well as an aggregation of any other clean fuels like alcohol) are produced by aggregating estimates of relevant fuel types. The model was used to derive clean fuel use estimates for 191 countries (ref. Stoner, O., Shaddick, G., Economou, T., Gumy, S., Lewis, J., Lucio, I., Ruggeri, G. and Adair-Rohani, H. (2020), Global household energy model: a multivariate hierarchical approach to estimating trends in the use of polluting and clean fuels for cooking. J. R. Stat. Soc. C, 69: 815-839). Countries classified by the World Bank as high income (57 countries) in the 2022 fiscal year are assumed to have universal access to clean fuels and technologies for cooking.","theme":"secondary","source_group":"wb"},{"code":"EG.CFT.ACCS.UR.ZS","name":"Accès à des combustibles propres et à des technologies pour la cuisson, urbain ( % de la population urbaine)","description":"L'accès aux combustibles et technologies propres pour la cuisson en milieu urbain correspond à la proportion de la population urbaine utilisant pri...","source_link":"https://donnees.banquemondiale.org/indicateur/EG.CFT.ACCS.UR.ZS?locations=CI","methodology":"Methodology: Data for access to clean fuels and technologies for cooking are based on the World Health Organization’s (WHO) Global Household Energy Database. They are collected among different sources: only data from nationally representative household surveys (including national censuses) were used. Survey sources include Demographic and Health Surveys (DHS) and Living Standards Measurement Surveys (LSMS), Multi-Indicator Cluster Surveys (MICS), the World Health Survey (WHS), other nationally developed and implemented surveys, and various government agencies (for example, ministries of energy and utilities). Trends in the proportion of the population using each fuel type are estimated using a single multivariate hierarchical model, with urban and rural disaggregation. Estimates for overall ‘polluting’ fuels (unprocessed biomass, charcoal, coal, and kerosene) and ‘clean’ fuels (gaseous fuels, electricity, as well as an aggregation of any other clean fuels like alcohol) are produced by aggregating estimates of relevant fuel types. The model was used to derive clean fuel use estimates for 191 countries (ref. Stoner, O., Shaddick, G., Economou, T., Gumy, S., Lewis, J., Lucio, I., Ruggeri, G. and Adair-Rohani, H. (2020), Global household energy model: a multivariate hierarchical approach to estimating trends in the use of polluting and clean fuels for cooking. J. R. Stat. Soc. C, 69: 815-839). Countries classified by the World Bank as high income (57 countries) in the 2022 fiscal year are assumed to have universal access to clean fuels and technologies for cooking.","theme":"secondary","source_group":"wb"},{"code":"EG.ELC.ACCS.ZS","name":"Accès à l'électricité ( % de la population)","description":"L'accès à l'électricité est le pourcentage de la population ayant accès à l'électricité.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.ACCS.ZS?locations=CI","methodology":"Methodology: The World Bank’s Global Electrification Database (GED) compiles nationally representative household survey data, and occasionally census data, from sources going back as far as 1990. The database also incorporates data from the Socio-Economic Database for Latin America and the Caribbean (SEDLAC), Middle East and North Africa Poverty Database (MNAPOV) and the Europe and Central Asia Poverty Database (ECAPOV), which are based on similar surveys. At the time of this analysis, the GED contained 1,375 surveys for 149 countries in 1990-2021.","theme":"secondary","source_group":"wb"},{"code":"EG.ELC.ACCS.RU.ZS","name":"Accès à l'électricité, rural ( % de la population rurale)","description":"L'accès à l'électricité en milieu rural est le pourcentage de la population rurale ayant accès à l'électricité.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.ACCS.RU.ZS?locations=CI","methodology":"Methodology: The World Bank’s Global Electrification Database (GED) compiles nationally representative household survey data, and occasionally census data, from sources going back as far as 1990. The database also incorporates data from the Socio-Economic Database for Latin America and the Caribbean (SEDLAC), Middle East and North Africa Poverty Database (MNAPOV) and the Europe and Central Asia Poverty Database (ECAPOV), which are based on similar surveys. At the time of this analysis, the GED contained 1,375 surveys for 149 countries in 1990-2021.","theme":"secondary","source_group":"wb"},{"code":"EG.ELC.ACCS.UR.ZS","name":"Accès à l'électricité, urbain ( % de la population urbaine)","description":"L'accès à l'électricité en milieu urbain est le pourcentage de la population urbaine ayant accès à l'électricité.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.ACCS.UR.ZS?locations=CI","methodology":"Methodology: The World Bank’s Global Electrification Database (GED) compiles nationally representative household survey data, and occasionally census data, from sources going back as far as 1990. The database also incorporates data from the Socio-Economic Database for Latin America and the Caribbean (SEDLAC), Middle East and North Africa Poverty Database (MNAPOV) and the Europe and Central Asia Poverty Database (ECAPOV), which are based on similar surveys. At the time of this analysis, the GED contained 1,375 surveys for 149 countries in 1990-2021.","theme":"secondary","source_group":"wb"},{"code":"FX.OWN.TOTL.ZS","name":"Titulaire d'un compte dans une institution financière ou auprès d'un fournisseur de services d'argent mobile ( % de la population âgée de 15 ans et +)","description":"Le compte désigne le pourcentage de répondants qui déclarent avoir un compte (seuls ou avec quelqu'un d'autre) dans une banque ou un autre type d'i...","source_link":"https://donnees.banquemondiale.org/indicateur/FX.OWN.TOTL.ZS?locations=CI","methodology":"Methodology: Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (% age 15+). Assessment conducted triennially\nStatistical concept(s): Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (% age 15+). Assessment conducted triennially","theme":"tertiary","source_group":"wb"},{"code":"FX.OWN.TOTL.FE.ZS","name":"Titulaire d'un compte dans une institution financière ou auprès d'un fournisseur de services d'argent mobile, femmes ( % de la population âgée de 15 ans et +)","description":"Le compte indique le pourcentage de personnes interrogées qui déclarent avoir un compte (individuellement ou avec quelqu'un d'autre) dans une banqu...","source_link":"https://donnees.banquemondiale.org/indicateur/FX.OWN.TOTL.FE.ZS?locations=CI","methodology":"Methodology: Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (female, % age 15+). Assessment of this occurs triennial\nStatistical concept(s): Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (female, % age 15+). Assessment of this occurs triennial","theme":"tertiary","source_group":"wb"},{"code":"FX.OWN.TOTL.MA.ZS","name":"Titulaire d'un compte dans une institution financière ou auprès d'un fournisseur de services d'argent mobile, hommes ( % de la population âgée de 15 ans et +)","description":"Le compte indique le pourcentage de répondants qui déclarent avoir un compte (seuls ou avec quelqu'un d'autre) dans une banque ou un autre type d'i...","source_link":"https://donnees.banquemondiale.org/indicateur/FX.OWN.TOTL.MA.ZS?locations=CI","methodology":"Methodology: Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (male, % age 15+). Assessment of this occurs triennial.\nStatistical concept(s): Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (male, % age 15+). Assessment of this occurs triennial.","theme":"tertiary","source_group":"wb"},{"code":"FX.OWN.TOTL.OL.ZS","name":"Titulaire d'un compte dans une institution financière ou auprès d'un fournisseur de services d'argent mobile, personnes âgées ( % de la population âgée de 25 ans et +)","description":"Le compte désigne le pourcentage de personnes interrogées qui déclarent avoir un compte (individuellement ou avec quelqu'un d'autre) dans une banqu...","source_link":"https://donnees.banquemondiale.org/indicateur/FX.OWN.TOTL.OL.ZS?locations=CI","methodology":"Methodology: Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (older adults, % of population ages 25+). This assessment occurs triennially\nStatistical concept(s): Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (older adults, % of population ages 25+). This assessment occurs triennially","theme":"tertiary","source_group":"wb"},{"code":"FX.OWN.TOTL.40.ZS","name":"Titulaire d'un compte dans une institution financière ou auprès d'un fournisseur de services d'argent mobile, 40 % des plus pauvres ( % de la population âgée de 15 ans et +)","description":"Le compte désigne le pourcentage de personnes interrogées qui déclarent avoir un compte (individuellement ou avec quelqu'un d'autre) dans une banqu...","source_link":"https://donnees.banquemondiale.org/indicateur/FX.OWN.TOTL.40.ZS?locations=CI","methodology":"Methodology: Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (poorest 40%, share of population ages 15+).\nStatistical concept(s): Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (poorest 40%, share of population ages 15+).","theme":"tertiary","source_group":"wb"},{"code":"FX.OWN.TOTL.PL.ZS","name":"Titulaire d'un compte dans une institution financière ou auprès d'un fournisseur de services d'argent mobile, éducation primaire ou moins ( % de la population âgée de 15 ans et +)","description":"Le compte désigne le pourcentage de répondants qui déclarent avoir un compte (seuls ou avec quelqu'un d'autre) dans une banque ou un autre type d'i...","source_link":"https://donnees.banquemondiale.org/indicateur/FX.OWN.TOTL.PL.ZS?locations=CI","methodology":"Methodology: Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (primary education or less, % of population ages 15+). This assessment is conducted triennially \nStatistical concept(s): Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (primary education or less, % of population ages 15+). This assessment is conducted triennially","theme":"tertiary","source_group":"wb"},{"code":"FX.OWN.TOTL.60.ZS","name":"Titulaire d'un compte dans une institution financière ou auprès d'un fournisseur de services d'argent mobile, 60 % les plus riches ( % de la population âgée de 15 ans et +)","description":"Le compte désigne le pourcentage de personnes interrogées qui déclarent avoir un compte (individuellement ou avec quelqu'un d'autre) dans une banqu...","source_link":"https://donnees.banquemondiale.org/indicateur/FX.OWN.TOTL.60.ZS?locations=CI","methodology":"Methodology: Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (richest 60%, share of population ages 15+).\nStatistical concept(s): Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (richest 60%, share of population ages 15+).","theme":"tertiary","source_group":"wb"},{"code":"FX.OWN.TOTL.SO.ZS","name":"Titulaire d'un compte dans une institution financière ou auprès d'un fournisseur de services d'argent mobile, formation secondaire ou plus ( % de la population âgée de 15 ans et +)","description":"Le compte désigne le pourcentage de répondants qui déclarent avoir un compte (seuls ou avec quelqu'un d'autre) dans une banque ou un autre type d'i...","source_link":"https://donnees.banquemondiale.org/indicateur/FX.OWN.TOTL.SO.ZS?locations=CI","methodology":"Methodology: Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (secondary education or more, % of population ages 15+). This assessment is conducted triennially\nStatistical concept(s): Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (secondary education or more, % of population ages 15+). This assessment is conducted triennially","theme":"tertiary","source_group":"wb"},{"code":"FX.OWN.TOTL.YG.ZS","name":"Titulaire d'un compte dans une institution financière ou auprès d'un fournisseur de services d'argent mobile, jeunes adultes ( % de la population âgée de 15 à 24 ans)","description":"Le compte désigne le pourcentage de répondants qui déclarent avoir un compte (seuls ou avec quelqu'un d'autre) dans une banque ou un autre type d'i...","source_link":"https://donnees.banquemondiale.org/indicateur/FX.OWN.TOTL.YG.ZS?locations=CI","methodology":"Methodology: Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (young adults, % of population ages 15-24).  This assessment is conducted triennially.\nStatistical concept(s): Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (young adults, % of population ages 15-24).  This assessment is conducted triennially.","theme":"tertiary","source_group":"wb"},{"code":"per_si_allsi.adq_pop_tot","name":"Adéquation des programmes d'assurance sociale ( % du bien-être total des ménages bénéficiaires)","description":"L'adéquation des programmes d'assurance sociale est mesurée par le montant total des transferts reçus par la population participant aux programmes ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_si_allsi.adq_pop_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_allsp.adq_pop_tot","name":"Adéquation des programmes de protection sociale et de travail ( % du bien-être total des ménages bénéficiaires)","description":"L'adéquation de la protection sociale et des programmes de travail (SPL) est mesurée par le montant total des transferts reçus par la population pa...","source_link":"https://donnees.banquemondiale.org/indicateur/per_allsp.adq_pop_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_sa_allsa.adq_pop_tot","name":"Adéquation des programmes de protection sociale ( % du bien-être total des ménages bénéficiaires)","description":"L’adéquation des programmes de filets de sécurité sociale est mesurée par le montant total des transferts reçus par la population participant aux p...","source_link":"https://donnees.banquemondiale.org/indicateur/per_sa_allsa.adq_pop_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_lm_alllm.adq_pop_tot","name":"Adéquation des prestations de chômage et des MPAM ( % du bien-être total des ménages bénéficiaires)","description":"L’adéquation des allocations de chômage et des programmes actifs du marché du travail (PAMT) est mesurée par le montant total des transferts reçus ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_lm_alllm.adq_pop_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"SE.PRM.TENR","name":"Taux net ajusté de scolarisation, primaire (en % des enfants en âge de fréquenter l'école primaire)","description":"Le taux de scolarisation net ajusté est le nombre d'élèves du groupe d'âge scolaire pour l'enseignement primaire, inscrits dans l'enseignement prim...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.TENR?locations=CI","methodology":"Methodology: Adjusted net enrollment rate in primary education is calculated by dividing the number of children in the official primary school age who are enrolled in primary or secondary education by the population of the same age group and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.PRM.TENR.FE","name":"Taux net ajusté de scolarisation, primaire, filles ( % des enfants en âge de fréquenter l'école primaire)","description":"Le taux de scolarisation net ajusté est le nombre d'élèves du groupe d'âge scolaire pour l'enseignement primaire, inscrits dans l'enseignement prim...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.TENR.FE?locations=CI","methodology":"Methodology: Adjusted net enrollment rate in primary education is calculated by dividing the number of children in the official primary school age who are enrolled in primary or secondary education by the population of the same age group and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.PRM.TENR.MA","name":"Taux net ajusté de scolarisation, primaire, garçons ( % des enfants en âge de fréquenter l'école primaire)","description":"Le taux de scolarisation net ajusté est le nombre d'élèves du groupe d'âge scolaire pour l'enseignement primaire, inscrits dans l'enseignement prim...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.TENR.MA?locations=CI","methodology":"Methodology: Adjusted net enrollment rate in primary education is calculated by dividing the number of children in the official primary school age who are enrolled in primary or secondary education by the population of the same age group and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"NY.ADJ.NNTY.KD.ZG","name":"Revenu national net ajusté (croissance annuelle en %)","description":"Le revenu national net ajusté correspond au RNB moins la consommation de capital fixe et l’épuisement des ressources naturelles.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.NNTY.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.NNTY.KD","name":"Revenu national net ajusté (en dollars constants de 2015)","description":"Le revenu national net ajusté correspond au RNB moins la consommation de capital fixe et l’épuisement des ressources naturelles.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.NNTY.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.NNTY.CD","name":"Revenu national net ajusté (en dollars américains courants)","description":"Le revenu national net ajusté correspond au RNB moins la consommation de capital fixe et l’épuisement des ressources naturelles.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.NNTY.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.NNTY.PC.KD.ZG","name":"Revenu national net ajusté par habitant (croissance annuelle en %)","description":"Le revenu national net ajusté correspond au RNB moins la consommation de capital fixe et l’épuisement des ressources naturelles.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.NNTY.PC.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.NNTY.PC.KD","name":"Revenu national net ajusté par habitant (en dollars constants de 2015)","description":"Le revenu national net ajusté correspond au RNB moins la consommation de capital fixe et l’épuisement des ressources naturelles.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.NNTY.PC.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.NNTY.PC.CD","name":"Revenu national net ajusté par habitant (en dollars courants des États-Unis)","description":"Le revenu national net ajusté correspond au RNB moins la consommation de capital fixe et l’épuisement des ressources naturelles.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.NNTY.PC.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.SVNX.GN.ZS","name":"Économies nettes ajustées, hors émissions de particules ( % du RNB)","description":"L’épargne nette ajustée est égale à l’épargne nationale nette plus les dépenses d’éducation et moins l’épuisement de l’énergie, l’épuisement des mi...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.SVNX.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.SVNX.CD","name":"Économies nettes ajustées, hors dommages causés par les émissions de particules (en dollars américains courants)","description":"L’épargne nette ajustée est égale à l’épargne nationale nette plus les dépenses d’éducation et moins l’épuisement de l’énergie, l’épuisement des mi...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.SVNX.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.SVNG.GN.ZS","name":"Économies nettes ajustées, y compris les dommages causés par les émissions de particules ( % du RNB)","description":"Les économies nettes ajustées sont égales à l’épargne nationale nette plus les dépenses d’éducation et moins l’épuisement de l’énergie, l’épuisemen...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.SVNG.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.SVNG.CD","name":"Économies nettes ajustées, y compris les dommages causés par les émissions de particules (en dollars américains courants)","description":"Les économies nettes ajustées sont égales à l’épargne nationale nette plus les dépenses d’éducation et moins l’épuisement de l’énergie, l’épuisemen...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.SVNG.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DCO2.GN.ZS","name":"Économies ajustées, dommages causés par le dioxyde de carbone ( % du RNB)","description":"Coût des dommages dus aux émissions de dioxyde de carbone dues à l’utilisation de combustibles fossiles et à la fabrication du ciment, estimé à 40 ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DCO2.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DCO2.CD","name":"Économies ajustées, dommages causés par le dioxyde de carbone ($ US courants)","description":"Coût des dommages dus aux émissions de dioxyde de carbone dues à l’utilisation de combustibles fossiles et à la fabrication du ciment, estimé à 40 ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DCO2.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DKAP.GN.ZS","name":"Épargne ajustée, consommation de capital fixe ( % du RNB)","description":"La consommation de capital fixe représente la valeur de remplacement du capital utilisé dans le processus de production.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DKAP.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DKAP.CD","name":"Épargne ajustée, consommation de capital fixe ($ US courants)","description":"La consommation de capital fixe représente la valeur de remplacement du capital utilisé dans le processus de production.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DKAP.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.AEDU.GN.ZS","name":"Épargne ajustée, dépenses d'éducation ( % du RNB)","description":"Les dépenses d'éducation font référence aux dépenses de fonctionnement courantes dans l'éducation, y compris les salaires et traitements et à l'exc...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.AEDU.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.AEDU.CD","name":"Épargne ajustée, dépenses d'éducation (en dollars américains courants)","description":"Les dépenses d'éducation font référence aux dépenses de fonctionnement courantes dans l'éducation, y compris les salaires et traitements et à l'exc...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.AEDU.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DNGY.GN.ZS","name":"Économies ajustées, épuisement de l'énergie ( % du RNB)","description":"L'épuisement énergétique est le rapport entre la valeur du stock de ressources énergétiques et la durée de vie restante de la réserve (plafonnée à ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DNGY.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DNGY.CD","name":"Économies ajustées, épuisement de l'énergie ($ US courants)","description":"L'épuisement énergétique est le rapport entre la valeur du stock de ressources énergétiques et la durée de vie restante de la réserve (plafonnée à ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DNGY.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.ICTR.GN.ZS","name":"Épargne ajustée, épargne brute ( % du RNB)","description":"L'épargne brute est la différence entre le revenu national brut et la consommation publique et privée, plus les transferts courants nets.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.ICTR.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DMIN.GN.ZS","name":"Économies ajustées, épuisement des minéraux ( % du RNB)","description":"L'épuisement des ressources minérales est le rapport entre la valeur du stock de ressources minérales et la durée de vie restante des réserves (pla...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DMIN.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DMIN.CD","name":"Économies ajustées, épuisement des minéraux ($ US courants)","description":"L'épuisement des ressources minérales est le rapport entre la valeur du stock de ressources minérales et la durée de vie restante des réserves (pla...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DMIN.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DRES.GN.ZS","name":"Épargne ajustée, épuisement des ressources naturelles ( % du RNB)","description":"L’épuisement des ressources naturelles est la somme de l’épuisement net des forêts, de l’épuisement énergétique et de l’épuisement des minéraux.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DRES.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DFOR.GN.ZS","name":"Économies ajustées, épuisement net des forêts ( % du RNB)","description":"L’épuisement net des forêts est calculé comme le produit des rentes unitaires de ressources et de l’excédent de récolte de bois rond par rapport à ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DFOR.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DFOR.CD","name":"Économies ajustées, épuisement net des forêts (en dollars américains courants)","description":"L’épuisement net des forêts est calculé comme le produit des rentes unitaires de ressources et de l’excédent de récolte de bois rond par rapport à ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DFOR.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.NNAT.GN.ZS","name":"Épargne ajustée, épargne nationale nette ( % du RNB)","description":"L'épargne nationale nette est égale à l'épargne nationale brute moins la valeur de la consommation de capital fixe.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.NNAT.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.NNAT.CD","name":"Épargne ajustée, épargne nationale nette (en dollars américains courants)","description":"L'épargne nationale nette est égale à l'épargne nationale brute moins la valeur de la consommation de capital fixe.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.NNAT.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DPEM.GN.ZS","name":"Économies ajustées, dommages causés par les émissions de particules ( % du RNB)","description":"Les dommages causés par les émissions de particules sont les dommages dus à l'exposition de la population d'un pays à des concentrations ambiantes ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DPEM.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.ADJ.DPEM.CD","name":"Économies ajustées, dommages causés par les émissions de particules ($ US courants)","description":"Les dommages causés par les émissions de particules sont les dommages dus à l'exposition de la population d'un pays à des concentrations ambiantes ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.ADJ.DPEM.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"SP.ADO.TFRT","name":"Taux de fécondité chez les adolescentes (naissances pour 1 000 femmes âgées de 15 à 19 ans)","description":"Le taux de fécondité des adolescentes correspond au nombre de naissances pour 1 000 femmes âgées de 15 à 19 ans.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.ADO.TFRT?locations=CI","methodology":"Methodology: Adolescent fertility rates are based on data on registered live births from vital registration systems or, in the absence of such systems, from censuses or sample surveys. The estimated rates are generally considered reliable measures of fertility in the recent past. Where no empirical information on age-specific fertility rates is available, a model is used to estimate the share of births to adolescents. For countries without vital registration systems fertility rates are generally based on censuses or surveys.\nStatistical concept(s): Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.","theme":"demo","source_group":"wb"},{"code":"SE.SEC.UNER.LO.ZS","name":"Adolescents non scolarisés ( % de l'âge du premier cycle du secondaire)","description":"Les adolescents non scolarisés représentent le pourcentage d’adolescents en âge de fréquenter l’école secondaire inférieure qui ne sont pas inscrit...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.UNER.LO.ZS?locations=CI","methodology":"Methodology: The rate of out-of-school adolescents allows to compare across countries with different population sizes. It shows the share of official lower secondary age adolescents who never attended school or dropped out to the population of official lower secondary school age.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator measures the proportion of the population within the official age range for a specific educational level who are not currently enrolled in school. The data aids in identifying these individuals to tailor targeted interventions and formulate effective policies, ensuring that all children have the opportunity to attend school. It encompasses children who have never attended school, those who may enroll at a later age, and those who have started education but did not continue to the expected age of completion for the specified level.","theme":"education","source_group":"wb"},{"code":"SE.SEC.UNER.LO.FE.ZS","name":"Adolescentes non scolarisées, filles ( % des filles en âge de fréquenter le premier cycle de l'enseignement secondaire)","description":"Les adolescents non scolarisés représentent le pourcentage d’adolescents en âge de fréquenter l’école secondaire inférieure qui ne sont pas inscrit...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.UNER.LO.FE.ZS?locations=CI","methodology":"Methodology: The rate of out-of-school adolescents allows to compare across countries with different population sizes. It shows the share of official lower secondary age adolescents who never attended school or dropped out to the population of official lower secondary school age.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator measures the proportion of the population within the official age range for a specific educational level who are not currently enrolled in school. The data aids in identifying these individuals to tailor targeted interventions and formulate effective policies, ensuring that all children have the opportunity to attend school. It encompasses children who have never attended school, those who may enroll at a later age, and those who have started education but did not continue to the expected age of completion for the specified level.","theme":"education","source_group":"wb"},{"code":"SE.SEC.UNER.LO.MA.ZS","name":"Adolescents non scolarisés, garçons ( % des garçons en âge de fréquenter le premier cycle de l'enseignement secondaire)","description":"Les adolescents non scolarisés représentent le pourcentage d’adolescents en âge de fréquenter l’école secondaire inférieure qui ne sont pas inscrit...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.UNER.LO.MA.ZS?locations=CI","methodology":"Methodology: The rate of out-of-school adolescents allows to compare across countries with different population sizes. It shows the share of official lower secondary age adolescents who never attended school or dropped out to the population of official lower secondary school age.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator measures the proportion of the population within the official age range for a specific educational level who are not currently enrolled in school. The data aids in identifying these individuals to tailor targeted interventions and formulate effective policies, ensuring that all children have the opportunity to attend school. It encompasses children who have never attended school, those who may enroll at a later age, and those who have started education but did not continue to the expected age of completion for the specified level.","theme":"education","source_group":"wb"},{"code":"SH.HIV.INCD.TL","name":"Adultes (15 ans et +) et enfants (0 à 14 ans) nouvellement infectés par le VIH","description":"Nombre d'adultes (âgés de 15 ans et plus) et d'enfants (âgés de 0 à 14 ans) nouvellement infectés par le VIH.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.HIV.INCD.TL?locations=CI","methodology":"Methodology: Methods for monitoring HIV incidence vary depending on the epidemic setting and are typically categorized as either direct or indirect measures. Direct measurement at a population level is preferred but often difficult to obtain. Consequently, most countries rely on indirect measures or a combination of both.\nDirect measurement strategies include longitudinal follow-up and repeat testing among individuals without HIV infection, as well as estimation using laboratory tests for recent HIV infection and clinical data. However, longitudinal monitoring is costly and complex, requiring nationally representative population-based surveys.\nIndirect methods frequently rely on estimates constructed from mathematical modeling tools, such as Spectrum or the AIDS Epidemic Model. These models incorporate geographical and population-specific HIV surveys, surveillance, case reporting, mortality, program and clinical data, and sometimes assumptions about risk behavior and HIV transmission. Countries may also triangulate these data with other sources, such as serial population-based HIV prevalence estimates or estimates of HIV prevalence in young, recently exposed populations.\nIt is important to note that case-based surveillance systems capturing newly reported HIV infections should not be used as a direct source for estimating the number of new infections in the reporting year due to reporting delays and underdiagnosis. However, this information can be useful for triangulation or validation purposes, especially when combined with tests for the recency of HIV infection.","theme":"sante","source_group":"wb"},{"code":"SH.HIV.INCD","name":"Adultes (âgés de 15 à 49 ans) nouvellement infectés par le VIH","description":"Nombre d'adultes (âgés de 15 à 49 ans) nouvellement infectés par le VIH.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.HIV.INCD?locations=CI","methodology":"Methodology: Methods for monitoring HIV incidence vary depending on the epidemic setting and are typically categorized as either direct or indirect measures. Direct measurement at a population level is preferred but often difficult to obtain. Consequently, most countries rely on indirect measures or a combination of both.\nDirect measurement strategies include longitudinal follow-up and repeat testing among individuals without HIV infection, as well as estimation using laboratory tests for recent HIV infection and clinical data. However, longitudinal monitoring is costly and complex, requiring nationally representative population-based surveys.\nIndirect methods frequently rely on estimates constructed from mathematical modeling tools, such as Spectrum or the AIDS Epidemic Model. These models incorporate geographical and population-specific HIV surveys, surveillance, case reporting, mortality, program and clinical data, and sometimes assumptions about risk behavior and HIV transmission. Countries may also triangulate these data with other sources, such as serial population-based HIV prevalence estimates or estimates of HIV prevalence in young, recently exposed populations.\nIt is important to note that case-based surveillance systems capturing newly reported HIV infections should not be used as a direct source for estimating the number of new infections in the reporting year due to reporting delays and underdiagnosis. However, this information can be useful for triangulation or validation purposes, especially when combined with tests for the recency of HIV infection.","theme":"sante","source_group":"wb"},{"code":"SP.POP.DPND","name":"Taux de dépendance des personnes âgées ( % de la population en âge de travailler)","description":"Le ratio de dépendance selon l'âge est le rapport entre les personnes à charge (personnes de moins de 15 ans ou de plus de 64 ans) et la population...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.DPND?locations=CI","methodology":"Methodology: Age dependency ratio is calculated as 100 x (Population (0-14) + Population (65+)) / Population (15-64). Data are shown as the proportion of dependents per 100 working-age population.\nStatistical concept(s): Dependency ratios capture variations in the proportions of children, elderly people, and working-age people in the population that imply the dependency burden that the working-age population bears in relation to children and the elderly. But dependency ratios show only the age composition of a population, not economic dependency. Some children and elderly people are part of the labor force, and many working-age people are not.\nAge structure in the World Bank's population estimates is based on the age structure in United Nations Population Division's World Population Prospects.","theme":"demo","source_group":"wb"},{"code":"SP.POP.DPND.OL","name":"Taux de dépendance des personnes âgées ( % de la population en âge de travailler)","description":"Le ratio de dépendance selon l'âge, vieux, est le rapport entre les personnes à charge plus âgées (les personnes de plus de 64 ans) et la populatio...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.DPND.OL?locations=CI","methodology":"Methodology: Age dependency ratio, old is calculated as 100 x (Population (65+)) / Population (15-64). Data are shown as the proportion of old dependents per 100 working-age population.\nStatistical concept(s): Dependency ratios capture variations in the proportions of children, elderly people, and working-age people in the population that imply the dependency burden that the working-age population bears in relation to children and the elderly. But dependency ratios show only the age composition of a population, not economic dependency. Some children and elderly people are part of the labor force, and many working-age people are not.\nAge structure in the World Bank's population estimates is based on the age structure in United Nations Population Division's World Population Prospects.","theme":"demo","source_group":"wb"},{"code":"SP.POP.DPND.YG","name":"Taux de dépendance des jeunes, jeunes ( % de la population en âge de travailler)","description":"Le taux de dépendance selon l'âge, jeune, est le rapport entre les personnes à charge plus jeunes (les personnes de moins de 15 ans) et la populati...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.DPND.YG?locations=CI","methodology":"Methodology: Age dependency ratio, young is calculated as 100 x (Population (0-14)) / Population (15-64). Data are shown as the proportion of young dependents per 100 working-age population.\nStatistical concept(s): Dependency ratios capture variations in the proportions of children, elderly people, and working-age people in the population that imply the dependency burden that the working-age population bears in relation to children and the elderly. But dependency ratios show only the age composition of a population, not economic dependency. Some children and elderly people are part of the labor force, and many working-age people are not.\nAge structure in the World Bank's population estimates is based on the age structure in United Nations Population Division's World Population Prospects.","theme":"demo","source_group":"wb"},{"code":"AG.LND.IRIG.AG.ZS","name":"Terres agricoles irriguées ( % de la superficie agricole totale)","description":"Les terres agricoles irriguées font référence aux zones agricoles volontairement alimentées en eau, y compris les terres irriguées par crues contrô...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.IRIG.AG.ZS?locations=CI","methodology":"Methodology: Irrigated agricultural area refers to area equipped to provide water (via artificial means of irrigation such as by diverting streams, flooding, or spraying) to the crops. In non-irrigated agricultural areas, production of crops is dependent on rain-fed irrigation. \nAgricultural land constitutes only a part of any country's total area, which can include areas not suitable for agriculture, such as forests, mountains, and inland water bodies. Agricultural land can also be classified as irrigated and non-irrigated land. In arid and semi-arid countries agriculture is often confined to irrigated land, with very little farming possible in non-irrigated areas.","theme":"primary","source_group":"wb"},{"code":"AG.LND.AGRI.ZS","name":"Terres agricoles ( % de la superficie)","description":"Les terres agricoles font référence à la part de la superficie des terres qui est arable, consacrée à des cultures permanentes et à des pâturages p...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.AGRI.ZS?locations=CI","methodology":"Methodology: Agriculture is still a major sector in many economies, and agricultural activities provide developing countries with food and revenue. But agricultural activities also can degrade natural resources. Poor farming practices can cause soil erosion and loss of soil fertility. Efforts to increase productivity by using chemical fertilizers, pesticides, and intensive irrigation have environmental costs and health impacts. Excessive use of chemical fertilizers can alter the chemistry of soil. Pesticide poisoning is common in developing countries. And salinization of irrigated land diminishes soil fertility. Thus, inappropriate use of inputs for agricultural production has far-reaching effects.\nAgricultural land is also sometimes classified as irrigated and non-irrigated land. In arid and semi-arid countries agriculture is often confined to irrigated land, with very little farming possible in non-irrigated areas. Land abandoned as a result of shifting cultivation is excluded from Arable land.\n\n\n\n\n\n\n\n\n\n\n\nData on agricultural land are valuable for conducting studies on a various perspectives concerning agricultural production, food security and for deriving cropping intensity among others uses. Agricultural land indicator, along with land-use indicators, can also elucidate the environmental sustainability of countries' agricultural practices.\n\n\n\n\n\n\n\n\n\n\n\nTotal land area does not include inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area.\nStatistical concept(s):","theme":"primary","source_group":"wb"},{"code":"AG.LND.AGRI.K2","name":"Terres agricoles (km²)","description":"Les terres agricoles font référence à la part de la superficie des terres qui est arable, consacrée à des cultures permanentes et à des pâturages p...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.AGRI.K2?locations=CI","methodology":"Methodology: Agricultural land constitutes only a part of any country's total area, which can include areas not suitable for agriculture, such as forests, mountains, and inland water bodies. Three components of the agricultural land are a) arable land - land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow, b) permanent pasture - land used for five or more years for forage, including natural and cultivated crops, and c) and under permanent crops - land cultivated with crops that occupy the land for long periods and need not be replanted after each harvest, such as cocoa, coffee, and rubber; land under flowering shrubs, fruit trees, nut trees, and vines is included, but land under trees grown for wood or timber is not.\nAgricultural land is also sometimes classified as irrigated and non-irrigated land. In arid and semi-arid countries agriculture is often confined to irrigated land, with very little farming possible in non-irrigated areas. Land abandoned as a result of shifting cultivation is excluded from arable land.\n\n\n\n\n\n\n\n\n\n\n\nData on agricultural land are valuable for conducting studies on a various perspectives concerning agricultural production, food security and for deriving cropping intensity among others uses. Agricultural land indicator, along with land-use indicators, can also elucidate the environmental sustainability of countries' agricultural practices.\nStatistical concept(s):","theme":"primary","source_group":"wb"},{"code":"TX.VAL.AGRI.ZS.UN","name":"Exportations de matières premières agricoles ( % des exportations de marchandises)","description":"Les matières premières agricoles comprennent la section 2 de la CTCI Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.AGRI.ZS.UN?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.AGRI.ZS.UN","name":"Importations de matières premières agricoles ( % des importations de marchandises)","description":"Les matières premières agricoles comprennent la section 2 de la CTCI Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.AGRI.ZS.UN?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"NV.AGR.TOTL.ZS","name":"Agriculture, sylviculture et pêche, valeur ajoutée ( % du PIB)","description":"L'agriculture, la sylviculture et la pêche correspondent aux divisions 01 à 03 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.AGR.TOTL.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"primary","source_group":"wb"},{"code":"NV.AGR.TOTL.KD.ZG","name":"Agriculture, sylviculture et pêche, valeur ajoutée (croissance annuelle en %)","description":"L'agriculture, la sylviculture et la pêche correspondent aux divisions 01 à 03 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.AGR.TOTL.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"primary","source_group":"wb"},{"code":"NV.AGR.TOTL.KD","name":"Agriculture, sylviculture et pêche, valeur ajoutée (en dollars constants de 2015)","description":"L'agriculture, la sylviculture et la pêche correspondent aux divisions 01 à 03 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.AGR.TOTL.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"primary","source_group":"wb"},{"code":"NV.AGR.TOTL.KN","name":"Agriculture, sylviculture et pêche, valeur ajoutée (UCL constantes)","description":"L'agriculture, la sylviculture et la pêche correspondent aux divisions 01 à 03 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.AGR.TOTL.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"primary","source_group":"wb"},{"code":"NV.AGR.TOTL.CN","name":"Agriculture, sylviculture et pêche, valeur ajoutée (UCL actuelles)","description":"L'agriculture, la sylviculture et la pêche correspondent aux divisions 01 à 03 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.AGR.TOTL.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"primary","source_group":"wb"},{"code":"NV.AGR.TOTL.CD","name":"Agriculture, sylviculture et pêche, valeur ajoutée (en dollars américains courants)","description":"L'agriculture, la sylviculture et la pêche correspondent aux divisions 01 à 03 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.AGR.TOTL.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"primary","source_group":"wb"},{"code":"NV.AGR.EMPL.KD","name":"Agriculture, sylviculture et pêche, valeur ajoutée par travailleur (en dollars constants de 2015)","description":"L'agriculture, la sylviculture et la pêche correspondent aux divisions 01 à 03 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.AGR.EMPL.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Value added per worker is calculated by dividing value added of a sector by the number employed in the sector.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"primary","source_group":"wb"},{"code":"IS.AIR.GOOD.MT.K1","name":"Transport aérien, fret (millions de tonnes-km)","description":"Le fret aérien est le volume de bagages de fret, express et diplomatiques transportés à chaque étape du vol (fonctionnement d'un avion du décollage...","source_link":"https://donnees.banquemondiale.org/indicateur/IS.AIR.GOOD.MT.K1?locations=CI","methodology":"Methodology: Freight tonne-kilometres equal the sum of the products obtained by multiplying the number of tonnes of freight, express, diplomatic bags carried on each flight stage by the stage distance. For ICAO statistical purposes freight includes express and diplomatic bags but not passenger baggage.\n\nThe air transport data represent the total (international and domestic) scheduled traffic carried by the air carriers registered in a country. Countries submit air transport data to International Civil Aviation Organization (ICAO) on the basis of standard instructions and definitions issued by ICAO. In many cases, however, the data include estimates by ICAO for nonreporting carriers. Where possible, these estimates are based on previous submissions supplemented by information published by the air carriers, such as flight schedules.\n\nThe data cover the air traffic carried on scheduled services, but changes in air transport regulations in Europe have made it more difficult to classify traffic as scheduled or nonscheduled. Thus, recent increases shown for some European countries may be due to changes in the classification of air traffic rather than actual growth. In the case of multinational air carriers owned by partner States, traffic within each partner State is shown separately as domestic and all other traffic as international. For countries with few air carriers or only one, the addition or discontinuation of a home-based air carrier may cause significant changes in air traffic.\n\nStatistical concept(s): Freight tonne-kilometres performed measures a metric tonne of freight carried one kilometre.","theme":"territory","source_group":"wb"},{"code":"IS.AIR.PSGR","name":"Transport aérien, passagers transportés","description":"Les passagers aériens transportés comprennent les passagers des avions nationaux et internationaux des transporteurs aériens enregistrés dans le pays.","source_link":"https://donnees.banquemondiale.org/indicateur/IS.AIR.PSGR?locations=CI","methodology":"Methodology: The number of passengers carried is obtained by counting each passenger on a particular flight (with one flight number) once only and not repeatedly on each individual stage of that flight, with a single exception that a passenger flying on both the international and domestic stages of the same flight should be counted as both a domestic and an international passenger.\n\nThe air transport data represent the total (international and domestic) scheduled traffic carried by the air carriers registered in a country. Countries submit air transport data to International Civil Aviation Organization (ICAO) on the basis of standard instructions and definitions issued by ICAO. In many cases, however, the data include estimates by ICAO for nonreporting carriers. Where possible, these estimates are based on previous submissions supplemented by information published by the air carriers, such as flight schedules.\n\nThe data cover the air traffic carried on scheduled services, but changes in air transport regulations in Europe have made it more difficult to classify traffic as scheduled or nonscheduled. Thus, recent increases shown for some European countries may be due to changes in the classification of air traffic rather than actual growth. In the case of multinational air carriers owned by partner States, traffic within each partner State is shown separately as domestic and all other traffic as international. For countries with few air carriers or only one, the addition or discontinuation of a home-based air carrier may cause significant changes in air traffic.\n\nStatistical concept(s): The number of passengers carried is obtained by counting each passenger on a particular flight (with one flight number) once only and not repeatedly on each individual stage of that flight, with a single exception that a passenger flying on both the international and domestic stages of the same flight should be counted as both a domestic and an international passenger.","theme":"territory","source_group":"wb"},{"code":"IS.AIR.DPRT","name":"Transport aérien, départs de transporteurs enregistrés dans le monde entier","description":"Les départs des transporteurs enregistrés dans le monde entier sont les décollages nationaux et les décollages à l'étranger des transporteurs aérie...","source_link":"https://donnees.banquemondiale.org/indicateur/IS.AIR.DPRT?locations=CI","methodology":"Methodology: The air transport data represent the total (international and domestic) scheduled traffic carried by the air carriers registered in a country. For statistical uses, departures are equal to the number of landings made or flight stages flown. A flight stage is the operation of an aircraft from take-off to its next landing. A flight stage is classified as either international or domestic. International flight stage is one or both terminals in the territory of a State, other than the State in which the air carrier has its principal place of business. \n\nThe air transport data represent the total (international and domestic) scheduled traffic carried by the air carriers registered in a country. Countries submit air transport data to International Civil Aviation Organization (ICAO) on the basis of standard instructions and definitions issued by ICAO. In many cases, however, the data include estimates by ICAO for nonreporting carriers. Where possible, these estimates are based on previous submissions supplemented by information published by the air carriers, such as flight schedules.\n\nThe data cover the air traffic carried on scheduled services, but changes in air transport regulations in Europe have made it more difficult to classify traffic as scheduled or nonscheduled. Thus, recent increases shown for some European countries may be due to changes in the classification of air traffic rather than actual growth. In the case of multinational air carriers owned by partner States, traffic within each partner State is shown separately as domestic and all other traffic as international. For countries with few air carriers or only one, the addition or discontinuation of a home-based air carrier may cause significant changes in air traffic.\n\nStatistical concept(s): Aircraft departures represent the number of take-offs of aircraft. For statistical purposes, departures are equal to the number of landings made or flight stages flown.","theme":"territory","source_group":"wb"},{"code":"EG.USE.COMM.CL.ZS","name":"Énergies alternatives et nucléaires ( % de la consommation totale d'énergie)","description":"L’énergie propre est une énergie non glucidique qui ne produit pas de dioxyde de carbone lorsqu’elle est générée.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.USE.COMM.CL.ZS?locations=CI","methodology":"Methodology: Energy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments.","theme":"secondary","source_group":"wb"},{"code":"ER.H2O.FWAG.ZS","name":"Prélèvements annuels d'eau douce, agriculture ( % du prélèvement total d'eau douce)","description":"Les prélèvements annuels d'eau douce font référence au total des prélèvements d'eau, sans compter les pertes par évaporation des bassins de stockage.","source_link":"https://donnees.banquemondiale.org/indicateur/ER.H2O.FWAG.ZS?locations=CI","methodology":"Methodology: This indicator measures the pressure on the renewable water resources of a country caused by irrigation. According to Commission on Sustainable Development (CSD) agriculture accounts for more than 70 percent of freshwater drawn from lakes, rivers and underground sources. Most is used for irrigation which provides about 40 percent of the world food production. Poor management has resulted in the salinization of about 20 percent of the world's irrigated land, with an additional 1.5 million ha affected annually.\nWater withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including for cooling thermoelectric plants).","theme":"territory","source_group":"wb"},{"code":"ER.H2O.FWDM.ZS","name":"Prélèvements annuels d'eau douce, intérieurs ( % du prélèvement total d'eau douce)","description":"Les prélèvements annuels d'eau douce font référence au total des prélèvements d'eau, sans compter les pertes par évaporation des bassins de stockage.","source_link":"https://donnees.banquemondiale.org/indicateur/ER.H2O.FWDM.ZS?locations=CI","methodology":"Methodology: Domestic water withdrawal, sometimes used interchangeably with municipal water withdrawal, focuses on human needs (drinking, cooking, cleaning, and sanitation). Data includes renewable freshwater resources, potential over-abstraction of renewable groundwater, withdrawal of fossil groundwater, and the potential use of desalinated water or treated wastewater. It is usually computed as the total water withdrawn by the public distribution network, and includes that part of the industries, which is connected to the municipal network. The ratio between the net consumption and the water withdrawn can vary from 5 to 15 percent in urban areas and from 10 to 50 percent in rural areas.\nWater withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes.","theme":"territory","source_group":"wb"},{"code":"ER.H2O.FWIN.ZS","name":"Prélèvements annuels d'eau douce, industrie ( % du prélèvement total d'eau douce)","description":"Les prélèvements annuels d'eau douce font référence au total des prélèvements d'eau, sans compter les pertes par évaporation des bassins de stockage.","source_link":"https://donnees.banquemondiale.org/indicateur/ER.H2O.FWIN.ZS?locations=CI","methodology":"Methodology: Annual industrial freshwater withdrawals include renewable water resources as well as potential over-abstraction of renewable groundwater or potential use of desalinated water or treated wastewater. It includes water for the cooling of thermoelectric plants, but it does not include hydropower.\nWater withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for industry are total withdrawals for direct industrial use (including withdrawals for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes.","theme":"territory","source_group":"wb"},{"code":"ER.H2O.FWTL.ZS","name":"Prélèvements annuels d'eau douce, total ( % des ressources internes)","description":"Les prélèvements annuels d'eau douce font référence au total des prélèvements d'eau, sans compter les pertes par évaporation des bassins de stockage.","source_link":"https://donnees.banquemondiale.org/indicateur/ER.H2O.FWTL.ZS?locations=CI","methodology":"Methodology: Annual freshwater withdrawals are total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes.","theme":"territory","source_group":"wb"},{"code":"ER.H2O.FWTL.K3","name":"Prélèvements annuels d'eau douce, total (milliards de mètres cubes)","description":"Les prélèvements annuels d'eau douce font référence au total des prélèvements d'eau, sans compter les pertes par évaporation des bassins de stockage.","source_link":"https://donnees.banquemondiale.org/indicateur/ER.H2O.FWTL.K3?locations=CI","methodology":"Methodology: Annual freshwater withdrawals are total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Water withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes.","theme":"territory","source_group":"wb"},{"code":"SI.SPR.PC40.ZG","name":"Taux de croissance moyen annualisé par habitant : consommation ou revenu moyen de l'enquête, 40 % inférieurs de la population ( %)","description":"Le taux de croissance de l’agrégat de bien-être des 40 % les plus pauvres est calculé comme le taux de croissance moyen annualisé de la consommatio...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.SPR.PC40.ZG?locations=CI","methodology":"Methodology: The annualized growth rate in per capita real survey mean consumption of the bottom 40% is computed in the following steps. First, obtain the mean consumption or income levels of the bottom 40% of the survey distribution in two different periods. The two survey data sets should be comparable - that is, they use a similar method of sampling, collecting data, and constructing the welfare aggregate. Second, the rate of change in the survey mean values of the bottom 40% is annualized.\nStatistical concept(s): The annualized growth rate in per capita real survey mean consumption or income of the bottom 40% measures the rate of change in per capita consumption or income of the bottom 40% in a year.","theme":"social","source_group":"wb"},{"code":"SI.SPR.PCAP.ZG","name":"Taux de croissance moyen annualisé par habitant : consommation ou revenu moyen de l'enquête, population totale ( %)","description":"Le taux de croissance de l'agrégat de bien-être de la population totale est calculé comme le taux de croissance moyen annualisé de la consommation ...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.SPR.PCAP.ZG?locations=CI","methodology":"Methodology: The annualized growth rate in per capita real survey mean consumption of the total population is computed in the following steps. First, obtain the mean consumption or income levels of the total population of the survey distribution in two different periods. The two survey data sets should be comparable - that is, they use a similar method of sampling, collecting data, and constructing the welfare aggregate. Second, the rate of change in the survey mean values of the total population is annualized.\nStatistical concept(s): The annualized growth rate in per capita real survey mean consumption or income measures the rate of change in per capita consumption or income changes in a year.","theme":"social","source_group":"wb"},{"code":"SH.HIV.ARTC.ZS","name":"Couverture de la thérapie antirétrovirale ( % de personnes vivant avec le VIH)","description":"La couverture du traitement antirétroviral indique le pourcentage de toutes les personnes vivant avec le VIH qui reçoivent un traitement antirétrov...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.HIV.ARTC.ZS?locations=CI","methodology":"Methodology: Data on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS.\nAntiretroviral therapy has led to huge reductions in death and suffering of people with advanced HIV infection.","theme":"sante","source_group":"wb"},{"code":"SH.HIV.PMTC.ZS","name":"Couverture de la thérapie antirétrovirale pour la PTME ( % de femmes enceintes vivant avec le VIH)","description":"Pourcentage de femmes enceintes séropositives qui reçoivent des médicaments antirétroviraux pour la prévention de la transmission mère-enfant (PTME).","source_link":"https://donnees.banquemondiale.org/indicateur/SH.HIV.PMTC.ZS?locations=CI","methodology":"Methodology: The coverage of antiretrovirals for PMTCT is calculated by dividing the number of pregnant women living with HIV who received antiretrovirals for PMTCT by the estimated number of pregnant women living with HIV who need antiretrovirals for PMTCT in the country. \nEstimating the Numerator: The number of pregnant women living with HIV receiving antiretrovirals for PMTCT is derived from national program data aggregated from facilities or other service delivery sites and reported by the country.\nEstimating the Denominator: The number of pregnant women living with HIV who need antiretroviral medicine for PMTCT is estimated using standardized statistical modeling based on UNAIDS/WHO methods. These methods consider various epidemic and demographic parameters, such as HIV prevalence among women of reproductive age, the effect of HIV on fertility, and national program coverage of antiretroviral therapy. These statistical modeling procedures provide a comprehensive population-based estimate of the number of pregnant women living with HIV who need antiretrovirals for PMTCT in the country.","theme":"sante","source_group":"wb"},{"code":"ER.FSH.AQUA.MT","name":"Production aquacole (tonnes métriques)","description":"L'aquaculture désigne l'élevage d'organismes aquatiques, notamment les poissons, les mollusques, les crustacés et les plantes aquatiques.","source_link":"https://donnees.banquemondiale.org/indicateur/ER.FSH.AQUA.MT?locations=CI","methodology":"Methodology: Aquaculture production specifically refers to output from aquaculture activities, which are designated for final harvest for consumption. At this time, harvest for ornamental purposes is not included.","theme":"primary","source_group":"wb"},{"code":"AG.LND.ARBL.ZS","name":"Terres arables ( % de la superficie)","description":"Les terres arables comprennent les terres définies par la FAO comme les terres consacrées à des cultures temporaires (les superficies en double cul...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.ARBL.ZS?locations=CI","methodology":"Methodology: Temporary fallow land refers to land left fallow for less than five years. The abandoned land resulting from shifting cultivation is not included in this category. Data for \"Arable land\" are not meant to indicate the amount of land that is potentially cultivable. Total land area does not include inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area. The data collected by the Food and Agriculture Organization (FAO) of the United Nations from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.","theme":"primary","source_group":"wb"},{"code":"AG.LND.ARBL.HA.PC","name":"Terres arables (hectares par personne)","description":"Les terres arables (hectares par personne) comprennent les terres définies par la FAO comme les terres consacrées à des cultures temporaires (les s...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.ARBL.HA.PC?locations=CI","methodology":"Methodology: Temporary fallow land refers to land left fallow for less than five years. The abandoned land resulting from shifting cultivation is not included in this category. Data for \"Arable land\" are not meant to indicate the amount of land that is potentially cultivable. The data collected by the Food and Agriculture Organization (FAO) of the United Nations from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.","theme":"primary","source_group":"wb"},{"code":"AG.LND.ARBL.HA","name":"Arable land (hectares)","description":"Les terres arables (en hectares) comprennent les terres définies par la FAO comme les terres en cultures temporaires (les superficies en double cul...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.ARBL.HA?locations=CI","methodology":"Methodology: Temporary fallow land refers to land left fallow for less than five years. The abandoned land resulting from shifting cultivation is not included in this category. Data for \"Arable land\" are not meant to indicate the amount of land that is potentially cultivable.","theme":"primary","source_group":"wb"},{"code":"SH.STA.ARIC.ZS","name":"Traitement de l'IRA ( % d'enfants de moins de 5 ans emmenés chez un prestataire de soins de santé)","description":"Les enfants atteints d'infection respiratoire aiguë (IRA) qui sont emmenés chez un prestataire de santé font référence au pourcentage d'enfants de ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.ARIC.ZS?locations=CI","methodology":"Methodology: Acute respiratory infection continues to be a leading cause of death among young children. Data are drawn mostly from household health surveys in which mothers report on number of episodes and treatment for acute respiratory infection.","theme":"sante","source_group":"wb"},{"code":"MS.MIL.TOTL.TF.ZS","name":"Personnel des forces armées ( % de la population active totale)","description":"Le personnel des forces armées est le personnel militaire en service actif, y compris les forces paramilitaires si la formation, l'organisation, l'...","source_link":"https://donnees.banquemondiale.org/indicateur/MS.MIL.TOTL.TF.ZS?locations=CI","methodology":"Methodology: Military data on manpower represent quantitative assessment of the personnel strengths of the world's armed forces. The numbers are based on the most accurate data available to, or, on the best estimate that can be made by the International Institute for Strategic Studies (IISS) at the time of its annual publication. The IISS collects the data from national governments.\n\nArmed forces personnel comprise all servicemen and women on full-time duty (including conscripts and long-term assignments from the Reserves). Reserve describes formations and units not fully manned or operational in peacetime, but which can be mobilized by recalling reservists in an emergency. IISS estimates of effective reservist strengths on the numbers available within five years of completing full-time service, unless there is good evidence that obligations are enforced for longer. Although paramilitary forces whose training, organization, equipment and control suggest they may be used to support or replace regular military forces, they are not included in the armed forces personnel. Home Guard units are counted as paramilitary.\n\nData are shown as percentage of total labor force. According to International Labour Organization (ILO armed forces occupations include all jobs held by members of the armed forces. Members of the armed forces are those personnel who are currently serving in the armed forces, including auxiliary services, whether on a voluntary or compulsory basis, and who are not free to accept civilian employment and are subject to military discipline. Included are regular members of the army, navy, air force and other military services, as well as conscripts enrolled for military training or other service for a specified period. Excluded are persons in civilian employment of government establishments concerned with defense issues; police (other than military police); customs inspectors and members of border or other armed civilian services; persons who have been temporarily withdrawn from civilian life for a short period of military training or retraining, according to national requirements, and members of military reserves not currently on active service.","theme":"politique","source_group":"wb"},{"code":"MS.MIL.TOTL.P1","name":"Personnel des forces armées, total","description":"Le personnel des forces armées est le personnel militaire en service actif, y compris les forces paramilitaires si la formation, l'organisation, l'...","source_link":"https://donnees.banquemondiale.org/indicateur/MS.MIL.TOTL.P1?locations=CI","methodology":"Methodology: Military data on manpower represent quantitative assessment of the personnel strengths of the world's armed forces. The IISS collects the data from a wide variety of sources. The numbers are based on the most accurate data available to, or on the best estimate that can be made by the International Institute for Strategic Studies (IISS) at the time of its annual publication. The current WDI indicator includes active armed forces and active paramilitary (but not reservists). Armed forces personnel comprise all servicemen and women on full-time duty, including conscripts and long-term assignments from the Reserves (“Reserve” describes formations and units not fully manned or operational in peacetime, but which can be mobilized by recalling reservists in an emergency). The indicator includes paramilitary forces. The source of the data (IISS) reports armed forces and paramilitary forces separately, however these figures are added for the purpose of computing this series. Home Guard units are counted as paramilitary.","theme":"politique","source_group":"wb"},{"code":"MS.MIL.XPRT.KD","name":"Exportations d'armes (valeurs des indicateurs de tendance du SIPRI)","description":"Les transferts (exportations) d’armes couvrent le volume des transferts d’armes majeures par le biais de ventes et de cadeaux, ainsi que ceux effec...","source_link":"https://donnees.banquemondiale.org/indicateur/MS.MIL.XPRT.KD?locations=CI","methodology":"Methodology: Stockholm International Peace Research Institute (SIPRI)'s Arms Transfers Program collects data on arms transfers from open sources. Since publicly available information is inadequate for tracking all weapons and other military equipment, SIPRI covers only what it terms major conventional weapons. Data cover the supply of weapons through sales, aid, gifts, and manufacturing licenses; therefore the term arms transfers rather than arms trade is used. SIPRI data also cover weapons supplied to or from rebel forces in an armed conflict as well as arms deliveries for which neither the supplier nor the recipient can be identified with acceptable certainty; these data are available in SIPRI's database.\nData cover major conventional weapons such as aircraft, armored vehicles, artillery, radar systems and other sensors, missiles, and ships designed for military use as well as some major components such as turrets for armored vehicles and engines. Excluded are other military equipment such as most small arms and light weapons, trucks, small artillery, ammunition, support equipment, technology transfers, and other services.\nWorld total includes arms transfers values for paramilitary groups.\nFor the method used for the SIPRI TIV see <https://www.sipri.org/databases/armstransfers/sources-and-methods>.","theme":"politique","source_group":"wb"},{"code":"MS.MIL.MPRT.KD","name":"Importations d'armes (valeurs des indicateurs de tendance du SIPRI)","description":"Les transferts (importations) d’armes couvrent le volume des transferts d’armes majeures par le biais de ventes et de cadeaux, ainsi que ceux effec...","source_link":"https://donnees.banquemondiale.org/indicateur/MS.MIL.MPRT.KD?locations=CI","methodology":"Methodology: Stockholm International Peace Research Institute (SIPRI)'s Arms Transfers Program collects data on arms transfers from open sources. Since publicly available information is inadequate for tracking all weapons and other military equipment, SIPRI covers only what it terms major conventional weapons. Data cover the supply of weapons through sales, aid, gifts, and manufacturing licenses; therefore the term arms transfers rather than arms trade is used. SIPRI data also cover weapons supplied to or from rebel forces in an armed conflict as well as arms deliveries for which neither the supplier nor the recipient can be identified with acceptable certainty; these data are available in SIPRI's database.\nData cover major conventional weapons such as aircraft, armored vehicles, artillery, radar systems and other sensors, missiles, and ships designed for military use as well as some major components such as turrets for armored vehicles and engines. Excluded are other military equipment such as most small arms and light weapons, trucks, small artillery, ammunition, support equipment, technology transfers, and other services.\nWorld total includes arms transfers values for paramilitary groups.\nFor the method used for the SIPRI TIV see <https://www.sipri.org/databases/armstransfers/sources-and-methods>.","theme":"politique","source_group":"wb"},{"code":"SM.POP.ASYS.EA","name":"Demandeurs d'asile par pays ou territoire d'asile","description":"Les demandeurs d'asile sont des personnes qui ont demandé une protection internationale et dont les demandes de statut de réfugié n'ont pas encore ...","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.ASYS.EA?locations=CI","methodology":"Methodology: Data collection on asylum-seekers is primarily handled through administrative records maintained by national authorities responsible for processing asylum claims. These records capture various stages of the asylum process, including the number of new applications, repeat applications, and cases that are pending resolution.\n\n\n\nThe methodology for collecting asylum-seeker data is guided by the International Recommendations on Refugee Statistics (IRRS), which provide standardized guidelines for data collection and reporting. These guidelines aim to ensure that data on asylum-seekers is comparable across different countries and regions, facilitating a coherent global understanding of asylum trends. The IRRS recommends that data be disaggregated by key variables such as the stage of the asylum process, the demographic characteristics of applicants, and the country of origin.","theme":"demo","source_group":"wb"},{"code":"SM.POP.ASYS.EO","name":"Demandeurs d'asile par pays ou territoire d'origine","description":"Les demandeurs d'asile sont des personnes qui ont demandé une protection internationale et dont les demandes de statut de réfugié n'ont pas encore ...","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.ASYS.EO?locations=CI","methodology":"Methodology: Data collection on asylum-seekers is primarily handled through administrative records maintained by national authorities responsible for processing asylum claims. These records capture various stages of the asylum process, including the number of new applications, repeat applications, and cases that are pending resolution.\n\n\n\nThe methodology for collecting asylum-seeker data is guided by the International Recommendations on Refugee Statistics (IRRS), which provide standardized guidelines for data collection and reporting. These guidelines aim to ensure that data on asylum-seekers is comparable across different countries and regions, facilitating a coherent global understanding of asylum trends. The IRRS recommends that data be disaggregated by key variables such as the stage of the asylum process, the demographic characteristics of applicants, and the country of origin.","theme":"demo","source_group":"wb"},{"code":"FB.ATM.TOTL.P5","name":"Guichets automatiques bancaires (GAB) (pour 100 000 adultes)","description":"Les guichets automatiques bancaires (DAB) sont des appareils électromécaniques qui permettent aux clients des institutions financières d'effectuer ...","source_link":"https://donnees.banquemondiale.org/indicateur/FB.ATM.TOTL.P5?locations=CI","methodology":"Methodology: Data are shown as the total number of ATMs for every 100,000 adults in the reporting country. Calculated as (number of ATMs)*100,000/adult population in the reporting country.\nStatistical concept(s):  Data are shown as the total number of ATMs for every 100,000 adults in the reporting country. Calculated as (number of ATMs)*100,000/adult population in the reporting country.","theme":"tertiary","source_group":"wb"},{"code":"AG.LND.PRCP.MM","name":"Précipitations moyennes en profondeur (mm par an)","description":"Les précipitations moyennes sont la moyenne à long terme en profondeur (dans l’espace et dans le temps) des précipitations annuelles dans le pays.","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.PRCP.MM?locations=CI","methodology":"Methodology: Estimation of Areal Precipitation\nA single point precipitation measurement is quite often not representative of the volume of precipitation falling over a given catchment area. A dense network of point measurements and/or radar estimates can provide a better representation of the true volume over a given area. A network of precipitation measurements is converted to areal estimates using the arithmentic mean. This technique calculates areal precipitation using the arithmetic mean of all the point or areal measurements considered in the analysis.","theme":"primary","source_group":"wb"},{"code":"IC.CUS.DURS.EX","name":"Délai moyen de dédouanement des exportations (jours)","description":"Nombre moyen de jours pour dédouaner les exportations directes.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.CUS.DURS.EX?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.CUS.DURS.IM","name":"Délai moyen de dédouanement des importations (jours)","description":"Délai moyen, en jours, qu'il faut à un établissement pour pouvoir réclamer les marchandises importées à la douane, à partir de leur arrivée au poin...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.CUS.DURS.IM?locations=CI","methodology":"Since 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"SI.RMT.COST.OB.ZS","name":"Coût de transaction moyen pour l'envoi de fonds depuis un pays spécifique ( %)","description":"Le coût de transaction moyen de l'envoi de fonds depuis un pays spécifique est la moyenne du coût total de transaction en pourcentage du montant en...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.RMT.COST.OB.ZS?locations=CI","methodology":"Methodology: The World Bank calculates and tracks the global average cost for sending remittances following each iteration of Remittance Prices Worldwide (RPW). This is intended to provide a tool to track the trend of remittance prices by various policy makers, including measuring progress towards the commitment by the G8 member countries to reduce the cost of remittances by five percentage points over five years (the “5x5 Objective”), as well as the commitment by the G20 member countries to also reduce the global average to 5 percent. The Global Average Total Cost is calculated as the average total cost for sending USD 200 with all remittance service providers (RSPs) worldwide. In other terms, the global average total cost is the simple average of the total cost for sending USD 200 charged by each single RSP included in the RPW database, expressed as the percentage of the amount sent. The regional and national average total costs are calculated using the same methodology used to calculate the Global Average Total Cost. These represent the simple average total cost for sending USD 200 with every single RSP from a specific region of the world (regional), or from a specific country (national). The same applies to other averages such as the G8 average, which calculates the average cost of sending USD 200 from the G8 member countries, or the bank average, which represent the average cost of sending USD 200 with a bank worldwide. The reference years reflect third quarter data here; for example, data for 2016 refers to data in the third quarter of the year. For all quarterly data, visit http://remittanceprices.worldbank.org.","theme":"inter","source_group":"wb"},{"code":"SI.RMT.COST.IB.ZS","name":"Coût de transaction moyen pour l'envoi d'envois de fonds vers un pays spécifique ( %)","description":"Le coût de transaction moyen de l'envoi de fonds vers un pays spécifique est la moyenne du coût total de transaction en pourcentage du montant envo...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.RMT.COST.IB.ZS?locations=CI","methodology":"Methodology: The World Bank calculates and tracks the global average cost for sending remittances following each iteration of Remittance Prices Worldwide (RPW). This is intended to provide a tool to track the trend of remittance prices by various policy makers, including measuring progress towards the commitment by the G8 member countries to reduce the cost of remittances by five percentage points over five years (the “5x5 Objective”), as well as the commitment by the G20 member countries to also reduce the global average to 5 percent. The Global Average Total Cost is calculated as the average total cost for sending USD 200 with all remittance service providers (RSPs) worldwide. In other terms, the global average total cost is the simple average of the total cost for sending USD 200 charged by each single RSP included in the RPW database, expressed as the percentage of the amount sent. The regional and national average total costs are calculated using the same methodology used to calculate the Global Average Total Cost. These represent the simple average total cost for sending USD 200 with every single RSP to a specific region of the world (regional), or to a specific country (national). The reference years reflect third quarter data here; for example, data for 2016 refers to data in the third quarter of the year. For all quarterly data, visit http://remittanceprices.worldbank.org.","theme":"inter","source_group":"wb"},{"code":"SL.TLF.0714.SW.TM","name":"Durée moyenne du travail des enfants, études et travail, 7-14 ans (heures par semaine)","description":"La durée moyenne de travail des enfants qui étudient et travaillent fait référence à la durée hebdomadaire moyenne de travail des enfants qui fréqu...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.SW.TM?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.SW.FE.TM","name":"Durée moyenne du travail des enfants, études et travail, femmes, 7-14 ans (heures par semaine)","description":"La durée moyenne de travail des enfants qui étudient et travaillent fait référence à la durée hebdomadaire moyenne de travail des enfants qui fréqu...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.SW.FE.TM?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.SW.MA.TM","name":"Durée moyenne du travail des enfants, études et travail, hommes, 7-14 ans (heures par semaine)","description":"La durée moyenne de travail des enfants qui étudient et travaillent fait référence à la durée hebdomadaire moyenne de travail des enfants qui fréqu...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.SW.MA.TM?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.WK.TM","name":"Durée moyenne du travail des enfants, travaillant uniquement, âgés de 7 à 14 ans (heures par semaine)","description":"La durée moyenne de travail des enfants qui travaillent uniquement fait référence à la durée hebdomadaire moyenne de travail des enfants qui partic...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.WK.TM?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.WK.FE.TM","name":"Durée moyenne du travail des enfants, travaillant uniquement, femmes, âgés de 7 à 14 ans (heures par semaine)","description":"La durée moyenne de travail des enfants qui travaillent uniquement fait référence à la durée hebdomadaire moyenne de travail des enfants qui partic...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.WK.FE.TM?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.WK.MA.TM","name":"Durée moyenne du travail des enfants, hommes de sexe masculin, âgés de 7 à 14 ans (heures par semaine)","description":"La durée moyenne de travail des enfants qui travaillent uniquement fait référence à la durée hebdomadaire moyenne de travail des enfants qui partic...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.WK.MA.TM?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"FB.BNK.CAPA.ZS","name":"Ratio fonds propres des banques sur actifs ( %)","description":"L'indicateur est une mesure de l'adéquation des fonds propres qui évalue la solidité financière des institutions de dépôt en comparant les fonds pr...","source_link":"https://donnees.banquemondiale.org/indicateur/FB.BNK.CAPA.ZS?locations=CI","methodology":"Methodology: The ratio is calculated by dividing Tier 1 capital by total assets, expressed as a percentage. Tier 1 capital should be measured in accordance with the Basel regulatory framework as adopted by national supervisory authorities, ensuring consistency with international standards. Total assets are recorded at gross book value and include all financial and non-financial assets, without deduction for provisions, write-downs, or collateral. The data are compiled on a consolidated basis, typically using the cross-border, cross-sector, domestically incorporated consolidation approach (CBCSDI), which includes all relevant financial entities under common control, regardless of location or legal form.\nStatistical concept(s): The Tier 1 Capital to Assets ratio is a core financial soundness indicator that assesses the capital adequacy and financial resilience of deposit takers by measuring the proportion of high-quality, loss-absorbing capital relative to their total balance sheet size. Tier 1 capital, often referred to as core capital, comprises components such as common equity, retained earnings, and other instruments that meet Basel criteria for being fully available to cover losses.","theme":"tertiary","source_group":"wb"},{"code":"FD.RES.LIQU.AS.ZS","name":"Ratio réserves de liquidités bancaires par rapport aux actifs bancaires ( %)","description":"Le ratio des réserves liquides des banques par rapport aux actifs bancaires est le rapport entre les avoirs en monnaie nationale et les dépôts aupr...","source_link":"https://donnees.banquemondiale.org/indicateur/FD.RES.LIQU.AS.ZS?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FB.AST.NPER.ZS","name":"Prêts non performants bancaires par rapport au total des prêts bruts ( %)","description":"L’indicateur mesure la proportion du portefeuille de prêts d’une institution de dépôt qui est déprécié ou présentant un risque de défaut.","source_link":"https://donnees.banquemondiale.org/indicateur/FB.AST.NPER.ZS?locations=CI","methodology":"Methodology: The ratio is calculated by dividing the value of non-performing loans (NPLs) by the total value of gross loans, expressed as a percentage. Both NPLs and total gross loans should be reported at their gross book value, meaning before any deductions for provisions, write-offs, or collateral. Gross loans include all outstanding loans on the balance sheet, including those classified as non-performing. The classification of NPLs should be based on either quantitative criteria (e.g., days past due) or qualitative assessments (e.g., evidence of financial difficulties), following supervisory standards aligned with Basel guidance. Data should be compiled using a consistent consolidation basis, typically the cross-border, cross-sector, domestically incorporated consolidation approach (CBCSDI), to ensure comparability across reporting entities and jurisdictions. \nStatistical concept(s): The Non-performing Loans (NPLs) to Total Gross Loans ratio is a core indicator of asset quality within the banking sector. It measures the proportion of a deposit taker’s loan portfolio that is impaired or at significant risk of default. A loan is classified as non-performing when payments of principal or interest are overdue by 90 days or more, or when it is assessed that full repayment is unlikely without the realization of collateral, even if the loan is not yet past due. Data are submitted by national authorities to the IMF following the Financial Soundness Indicators (FSI) Compilation Guide.","theme":"tertiary","source_group":"wb"},{"code":"VC.BTL.DETH","name":"Décès liés aux combats (nombre de personnes)","description":"Les décès liés aux batailles sont les décès survenus dans des conflits liés aux batailles entre les parties belligérantes de la dyade du conflit (d...","source_link":"https://donnees.banquemondiale.org/indicateur/VC.BTL.DETH?locations=CI","methodology":"Methodology: During warfare, targets are usually the military and its installations or state institutions and state representatives, but there is often substantial collateral damage of civilians killed in crossfire, indiscriminate bombings, and other military activities. All deaths - civilian as well as military - incurred in such situations are counted as battle-related deaths.","theme":"politique","source_group":"wb"},{"code":"per_si_allsi.ben_q1_tot","name":"Incidence des prestations des programmes d'assurance sociale pour le quintile le plus pauvre ( % du total des prestations d'assurance sociale)","description":"L'incidence des prestations des programmes d'assurance sociale sur le quintile le plus pauvre montre le pourcentage du total des prestations d'assu...","source_link":"https://donnees.banquemondiale.org/indicateur/per_si_allsi.ben_q1_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_allsp.ben_q1_tot","name":"Incidence des prestations de la protection sociale et des programmes de travail pour le quintile le plus pauvre ( % du total des prestations SPL)","description":"L'incidence des prestations des programmes de protection sociale et du travail (SPL) pour le quintile le plus pauvre montre le pourcentage du total...","source_link":"https://donnees.banquemondiale.org/indicateur/per_allsp.ben_q1_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_sa_allsa.ben_q1_tot","name":"Incidence des avantages des programmes de protection sociale pour le quintile le plus pauvre ( % du total des prestations de protection sociale)","description":"L'incidence des bénéfices des programmes de filet de sécurité sociale pour le quintile le plus pauvre montre le pourcentage du total des bénéfices ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_sa_allsa.ben_q1_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_lm_alllm.ben_q1_tot","name":"Incidence des prestations de chômage et de la MPT dans le quintile le plus pauvre (en % du total des prestations U/MTPM)","description":"L'incidence des prestations de chômage et des programmes actifs du marché du travail (PAMT) pour le quintile le plus pauvre montre le pourcentage d...","source_link":"https://donnees.banquemondiale.org/indicateur/per_lm_alllm.ben_q1_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"TM.TAX.MRCH.BC.ZS","name":"Couverture des reliures, tous les produits ( %)","description":"La couverture des consolidations est le pourcentage de lignes de produits bénéficiant d'un taux consolidé convenu.","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.MRCH.BC.ZS?locations=CI","methodology":"Methodology: This indicator is calculated as the proportion of tariff lines for all products that are bound under World Trade Organization (WTO) commitments. A tariff line is considered bound if a maximum rate is legally committed in the WTO schedule of concessions. The binding coverage is computed by dividing the number of bound tariff lines by the total number of tariff lines in the relevant product category and multiplying the result by 100 to express it as a percentage. Binding coverage is the percentage of product lines with an agreed bound rate. Bound rates result from trade negotiations incorporated into a country's schedule of concessions and are thus enforceable. Tariff data are primarily sourced from the World Trade Organization (WTO) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. The indicator is compiled using only officially reported bound statuses without imputation. It is methodologically consistent across countries, with tariff line concordance procedures applied to standardize classification and maintain comparability across HS revisions.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.MANF.BC.ZS","name":"Couverture des liaisons, produits manufacturés ( %)","description":"La couverture des consolidations est le pourcentage de lignes de produits bénéficiant d'un taux consolidé convenu.","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.MANF.BC.ZS?locations=CI","methodology":"Methodology: This indicator is calculated as the proportion of tariff lines for manufactured products that are bound under World Trade Organization (WTO) commitments. A tariff line is considered bound if a maximum rate is legally committed in the WTO schedule of concessions. The binding coverage is computed by dividing the number of bound tariff lines by the total number of tariff lines in the relevant product category and multiplying the result by 100 to express it as a percentage. Binding coverage is the percentage of product lines with an agreed bound rate. Bound rates result from trade negotiations incorporated into a country's schedule of concessions and are thus enforceable. Manufactured products are commodities classified in Standard International Trade Classification (SITC) revision 3 sections 5-8 excluding division 68. Tariff data are primarily sourced from the World Trade Organization (WTO) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. The indicator is compiled using only officially reported bound statuses without imputation. It is methodologically consistent across countries, with tariff line concordance procedures applied to standardize classification and maintain comparability across HS revisions.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.TCOM.BC.ZS","name":"Couverture de liaison, produits primaires ( %)","description":"La couverture des consolidations est le pourcentage de lignes de produits bénéficiant d'un taux consolidé convenu.","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.TCOM.BC.ZS?locations=CI","methodology":"Methodology: This indicator is calculated as the proportion of tariff lines for primary products that are bound under World Trade Organization (WTO) commitments. A tariff line is considered bound if a maximum rate is legally committed in the WTO schedule of concessions. The binding coverage is computed by dividing the number of bound tariff lines by the total number of tariff lines in the relevant product category and multiplying the result by 100 to express it as a percentage. Binding coverage is the percentage of product lines with an agreed bound rate. Bound rates result from trade negotiations incorporated into a country's schedule of concessions and are thus enforceable. Primary products are commodities classified in Standard International Trade Classification (SITC) revision 3 sections 0-4 plus division 68 (nonferrous metals). Tariff data are primarily sourced from the World Trade Organization (WTO) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. The indicator is compiled using only officially reported bound statuses without imputation. It is methodologically consistent across countries, with tariff line concordance procedures applied to standardize classification and maintain comparability across HS revisions.","theme":"inter","source_group":"wb"},{"code":"EN.BIR.THRD.NO","name":"Espèces d'oiseaux, menacées","description":"Les oiseaux sont répertoriés pour les pays inclus dans leurs aires de reproduction ou d'hivernage.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.BIR.THRD.NO?locations=CI","methodology":"Methodology: Species assessed as Critically Endangered (CR), Endangered (EN) or Vulnerable (VU) are referred to as \"threatened\" species. The International Union for Conservation of Nature (IUCN) Red List of Threatened Species collects and disseminates information on the global threated species.\nProportion of threatened species is only reported for the more completely evaluated groups (i.e., >90% of species evaluated). Also, the reported percentage of threatened species for each group is presented as a best estimate within a range of possible values bounded by lower and upper estimates:\nLower estimate = % threatened extant species if all Data Deficient species are not threatened, i.e., (CR + EN + VU) / (total assessed - EX)\nBest estimate = % threatened extant species if Data Deficient species are equally threatened as data sufficient species, i.e., (CR + EN + VU) / (total assessed - EX - DD)\nUpper estimate = % threatened extant species if all Data Deficient species are threatened, i.e., (CR + EN + VU + DD) / (total assessed - EX)\nAdditional information on ecology and habitat preferences, threats, and conservation action are also collated and assessed as part of Red List process.","theme":"territory","source_group":"wb"},{"code":"SP.DYN.CBRT.IN","name":"Taux de natalité, brut (pour 1 000 personnes)","description":"Le taux brut de natalité indique le nombre de naissances vivantes survenues au cours de l'année, pour 1 000 habitants, estimé au milieu de l'année.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.CBRT.IN?locations=CI","methodology":"Methodology: The crude birth rate is calculated as the number of births in a given period divided by the average population in that period. For human populations the period is usually one year and, if the population changes in size over the year, the divisor is taken as the population at the mid-year. The rate is usually expressed in terms of 1,000 people: for example, a crude birth rate of 9.5 (per 1000 people) in a population of 1 million would imply 9500 births per year in the entire population.\nStatistical concept(s): Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration. Vital rates are based on data from birth and death registration systems, censuses, and sample surveys by national statistical offices and other organizations, or on demographic analysis. Data for the most recent year for some high-income countries are provisional estimates based on vital registers. The estimates for many other countries are from the United Nations Population Division.","theme":"demo","source_group":"wb"},{"code":"SH.STA.BRTC.ZS","name":"Accouchements assistés par du personnel de santé qualifié ( % du total)","description":"Les accouchements assistés par du personnel de santé qualifié correspondent au pourcentage d'accouchements assistés par du personnel formé pour don...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.BRTC.ZS?locations=CI","methodology":"Methodology: National-level household surveys are the primary sources for collecting data on skilled health personnel providing childbirth care. These surveys include Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), Reproductive Health Surveys (RHS), and other national surveys based on similar methodologies. Respondents in these surveys are asked about their last live birth and who assisted during delivery, covering a period of up to five years before the interview.\nAs part of the data harmonization process and interaction with countries, UNICEF conducts an annual country consultation. During this consultation, SDG country focal points are contacted to update and verify values included in the database and to obtain new data sources. These new data sources are reviewed and assessed jointly with WHO. Additionally, the national categories or occupational titles of skilled health personnel are verified. The reported data for some countries may include additional categories of trained personnel beyond doctors, nurses, and midwives.","theme":"sante","source_group":"wb"},{"code":"FB.CBK.BRWR.P3","name":"Emprunteurs auprès des banques commerciales (pour 1 000 adultes)","description":"Les emprunteurs auprès des banques commerciales correspondent au nombre déclaré de clients résidents qui sont des sociétés non financières (publiqu...","source_link":"https://donnees.banquemondiale.org/indicateur/FB.CBK.BRWR.P3?locations=CI","methodology":"Methodology: Number of borrowers refers to the number of resident nonfinancial corporations (public and private) and individuals in the household sector that have obtained credit (loans) from each type of financial institution.\n\n• A corporate entity must be counted as one borrower, irrespective of the number of loans extended to that corporate borrower.\n• An individual from the household sector must be counted as one borrower, irrespective of the number of loan accounts held.\n• If a loan is extended to a group of borrowers, all borrowers must be counted individually rather than as one borrower.\n\nStatistical concept(s): Borrowers from commercial banks denotes the total number of resident customers that are nonfinancial corporations (public and private) and households who obtained loans from commercial banks for every 1,000 adults in the reporting country. It is calculated as (number of borrowers)*1,000/adult population in the reporting country.","theme":"tertiary","source_group":"wb"},{"code":"TM.TAX.MRCH.BR.ZS","name":"Taux consolidé, moyenne simple, tous les produits ( %)","description":"Le taux consolidé moyen simple est la moyenne non pondérée de toutes les lignes de la liste tarifaire dans lesquelles des taux consolidés ont été f...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.MRCH.BR.ZS?locations=CI","methodology":"Methodology: This indicator represents the unweighted average of final bound tariff rates across all all products tariff lines. The calculation involves summing the bound rates applied to each individual tariff line and dividing by the total number of lines within the product category. Simple mean bound rate is the unweighted average of all the lines in the tariff schedule in which bound rates have been set. Bound rates result from trade negotiations incorporated into a country's schedule of concessions and are thus enforceable. Tariff data are primarily sourced from the World Trade Organization (World Trade Organization (WTO)) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. The indicator reflects commitments under WTO agreements and is not adjusted for trade volume. It includes only those lines for which binding rates have been reported. The methodology ensures consistency across countries by converting national tariff submissions to a harmonized HS version.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.MANF.BR.ZS","name":"Taux consolidé, moyenne simple, produits manufacturés ( %)","description":"Le taux consolidé moyen simple est la moyenne non pondérée de toutes les lignes de la liste tarifaire dans lesquelles des taux consolidés ont été f...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.MANF.BR.ZS?locations=CI","methodology":"Methodology: This indicator represents the unweighted average of final bound tariff rates across all manufactured products tariff lines. The calculation involves summing the bound rates applied to each individual tariff line and dividing by the total number of lines within the product category. Simple mean bound rate is the unweighted average of all the lines in the tariff schedule in which bound rates have been set. Bound rates result from trade negotiations incorporated into a country's schedule of concessions and are thus enforceable. Manufactured products are commodities classified in Standard International Trade Classification (SITC) revision 3 sections 5-8 excluding division 68. Tariff data are primarily sourced from the World Trade Organization (World Trade Organization (WTO)) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. The indicator reflects commitments under WTO agreements and is not adjusted for trade volume. It includes only those lines for which binding rates have been reported. The methodology ensures consistency across countries by converting national tariff submissions to a harmonized HS version.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.TCOM.BR.ZS","name":"Taux consolidé, moyenne simple, produits primaires ( %)","description":"Le taux consolidé moyen simple est la moyenne non pondérée de toutes les lignes de la liste tarifaire dans lesquelles des taux consolidés ont été f...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.TCOM.BR.ZS?locations=CI","methodology":"Methodology: This indicator represents the unweighted average of final bound tariff rates across all primary products tariff lines. The calculation involves summing the bound rates applied to each individual tariff line and dividing by the total number of lines within the product category. Simple mean bound rate is the unweighted average of all the lines in the tariff schedule in which bound rates have been set. Bound rates result from trade negotiations incorporated into a country's schedule of concessions and are thus enforceable. Primary products are commodities classified in Standard International Trade Classification (SITC) revision 3 sections 0-4 plus division 68 (nonferrous metals). Tariff data are primarily sourced from the World Trade Organization (World Trade Organization (WTO)) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. The indicator reflects commitments under WTO agreements and is not adjusted for trade volume. It includes only those lines for which binding rates have been reported. The methodology ensures consistency across countries by converting national tariff submissions to a harmonized HS version.","theme":"inter","source_group":"wb"},{"code":"IC.BRE.BE.P1","name":"B-READY : Entrée d'entreprise Pilier 1 : Qualité de la réglementation pour l'entrée d'entreprise","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.BE.P1?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.BE.P2","name":"B-READY : Entrée des entreprises Pilier 2 : Services publics numériques et transparence de l'information pour l'entrée des entreprises","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.BE.P2?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.BE.P3","name":"B-READY : Entrée dans l'entreprise Pilier 3 : Efficacité opérationnelle de l'entrée dans l'entreprise","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.BE.P3?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.BE.OS","name":"B-READY : Entrée d'entreprise : Note globale","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.BE.OS?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.BI.P1","name":"B-READY : Insolvabilité des entreprises Pilier 1 : Qualité de la réglementation des procédures judiciaires d'insolvabilité","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.BI.P1?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.BI.P2","name":"B-READY : Insolvabilité des entreprises Pilier 2 : Qualité de l'infrastructure institutionnelle et opérationnelle pour les procédures judiciaires d'insolvabilité","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.BI.P2?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.BI.P3","name":"B-READY : Insolvabilité des entreprises Pilier 3 : Efficacité opérationnelle de la résolution des procédures judiciaires d'insolvabilité","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.BI.P3?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.BI.OS","name":"B-READY : Insolvabilité d'entreprise : score global","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.BI.OS?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.BL.P1","name":"B-READY : Implantation d'entreprises Pilier 1 : Qualité de la réglementation relative à l'implantation d'entreprises","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.BL.P1?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.BL.P2","name":"B-READY : Implantation d'entreprises Pilier 2 : Qualité des services publics et transparence de l'information pour l'implantation d'entreprises","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.BL.P2?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.BL.P3","name":"B-READY : Siège d'entreprise Pilier 3 : Efficacité opérationnelle de l'établissement d'un site d'établissement","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.BL.P3?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.BL.OS","name":"B-READY : Emplacement de l'entreprise : Note globale","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.BL.OS?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.DR.P1","name":"B-READY : Règlement des litiges Pilier 1 : Qualité des réglementations pour le règlement des litiges","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.DR.P1?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.DR.P2","name":"B-READY : Règlement des différends Pilier 2 : Services publics pour le règlement des différends","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.DR.P2?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.DR.P3","name":"B-READY : Règlement des litiges Pilier 3 : Facilité de résolution d'un litige commercial","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.DR.P3?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.DR.OS","name":"B-READY : Résolution des litiges : Note globale","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.DR.OS?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.FS.P1","name":"B-READY : Services financiers Pilier 1 : Qualité de la réglementation des services financiers","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.FS.P1?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.FS.P2","name":"B-READY : Services financiers Pilier 2 : Accessibilité de l'information dans les infrastructures de crédit","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.FS.P2?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.FS.P3","name":"B-READY : Services financiers Pilier 3 : Efficacité opérationnelle de la réception de services financiers","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.FS.P3?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.FS.OS","name":"B-READY : Services financiers : Note globale","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.FS.OS?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.IT.P1","name":"B-READY : Commerce international Pilier 1 : Qualité de la réglementation du commerce international","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.IT.P1?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.IT.P2","name":"B-READY : Commerce international Pilier 2 : Qualité des services publics pour la facilitation du commerce international","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.IT.P2?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.IT.P3","name":"B-READY : Commerce international Pilier 3 : Efficacité de l'importation et de l'exportation de biens et de la participation au commerce numérique","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.IT.P3?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.IT.OS","name":"B-READY : Commerce international : Note globale","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.IT.OS?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.LB.P1","name":"B-READY : Pilier Travail 1 : Qualité de la réglementation du travail","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.LB.P1?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.LB.P2","name":"B-READY : Pilier 2 du travail : Adéquation des services publics pour le travail","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.LB.P2?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.LB.P3","name":"B-READY : Pilier 3 du travail : Efficacité opérationnelle de la réglementation du travail et des services publics dans la pratique","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.LB.P3?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.LB.OS","name":"B-READY : Main-d'œuvre : Note globale","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.LB.OS?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.MC.P1","name":"B-READY : Concurrence sur le marché Pilier 1 : Qualité des réglementations qui favorisent la concurrence sur le marché","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.MC.P1?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.MC.P2","name":"B-READY : Concurrence sur le marché Pilier 2 : Des services publics qui favorisent la concurrence sur le marché","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.MC.P2?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.MC.P3","name":"B-READY : Concurrence sur le marché Pilier 3 : Mise en œuvre de services clés favorisant la concurrence sur le marché","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.MC.P3?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.MC.OS","name":"B-READY : Marché Concurrence : Note globale","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.MC.OS?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.P1.RF","name":"B-READY : Pilier 1 : Cadre réglementaire","description":"B-READY évalue l’environnement des affaires de l’économie en se concentrant sur le cadre réglementaire et la fourniture des services publics associ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.P1.RF?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.P2.PS","name":"B-READY : Pilier 2 : Services publics","description":"B-READY évalue l’environnement des affaires de l’économie en se concentrant sur le cadre réglementaire et la fourniture des services publics associ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.P2.PS?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.P3.OE","name":"B-READY : Pilier 3 : Efficacité opérationnelle","description":"B-READY évalue l’environnement des affaires de l’économie en se concentrant sur le cadre réglementaire et la fourniture des services publics associ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.P3.OE?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.TX.P1","name":"B-READY : Fiscalité Pilier 1 : Qualité de la réglementation fiscale","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.TX.P1?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.TX.P2","name":"B-READY : Pilier fiscal 2 : Services publics fournis par l'administration fiscale","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.TX.P2?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.TX.P3","name":"B-READY : Pilier 3 fiscal : Efficacité opérationnelle des systèmes fiscaux dans la pratique","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.TX.P3?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.TX.OS","name":"B-READY : Fiscalité : Note globale","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.TX.OS?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.US.P1","name":"B-READY : Services publics Pilier 1 : Qualité de la réglementation sur les services publics","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.US.P1?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.US.P2","name":"B-READY : Services de services publics Pilier 2 : Qualité de la gouvernance et transparence des services de services publics","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.US.P2?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.US.P3","name":"B-READY : Services d'utilité Pilier 3 : Efficacité opérationnelle de la fourniture de services d'utilité","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.US.P3?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.BRE.US.OS","name":"B-READY : Services utilitaires : Note globale","description":"B-READY se concentre sur dix sujets organisés en fonction du cycle de vie de l'entreprise et de sa participation au marché lors de l'ouverture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BRE.US.OS?locations=CI","methodology":"Methodology: B-READY is designed for benchmarking across economies. This requires the application of a homogeneous methodology across economies at different income levels and in different geographic locations. It also requires quantifying the business environment conditions using indicators that can be aggregated into comparable scores.  \nB-READY granular data provide a wealth of information that can be used to guide specific policy reform. These data are presented in the main body of the report and, in more detail, in the Business Ready website through accessible facilities and tools, including economy profiles.  \nBased on the data collected, B-READY generates scores for each topic area and potentially a set of aggregate scores. B-READY collects both de jure information and de facto measures. While de jure data are collected from expert consultations, de facto data are collected from both expert consultations and firm surveys.\nAll data obtained from either experts or firms are collected in raw form and then converted to a score that can be combined with other scores. The objective of the scoring methodology of raw data is to allow for score aggregation that preserves absolute cardinal differences, which can be used to compare across economies and over time (rather than purely ordinal or relative scoring). The granular data produced by the B-READY project are combined to produce a score for each of the ten B-READY topics. Every topic score will be generated by averaging the scores assigned to each of the three pillars (regulatory framework, public services, and efficiency) for that topic.\nIn addition, to facilitate international benchmarking, these granular data are used to obtain topic-specific pillar scores, topic scores, and overall pillar scores. A topic-specific pillar score is built from the points assigned to sets of indicators, organized in categories by subject matter. Each score can range from 0 to 100 (where 100 represents the best performance). Within each topic, there are three topic-specific pillars: Regulatory Framework, Public Services, and Operational Efficiency. The average of the three topic-specific pillar scores, in turn, equals the topic score. Each overall pillar score is the average of the corresponding topic-specific pillar scores across the ten B-READY topics. \nDetails about the B-READY methodology are available on the project website: https://www.worldbank.org/en/businessready/methodology#1","theme":"business","source_group":"wb"},{"code":"IC.FRM.BRIB.ZS","name":"Incidence de la corruption ( % d'entreprises ayant fait l'objet d'au moins une demande de paiement de pots-de-vin)","description":"Pourcentage d'entreprises ayant reçu au moins une demande de paiement de pots-de-vin dans le cadre de 6 transactions publiques traitant de l'accès ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.BRIB.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"FM.LBL.BMNY.GD.ZS","name":"Monnaie au sens large ( % du PIB)","description":"La monnaie au sens large est la somme de tous les instruments financiers liquides détenus par les secteurs détenteurs de monnaie qui sont largement...","source_link":"https://donnees.banquemondiale.org/indicateur/FM.LBL.BMNY.GD.ZS?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FM.LBL.BMNY.CN","name":"Monnaie au sens large (LCU actuelle)","description":"La monnaie au sens large est la somme de tous les instruments financiers liquides détenus par les secteurs détenteurs de monnaie qui sont largement...","source_link":"https://donnees.banquemondiale.org/indicateur/FM.LBL.BMNY.CN?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FM.LBL.BMNY.ZG","name":"Monnaie au sens large (croissance annuelle en %)","description":"La monnaie au sens large est la somme de tous les instruments financiers liquides détenus par les secteurs détenteurs de monnaie qui sont largement...","source_link":"https://donnees.banquemondiale.org/indicateur/FM.LBL.BMNY.ZG?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FM.LBL.BMNY.IR.ZS","name":"Rapport entre la masse monétaire au sens large et le total des réserves","description":"La monnaie au sens large est la somme de tous les instruments financiers liquides détenus par les secteurs détenteurs de monnaie qui sont largement...","source_link":"https://donnees.banquemondiale.org/indicateur/FM.LBL.BMNY.IR.ZS?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"ER.FSH.CAPT.MT","name":"Production des pêches de capture (tonnes métriques)","description":"La production des pêches de capture mesure le volume de captures de poisson débarquées par un pays à toutes fins commerciales, industrielles, récré...","source_link":"https://donnees.banquemondiale.org/indicateur/ER.FSH.CAPT.MT?locations=CI","methodology":"Methodology: Information on capture production is collected annually from relevant national offices concerned with fishery statistics, by means of a system of standardized forms, which list for each country the relative species items and fishing areas breakdown.\nIn the case of some \"aquatic products\", data are also obtained from trade associations or other specialized international organizations to which data are also submitted. In this way the statistics are reviewed by subject matter specialists.\nData concerning the nominal catch of certain major groups are generally reviewed in collaboration with the regional agency concerned. For example, for ISSCAAP group 36 (Tunas, bonitos and billfishes) data provided by the national correspondents are often replaced by the \"best scientific estimates\" produced by regional bodies collecting tuna catch statistics (i.e. ICCAT, IOTC, SPC and IATTC.)\nSee https://www.fao.org/fishery/en/collection/capture","theme":"primary","source_group":"wb"},{"code":"EN.GHG.CO2.ZG.AR5","name":"Émissions de dioxyde de carbone (CO2) (total), à l'exclusion de l'UTCATF (variation en % par rapport à 1990)","description":"Variation des émissions (en %) de l'année en cours par rapport aux émissions de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) d...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.ZG.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.MT.CE.AR5","name":"Émissions de dioxyde de carbone (CO2) (totales) à l'exclusion de l'UTCATF (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) de Kyoto, provenant des secteurs de l'agric...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.PC.CE.AR5","name":"Émissions de dioxyde de carbone (CO2) hors UTCATF par habitant (t CO2e/habitant)","description":"Émissions annuelles totales de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) de Kyoto, provenant des secteurs de l'agriculture,...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.PC.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.AG.MT.CE.AR5","name":"Émissions de dioxyde de carbone (CO2) de l'agriculture (Mt CO2e)","description":"Une mesure des émissions annuelles de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) de Kyoto, provenant du secteur agricole.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.AG.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.BU.MT.CE.AR5","name":"Émissions de dioxyde de carbone (CO2) provenant du bâtiment (énergie) (Mt CO2e)","description":"Une mesure des émissions annuelles de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) de Kyoto, du secteur du bâtiment (sous-sect...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.BU.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.FE.MT.CE.AR5","name":"Émissions de dioxyde de carbone (CO2) provenant des émissions fugitives (énergie) (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) de Kyoto, provenant des émissions fugitives...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.FE.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.IC.MT.CE.AR5","name":"Émissions de dioxyde de carbone (CO2) provenant de la combustion industrielle (énergie) (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) de Kyoto, provenant de la combustion indust...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.IC.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.IP.MT.CE.AR5","name":"Émissions de dioxyde de carbone (CO2) provenant des procédés industriels (Mt CO2e)","description":"Une mesure des émissions annuelles de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) de Kyoto, provenant des processus industrie...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.IP.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.PI.MT.CE.AR5","name":"Émissions de dioxyde de carbone (CO2) de l'industrie de l'électricité (énergie) (Mt CO2e)","description":"Une mesure des émissions annuelles de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) de Kyoto, provenant de la production d'élec...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.PI.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.TR.MT.CE.AR5","name":"Émissions de dioxyde de carbone (CO2) provenant des transports (énergie) (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) de Kyoto, du secteur des transports (sous-s...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.TR.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.WA.MT.CE.AR5","name":"Émissions de dioxyde de carbone (CO2) provenant des déchets (Mt CO2e)","description":"Une mesure des émissions annuelles de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) de Kyoto, provenant du secteur des déchets.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.WA.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.LU.DF.MT.CE.AR5","name":"Flux nets de dioxyde de carbone (CO2) provenant de l'UTCATF - Déforestation (Mt CO2e)","description":"Flux net de dioxyde de carbone (CO2) dans la catégorie « Déforestation ».","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.LU.DF.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.LU.FL.MT.CE.AR5","name":"Flux nets de dioxyde de carbone (CO2) provenant de l'UTCATF - Terres forestières (Mt CO2e)","description":"Flux net de dioxyde de carbone (CO2) dans la catégorie « Terres forestières ».","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.LU.FL.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.LU.OS.MT.CE.AR5","name":"Flux nets de dioxyde de carbone (CO2) provenant de l'UTCATF - Sol organique (Mt CO2e)","description":"Flux net de dioxyde de carbone (CO2) dans la catégorie « Sols organiques ».","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.LU.OS.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.LU.OL.MT.CE.AR5","name":"Flux nets de dioxyde de carbone (CO2) provenant de l'UTCATF - Autres terres (Mt d'équivalent CO2)","description":"Flux net de dioxyde de carbone (CO2) dans la catégorie « Autres terres ».","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.LU.OL.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.LU.MT.CE.AR5","name":"Flux nets de dioxyde de carbone (CO2) provenant de l'UTCATF - Total à l'exclusion des incendies non tropicaux (Mt d'équivalents en CO2)","description":"Flux net de dioxyde de carbone (CO2) provenant de l'utilisation des terres, du changement d'affectation des terres et de la foresterie UTCATF, à l'...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.LU.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.RT.GDP.PP.KD","name":"Intensité carbone du PIB (kg d'équivalent CO2 par dollar PPA de 2021)","description":"Émissions annuelles de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) de Kyoto, provenant des secteurs de l'agriculture, de l'én...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.RT.GDP.PP.KD?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CO2.RT.GDP.KD","name":"Intensité carbone du PIB (kg d'équivalent CO2 par dollar américain constant de PIB de 2021)","description":"Émissions annuelles de dioxyde de carbone (CO2), l'un des six gaz à effet de serre (GES) de Kyoto, provenant des secteurs de l'agriculture, de l'én...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CO2.RT.GDP.KD?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"SH.DTH.COMM.ZS","name":"Causes de décès, selon les maladies transmissibles et les affections maternelles, prénatales et nutritionnelles ( % du total)","description":"La cause du décès fait référence à la part de tous les décès, tous âges confondus, par causes sous-jacentes.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DTH.COMM.ZS?locations=CI","methodology":"Methodology: Data on cause of death are compiled by the WHO, based mainly on data from national vital registry systems, as well as sample registration systems, population laboratories, and epidemiological analysis of specific conditions. Data are classified based on the International Statistical Classification of Diseases and Related Health Problems, 10th revision. Data have been carefully analyzed to take into account incomplete coverage of vital registration and the likely differences in cause of death patterns that would be expected in undercovered and often poorer subpopulations. Special attention has also been paid to misattribution or miscoding of causes of death in cardiovascular diseases, cancer, injuries, and general ill-defined categories. For further information, consult the original source.","theme":"sante","source_group":"wb"},{"code":"SH.DTH.INJR.ZS","name":"Causes de décès, par blessure ( % du total)","description":"La cause du décès fait référence à la part de tous les décès, tous âges confondus, par causes sous-jacentes.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DTH.INJR.ZS?locations=CI","methodology":"Methodology: Data on cause of death are compiled by the WHO, based mainly on data from national vital registry systems, as well as sample registration systems, population laboratories, and epidemiological analysis of specific conditions. Data are classified based on the International Statistical Classification of Diseases and Related Health Problems, 10th revision. Data have been carefully analyzed to take into account incomplete coverage of vital registration and the likely differences in cause of death patterns that would be expected in under-covered and often poorer subpopulations. Special attention has also been paid to misattribution or miscoding of causes of death in cardiovascular diseases, cancer, injuries, and general ill-defined categories. For further information, consult the original source.","theme":"sante","source_group":"wb"},{"code":"SH.DTH.NCOM.ZS","name":"Causes de décès, par maladies non transmissibles ( % du total)","description":"La cause du décès fait référence à la part de tous les décès, tous âges confondus, par causes sous-jacentes.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DTH.NCOM.ZS?locations=CI","methodology":"Methodology: Data on cause of death are compiled by the WHO, based mainly on data from national vital registry systems, as well as sample registration systems, population laboratories, and epidemiological analysis of specific conditions. Data are classified based on the International Statistical Classification of Diseases and Related Health Problems, 10th revision. Data have been carefully analyzed to take into account incomplete coverage of vital registration and the likely differences in cause of death patterns that would be expected in undercovered and often poorer subpopulations. Special attention has also been paid to misattribution or miscoding of causes of death in cardiovascular diseases, cancer, injuries, and general ill-defined categories. For further information, consult the original source.","theme":"sante","source_group":"wb"},{"code":"GC.DOD.TOTL.GD.ZS","name":"Dette de l'administration centrale, totale ( % du PIB)","description":"La dette est l’ensemble des obligations contractuelles directes à durée déterminée du gouvernement envers d’autres, impayées à une date donnée.","source_link":"https://donnees.banquemondiale.org/indicateur/GC.DOD.TOTL.GD.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.DOD.TOTL.CN","name":"Dette de l'administration centrale, totale (LCU courante)","description":"La dette est l’ensemble des obligations contractuelles directes à durée déterminée du gouvernement envers d’autres, impayées à une date donnée.","source_link":"https://donnees.banquemondiale.org/indicateur/GC.DOD.TOTL.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"AG.PRD.CREL.MT","name":"Production céréalière (tonnes)","description":"Les données sur la production céréalière concernent uniquement les cultures récoltées pour les céréales sèches.","source_link":"https://donnees.banquemondiale.org/indicateur/AG.PRD.CREL.MT?locations=CI","methodology":"Methodology: A cereal is a grass cultivated for the edible components of their grain, composed of the endosperm, germ, and bran. Cereal grains are grown in greater quantities and provide more food energy worldwide than any other type of crop; cereal crops therefore can also be called staple crops. Cereals production data relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded. The Food and Agriculture Organization (FAO) allocates production data to the calendar year in which the bulk of the harvest took place. Most of a crop harvested near the end of a year will be used in the following year.","theme":"primary","source_group":"wb"},{"code":"AG.YLD.CREL.KG","name":"Rendement céréalier (kg par hectare)","description":"Le rendement céréalier, mesuré en kilogrammes par hectare de terre récoltée, comprend le blé, le riz, le maïs, l'orge, l'avoine, le seigle, le mill...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.YLD.CREL.KG?locations=CI","methodology":"Methodology: A cereal is a grass cultivated for the edible components of their grain, composed of the endosperm, germ, and bran. Cereal yield is measured as kilograms per hectare of harvested land. Cereal grains are grown in greater quantities and provide more food energy worldwide than any other type of crop; cereal crops therefore can also be called staple crops Cereals production includes wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded.","theme":"primary","source_group":"wb"},{"code":"NE.GDI.STKB.KN","name":"Variations des stocks (UCM constantes)","description":"Les variations de stocks correspondent à la valeur des entrées en stocks diminuée de la valeur des sorties et de la valeur des éventuelles pertes r...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.STKB.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.STKB.CN","name":"Variations des stocks (UCL courantes)","description":"Les variations de stocks correspondent à la valeur des entrées en stocks diminuée de la valeur des sorties et de la valeur des éventuelles pertes r...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.STKB.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.STKB.CD","name":"Variations des stocks (en dollars américains courants)","description":"Les variations de stocks correspondent à la valeur des entrées en stocks diminuée de la valeur des sorties et de la valeur des éventuelles pertes r...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.STKB.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"BM.GSR.ROYL.CD","name":"Frais pour l'utilisation de la propriété intellectuelle, paiements (BoP, $ US courants)","description":"Frais pour l'utilisation des droits de propriété (tels que les brevets, les marques, les droits d'auteur, les procédés et dessins industriels, y co...","source_link":"https://donnees.banquemondiale.org/indicateur/BM.GSR.ROYL.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BX.GSR.ROYL.CD","name":"Frais pour l'utilisation de la propriété intellectuelle, recettes (BdP, $ US courants)","description":"Frais pour l'utilisation des droits de propriété (tels que les brevets, les marques, les droits d'auteur, les procédés et dessins industriels, y co...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GSR.ROYL.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"NV.MNF.CHEM.ZS.UN","name":"Produits chimiques ( % de la valeur ajoutée dans l'industrie manufacturière)","description":"La fabrication de produits chimiques et de produits chimiques comprend les industries classées dans la division 24 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.MNF.CHEM.ZS.UN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"SL.AGR.0714.ZS","name":"Emploi des enfants dans l'agriculture ( % des enfants actifs âgés de 7 à 14 ans)","description":"L'emploi par activité économique fait référence à la répartition des enfants économiquement actifs selon les principales catégories industrielles d...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.AGR.0714.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.AGR.0714.FE.ZS","name":"Emploi des enfants dans l'agriculture, femmes ( % des enfants de sexe féminin âgés de 7 à 14 ans)","description":"L'emploi par activité économique fait référence à la répartition des enfants économiquement actifs selon les principales catégories industrielles d...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.AGR.0714.FE.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.AGR.0714.MA.ZS","name":"Emploi des enfants dans l'agriculture, hommes ( % des enfants de sexe masculin économiquement actifs âgés de 7 à 14 ans)","description":"L'emploi par activité économique fait référence à la répartition des enfants économiquement actifs selon les principales catégories industrielles d...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.AGR.0714.MA.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.MNF.0714.ZS","name":"Emploi des enfants dans l'industrie manufacturière ( % des enfants actifs âgés de 7 à 14 ans)","description":"L'emploi par activité économique fait référence à la répartition des enfants économiquement actifs selon les principales catégories industrielles d...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.MNF.0714.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.MNF.0714.FE.ZS","name":"Emploi des enfants dans l'industrie manufacturière, femmes ( % des enfants de sexe féminin âgés de 7 à 14 ans)","description":"L'emploi par activité économique fait référence à la répartition des enfants économiquement actifs selon les principales catégories industrielles d...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.MNF.0714.FE.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.MNF.0714.MA.ZS","name":"Emploi des enfants dans l'industrie manufacturière (en % des enfants de sexe masculin âgés de 7 à 14 ans)","description":"L'emploi par activité économique fait référence à la répartition des enfants économiquement actifs selon les principales catégories industrielles d...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.MNF.0714.MA.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.SRV.0714.ZS","name":"Emploi des enfants dans les services ( % des enfants économiquement actifs âgés de 7 à 14 ans)","description":"L'emploi par activité économique fait référence à la répartition des enfants économiquement actifs selon les principales catégories industrielles d...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.SRV.0714.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.SRV.0714.FE.ZS","name":"Emploi des enfants dans les services, femmes ( % des enfants économiquement actifs âgés de 7 à 14 ans)","description":"L'emploi par activité économique fait référence à la répartition des enfants économiquement actifs selon les principales catégories industrielles d...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.SRV.0714.FE.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SL.SRV.0714.MA.ZS","name":"Emploi des enfants dans les services, hommes ( % des enfants de sexe masculin économiquement actifs âgés de 7 à 14 ans)","description":"L'emploi par activité économique fait référence à la répartition des enfants économiquement actifs selon les principales catégories industrielles d...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.SRV.0714.MA.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).","theme":"emploi","source_group":"wb"},{"code":"SH.HIV.0014","name":"Enfants (0-14) vivant avec le VIH","description":"Les enfants vivant avec le VIH font référence au nombre d’enfants âgés de 0 à 14 ans infectés par le VIH.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.HIV.0014?locations=CI","methodology":"Methodology: HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable.\nData on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates.","theme":"sante","source_group":"wb"},{"code":"SH.HIV.INCD.14","name":"Enfants (âgés de 0 à 14 ans) nouvellement infectés par le VIH","description":"Nombre d'enfants (âgés de 0 à 14 ans) nouvellement infectés par le VIH.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.HIV.INCD.14?locations=CI","methodology":"Methodology: Methods for monitoring HIV incidence vary depending on the epidemic setting and are typically categorized as either direct or indirect measures. Direct measurement at a population level is preferred but often difficult to obtain. Consequently, most countries rely on indirect measures or a combination of both.\nDirect measurement strategies include longitudinal follow-up and repeat testing among individuals without HIV infection, as well as estimation using laboratory tests for recent HIV infection and clinical data. However, longitudinal monitoring is costly and complex, requiring nationally representative population-based surveys.\nIndirect methods frequently rely on estimates constructed from mathematical modeling tools, such as Spectrum or the AIDS Epidemic Model. These models incorporate geographical and population-specific HIV surveys, surveillance, case reporting, mortality, program and clinical data, and sometimes assumptions about risk behavior and HIV transmission. Countries may also triangulate these data with other sources, such as serial population-based HIV prevalence estimates or estimates of HIV prevalence in young, recently exposed populations.\nIt is important to note that case-based surveillance systems capturing newly reported HIV infections should not be used as a direct source for estimating the number of new infections in the reporting year due to reporting delays and underdiagnosis. However, this information can be useful for triangulation or validation purposes, especially when combined with tests for the recency of HIV infection.","theme":"sante","source_group":"wb"},{"code":"SL.TLF.0714.FE.ZS","name":"Enfants ayant un emploi, sexe féminin ( % des filles âgées de 7 à 14 ans)","description":"Les enfants occupés font référence aux enfants impliqués dans une activité économique pendant au moins une heure au cours de la semaine de référenc...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.FE.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.MA.ZS","name":"Enfants ayant un emploi, garçons ( % des enfants de sexe masculin âgés de 7 à 14 ans)","description":"Les enfants occupés font référence aux enfants impliqués dans une activité économique pendant au moins une heure au cours de la semaine de référenc...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.MA.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.SLF.0714.ZS","name":"Enfants ayant un emploi, travailleurs indépendants ( % d'enfants ayant un emploi, âgés de 7 à 14 ans)","description":"Les travailleurs indépendants sont des personnes dont la rémunération dépend directement des bénéfices tirés des biens et services qu'ils produisen...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.SLF.0714.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.SLF.0714.FE.ZS","name":"Enfants ayant un emploi, travailleurs indépendants, filles ( % d'enfants de sexe féminin ayant un emploi, âgés de 7 à 14 ans)","description":"Les travailleurs indépendants sont des personnes dont la rémunération dépend directement des bénéfices tirés des biens et services qu'ils produisen...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.SLF.0714.FE.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.SLF.0714.MA.ZS","name":"Enfants ayant un emploi, travailleurs indépendants, hommes ( % d'enfants de sexe masculin ayant un emploi, âgés de 7 à 14 ans)","description":"Les travailleurs indépendants sont des personnes dont la rémunération dépend directement des bénéfices tirés des biens et services qu'ils produisen...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.SLF.0714.MA.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.SW.ZS","name":"Enfants ayant un emploi, étudiant ou travaillant ( % d'enfants ayant un emploi, âgés de 7 à 14 ans)","description":"Les enfants occupés font référence aux enfants impliqués dans une activité économique pendant au moins une heure au cours de la semaine de référenc...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.SW.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.SW.FE.ZS","name":"Enfants ayant un emploi, étudiant ou travaillant, de sexe féminin ( % d'enfants de sexe féminin ayant un emploi, âgés de 7 à 14 ans)","description":"Les enfants occupés font référence aux enfants impliqués dans une activité économique pendant au moins une heure au cours de la semaine de référenc...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.SW.FE.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.SW.MA.ZS","name":"Enfants ayant un emploi, étudiant ou travaillant, garçons ( % d'enfants de sexe masculin ayant un emploi, âgés de 7 à 14 ans)","description":"Les enfants occupés font référence aux enfants impliqués dans une activité économique pendant au moins une heure au cours de la semaine de référenc...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.SW.MA.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.ZS","name":"Enfants ayant un emploi, total ( % des enfants âgés de 7 à 14 ans)","description":"Les enfants occupés font référence aux enfants impliqués dans une activité économique pendant au moins une heure au cours de la semaine de référenc...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.FAM.0714.ZS","name":"Enfants ayant un emploi, travailleurs familiaux non rémunérés ( % d'enfants ayant un emploi, âgés de 7 à 14 ans)","description":"Les travailleurs familiaux non rémunérés sont des personnes qui travaillent sans rémunération dans un établissement axé sur le marché et géré par u...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.FAM.0714.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.FAM.0714.FE.ZS","name":"Enfants ayant un emploi, aides familiales non rémunérées, femmes ( % d'enfants de sexe féminin ayant un emploi, âgés de 7 à 14 ans)","description":"Les travailleurs familiaux non rémunérés sont des personnes qui travaillent sans rémunération dans un établissement axé sur le marché et géré par u...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.FAM.0714.FE.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.FAM.0714.MA.ZS","name":"Enfants ayant un emploi, travailleurs familiaux non rémunérés, hommes ( % des enfants de sexe masculin ayant un emploi, âgés de 7 à 14 ans)","description":"Les travailleurs familiaux non rémunérés sont des personnes qui travaillent sans rémunération dans un établissement axé sur le marché et géré par u...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.FAM.0714.MA.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.WAG.0714.ZS","name":"Enfants ayant un emploi, travailleurs salariés ( % d'enfants ayant un emploi, âgés de 7 à 14 ans)","description":"Les salariés (également appelés employés) sont des personnes titulaires de contrats de travail explicites (écrits ou oraux) ou implicites prévoyant...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.WAG.0714.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.WAG.0714.FE.ZS","name":"Enfants ayant un emploi, salariés, filles ( % d'enfants de sexe féminin ayant un emploi, âgés de 7 à 14 ans)","description":"Les salariés (également appelés employés) sont des personnes titulaires de contrats de travail explicites (écrits ou oraux) ou implicites prévoyant...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.WAG.0714.FE.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.WAG.0714.MA.ZS","name":"Enfants ayant un emploi, travailleurs salariés, garçons ( % d'enfants de sexe masculin ayant un emploi, âgés de 7 à 14 ans)","description":"Les salariés (également appelés employés) sont des personnes titulaires de contrats de travail explicites (écrits ou oraux) ou implicites prévoyant...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.WAG.0714.MA.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.WK.ZS","name":"Enfants ayant un emploi, travaillant uniquement ( % d'enfants ayant un emploi, âgés de 7 à 14 ans)","description":"Les enfants occupés font référence aux enfants impliqués dans une activité économique pendant au moins une heure au cours de la semaine de référenc...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.WK.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.WK.FE.ZS","name":"Enfants ayant un emploi, travaillant uniquement, de sexe féminin ( % d'enfants de sexe féminin ayant un emploi, âgés de 7 à 14 ans)","description":"Les enfants occupés font référence aux enfants impliqués dans une activité économique pendant au moins une heure au cours de la semaine de référenc...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.WK.FE.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.0714.WK.MA.ZS","name":"Enfants ayant un emploi, travaillant uniquement, garçons ( % d'enfants de sexe masculin ayant un emploi, âgés de 7 à 14 ans)","description":"Les enfants occupés font référence aux enfants impliqués dans une activité économique pendant au moins une heure au cours de la semaine de référenc...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.0714.WK.MA.ZS?locations=CI","methodology":"Methodology: Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of \"economic activity,\" the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).\n\nHousehold survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).\n\nIn line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called \"household chores\") - that is, the production of domestic and personal services by household members for a household's own consumption.\n\nCountry surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.","theme":"emploi","source_group":"wb"},{"code":"SE.PRM.UNER.ZS","name":"Enfants non scolarisés ( % de l'âge de l'école primaire)","description":"Les enfants non scolarisés représentent le pourcentage d’enfants en âge d’aller à l’école primaire qui ne sont pas inscrits à l’école primaire ou s...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.UNER.ZS?locations=CI","methodology":"Methodology: The rate of out-of-school children allows to compare across countries with different population sizes. It shows the share of official primary-school-age children who never attended school or dropped out to the population of official primary school age.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator measures the proportion of the population within the official age range for a specific educational level who are not currently enrolled in school. The data aids in identifying these individuals to tailor targeted interventions and formulate effective policies, ensuring that all children have the opportunity to attend school. It encompasses children who have never attended school, those who may enroll at a later age, and those who have started education but did not continue to the expected age of completion for the specified level.","theme":"education","source_group":"wb"},{"code":"SE.PRM.UNER.FE.ZS","name":"Enfants non scolarisés, filles ( % des filles en âge de fréquenter l'école primaire)","description":"Les enfants non scolarisés représentent le pourcentage d’enfants en âge d’aller à l’école primaire qui ne sont pas inscrits à l’école primaire ou s...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.UNER.FE.ZS?locations=CI","methodology":"Methodology: The rate of out-of-school children allows to compare across countries with different population sizes. It shows the share of official primary-school-age children who never attended school or dropped out to the population of official primary school age.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator measures the proportion of the population within the official age range for a specific educational level who are not currently enrolled in school. The data aids in identifying these individuals to tailor targeted interventions and formulate effective policies, ensuring that all children have the opportunity to attend school. It encompasses children who have never attended school, those who may enroll at a later age, and those who have started education but did not continue to the expected age of completion for the specified level.","theme":"education","source_group":"wb"},{"code":"SE.PRM.UNER.MA.ZS","name":"Enfants non scolarisés, garçons ( % des garçons en âge de fréquenter l'école primaire)","description":"Les enfants non scolarisés représentent le pourcentage d’enfants en âge d’aller à l’école primaire qui ne sont pas inscrits à l’école primaire ou s...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.UNER.MA.ZS?locations=CI","methodology":"Methodology: The rate of out-of-school children allows to compare across countries with different population sizes. It shows the share of official primary-school-age children who never attended school or dropped out to the population of official primary school age.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator measures the proportion of the population within the official age range for a specific educational level who are not currently enrolled in school. The data aids in identifying these individuals to tailor targeted interventions and formulate effective policies, ensuring that all children have the opportunity to attend school. It encompasses children who have never attended school, those who may enroll at a later age, and those who have started education but did not continue to the expected age of completion for the specified level.","theme":"education","source_group":"wb"},{"code":"SE.PRM.UNER","name":"Enfants non scolarisés, primaire","description":"Les enfants non scolarisés correspondent au nombre d’enfants en âge d’aller à l’école primaire qui ne sont pas inscrits à l’école primaire ou secon...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.UNER?locations=CI","methodology":"Methodology: The number of out-of-school children is calculated by subtracting the number of primary school-age children enrolled in primary or secondary school from the total population of the official primary school-age children. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator measures the proportion of the population within the official age range for a specific educational level who are not currently enrolled in school. The data aids in identifying these individuals to tailor targeted interventions and formulate effective policies, ensuring that all children have the opportunity to attend school. It encompasses children who have never attended school, those who may enroll at a later age, and those who have started education but did not continue to the expected age of completion for the specified level.","theme":"education","source_group":"wb"},{"code":"SE.PRM.UNER.FE","name":"Enfants non scolarisés, primaires, filles","description":"Les enfants non scolarisés correspondent au nombre d’enfants en âge d’aller à l’école primaire qui ne sont pas inscrits à l’école primaire ou secon...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.UNER.FE?locations=CI","methodology":"Methodology: The number of out-of-school children is calculated by subtracting the number of primary school-age children enrolled in primary or secondary school from the total population of the official primary school-age children. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator measures the proportion of the population within the official age range for a specific educational level who are not currently enrolled in school. The data aids in identifying these individuals to tailor targeted interventions and formulate effective policies, ensuring that all children have the opportunity to attend school. It encompasses children who have never attended school, those who may enroll at a later age, and those who have started education but did not continue to the expected age of completion for the specified level.","theme":"education","source_group":"wb"},{"code":"SE.PRM.UNER.MA","name":"Enfants non scolarisés, primaires, garçons","description":"Les enfants non scolarisés correspondent au nombre d’enfants en âge d’aller à l’école primaire qui ne sont pas inscrits à l’école primaire ou secon...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.UNER.MA?locations=CI","methodology":"Methodology: The number of out-of-school children is calculated by subtracting the number of primary school-age children enrolled in primary or secondary school from the total population of the official primary school-age children. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator measures the proportion of the population within the official age range for a specific educational level who are not currently enrolled in school. The data aids in identifying these individuals to tailor targeted interventions and formulate effective policies, ensuring that all children have the opportunity to attend school. It encompasses children who have never attended school, those who may enroll at a later age, and those who have started education but did not continue to the expected age of completion for the specified level.","theme":"education","source_group":"wb"},{"code":"SH.MLR.TRET.ZS","name":"Enfants fiévreux recevant des médicaments antipaludéens ( % d'enfants de moins de 5 ans ayant de la fièvre)","description":"Le traitement du paludisme fait référence au pourcentage d’enfants de moins de cinq ans qui ont eu de la fièvre au cours des deux dernières semaine...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.MLR.TRET.ZS?locations=CI","methodology":"Methodology: Malaria is endemic to the poorest countries in the world, mainly in tropical and subtropical regions of Africa, Asia, and the Americas. Prompt and effective treatment of malaria is a critical element of malaria control. It is vital that sufferers, especially children under age 5, start treatment within 24 hours of the onset of symptoms, to prevent progression - often rapid - to severe malaria and death. Data on malaria are from national-level surveys, including Multiple Indicator Cluster Surveys, Demographic and Health Surveys, and Malaria Indicator Surveys.","theme":"sante","source_group":"wb"},{"code":"FM.AST.CGOV.ZG.M3","name":"Créances sur l'administration centrale (croissance annuelle en % de la monnaie au sens large)","description":"Les créances sur l'administration centrale comprennent les prêts aux institutions de l'administration centrale, nets des dépôts.","source_link":"https://donnees.banquemondiale.org/indicateur/FM.AST.CGOV.ZG.M3?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FS.AST.CGOV.GD.ZS","name":"Créances sur l'administration centrale, etc. (en % du PIB)","description":"Les créances sur l'administration centrale comprennent les prêts aux institutions de l'administration centrale, nets des dépôts.","source_link":"https://donnees.banquemondiale.org/indicateur/FS.AST.CGOV.GD.ZS?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FS.AST.DOMO.GD.ZS","name":"Créances sur d'autres secteurs de l'économie nationale (en % du PIB)","description":"Les créances sur d’autres secteurs de l’économie nationale comprennent les crédits bruts du système financier aux ménages, aux institutions à but n...","source_link":"https://donnees.banquemondiale.org/indicateur/FS.AST.DOMO.GD.ZS?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FM.AST.DOMO.ZG.M3","name":"Créances sur d'autres secteurs de l'économie nationale (croissance annuelle en % de la monnaie au sens large)","description":"Les créances sur d’autres secteurs de l’économie nationale comprennent les crédits bruts du système financier aux ménages, aux institutions à but n...","source_link":"https://donnees.banquemondiale.org/indicateur/FM.AST.DOMO.ZG.M3?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FM.AST.PRVT.ZG.M3","name":"Créances sur le secteur privé (croissance annuelle en % de la monnaie au sens large)","description":"Les créances sur le secteur privé comprennent les crédits bruts du système financier aux particuliers, aux entreprises, aux entités publiques non f...","source_link":"https://donnees.banquemondiale.org/indicateur/FM.AST.PRVT.ZG.M3?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.COAL.RT.ZS","name":"Rentes du charbon ( % du PIB)","description":"Les rentes du charbon correspondent à la différence entre la valeur de la production de houille et de houille aux prix mondiaux et leurs coûts tota...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.COAL.RT.ZS?locations=CI","methodology":"Methodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).","theme":"secondary","source_group":"wb"},{"code":"EG.USE.CRNW.ZS","name":"Énergies renouvelables combustibles et déchets ( % de l'énergie totale)","description":"Les énergies renouvelables combustibles et les déchets comprennent la biomasse solide, la biomasse liquide, le biogaz, les déchets industriels et l...","source_link":"https://donnees.banquemondiale.org/indicateur/EG.USE.CRNW.ZS?locations=CI","methodology":"Methodology: Energy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments.\nThe indicator is calculated as the share of biofuels and waste in the total energy supply of the country.\nData for combustible renewables and waste are often based on small surveys or other incomplete information and thus give only a broad impression of developments and are not strictly comparable across countries. The IEA reports include country notes that explain some of these differences. All forms of energy - primary energy and primary electricity - are converted into oil equivalents. A notional thermal efficiency of 33 percent is assumed for converting nuclear electricity into oil equivalents and 100 percent efficiency for converting hydroelectric power.","theme":"secondary","source_group":"wb"},{"code":"FB.CBK.BRCH.P5","name":"Succursales de banques commerciales (pour 100 000 adultes)","description":"Les succursales de banques commerciales sont des points de vente au détail de banques commerciales résidentes et d'autres banques résidentes qui fo...","source_link":"https://donnees.banquemondiale.org/indicateur/FB.CBK.BRCH.P5?locations=CI","methodology":"Methodology: Number of branches refers to all units in the country that are physically separated from the main offices, but not incorporated as separate subsidiaries. The number of main offices is excluded. Typically, a branch provides a wide range of services to its customers including cash withdrawals, deposits in an account with a teller, financial advice, safe deposit box rentals, and currency exchange. Units, with or without human staff, which offer only automated services for cash withdrawal and deposits, or computer terminals for online banking and check depositing machines should also be counted as branches.\nStatistical concept(s): Data are shown as the number of branches of commercial banks for every 100,000 adults in the reporting country. It is calculated as (number of institutions + number of branches)*100,000/adult population in the reporting country.","theme":"tertiary","source_group":"wb"},{"code":"DT.NFL.PCBO.CD","name":"Banques commerciales et autres prêts (PPG + PNG) (NFL, $ US courants)","description":"Les prêts bancaires commerciaux et autres prêts comprennent les prêts bancaires commerciaux nets (publics et garantis par l'État et privés non gara...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.PCBO.CD?locations=CI","methodology":"Methodology: Commercial banks include all commercial banks, whether or not publicly owned, that provide loans and other financial services. Private creditors include commercial banks, bondholders, and other private creditors. This indicator includes only publicly guaranteed creditors. Nonguaranteed private creditors are shown separately. Bonds include publicly issued or privately placed bonds. Commercial bank loans are loans from private banks and other private financial institutions. Credits of other private creditors include credits from manufacturers, exporters, and other suppliers of goods, plus bank credits covered by a guarantee of an export credit agency.\n\nChanged to:\nCountries that report to the World Bank’s Debtor Reporting System (DRS) submit their 1- public and publicly guaranteed debt (PPG) and private debt with a public guarantee on a loan-by-loan basis and 2- private nonguaranteed (PNG) debt on an aggregate basis. The World Bank Debt Data Team then compiles this information to produce this indicator.\n\n\nStatistical concept(s): Commercial banks include all commercial banks, whether or not publicly owned, that provide loans and other financial services. Private creditors include commercial banks, bondholders, and other private creditors. This indicator includes only publicly guaranteed creditors. Nonguaranteed private creditors are shown separately. Bonds include publicly issued or privately placed bonds. Commercial bank loans are loans from private banks and other private financial institutions. Credits of other private creditors include credits from manufacturers, exporters, and other suppliers of goods, plus bank credits covered by a guarantee of an export credit agency.\n\nproposed: Commercial banks include all commercial banks, whether or not publicly owned, that provide loans and other financial services. Credits of other private creditors include credits from manufacturers, exporters, and other suppliers of goods, plus bank credits covered by a guarantee of an export credit agency.","theme":"finance","source_group":"wb"},{"code":"TX.VAL.SERV.CD.WT","name":"Exportations de services commerciaux (en dollars américains courants)","description":"Les exportations de services commerciaux correspondent au total des exportations de services moins les exportations de services gouvernementaux non...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.SERV.CD.WT?locations=CI","methodology":"Methodology: International trade in services statistics are compiled in accordance with international standards: Manual on Statistics of International Trade in Services 2010. Specific information on how countries compile their trade in service statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of international trade in services covers trade in services in the conventional sense of transactions (exports and imports) between residents and non-residents. In addition, it covers services delivered through enterprises that are locally established but foreign-controlled and cases where individuals are temporarily present abroad for the purpose of supplying a service.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.SERV.CD.WT","name":"Importations de services commerciaux (en dollars courants des États-Unis)","description":"Les importations de services commerciaux correspondent au total des importations de services moins les importations de services gouvernementaux non...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.SERV.CD.WT?locations=CI","methodology":"Methodology: International trade in services statistics are compiled in accordance with international standards: Manual on Statistics of International Trade in Services 2010. Specific information on how countries compile their trade in service statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of international trade in services covers trade in services in the conventional sense of transactions (exports and imports) between residents and non-residents. In addition, it covers services delivered through enterprises that are locally established but foreign-controlled and cases where individuals are temporarily present abroad for the purpose of supplying a service.","theme":"inter","source_group":"wb"},{"code":"BX.GSR.CMCP.ZS","name":"Communications, informatique, etc. (en % des exportations de services, BdP)","description":"Les services de communication, informatiques, d'information et autres couvrent les télécommunications internationales ; données informatiques; tran...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GSR.CMCP.ZS?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BM.GSR.CMCP.ZS","name":"Communications, informatique, etc. ( % des importations de services, BdP)","description":"Les services de communication, informatiques, d'information et autres couvrent les télécommunications internationales ; données informatiques; tran...","source_link":"https://donnees.banquemondiale.org/indicateur/BM.GSR.CMCP.ZS?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"SH.MED.CMHW.P3","name":"Agents de santé communautaires (pour 1 000 personnes)","description":"Les agents de santé communautaire comprennent divers types d'aides de santé communautaire, dont beaucoup portent des titres professionnels spécifiq...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.MED.CMHW.P3?locations=CI","methodology":"Methodology: The method of estimation for number of community health workers (including community health officers, community health-education workers, community health aides, family health workers and associated occupations) depends on the nature of the original data source. Enumeration based on population census data is a count of the number of people reporting 'community health worker' as their current occupation (as classified according to the tasks and duties of their job). A similar method is used for estimates based on labour force survey data, with the additional application of a sampling weight to calibrate for national representation. Data from health facility assessments and administrative reporting systems may be based on head counts of employees, staffing records, payroll records, training records, or tallies from other types of routine administrative records on human resources.\nStatistical concept(s): Health systems - the combined arrangements of institutions and actions whose primary purpose is to promote, restore, or maintain health (World Health Organization, World Health Report 2000) - are increasingly being recognized as key to combating disease and improving the health status of populations. The World Bank's Healthy Development: Strategy for Health, Nutrition, and Population Results emphasizes the need to strengthen health systems, which are weak in many countries, in order to increase the effectiveness of programs aimed at reducing specific diseases and further reduce morbidity and mortality. To evaluate health systems, the World Health Organization (WHO) has recommended that key components - such as financing, service delivery, workforce, governance, and information - be monitored using several key indicators. The data are a subset of the key indicators. Monitoring health systems allows the effectiveness, efficiency, and equity of different health system models to be compared. Health system data also help identify weaknesses and strengths and areas that need investment, such as additional health facilities, better health information systems, or better trained human resources.\n\n\n\nData on health worker (physicians, nurses and midwives, and community health workers) density show the availability of medical personnel.","theme":"sante","source_group":"wb"},{"code":"GC.XPN.COMP.ZS","name":"Rémunération des salariés ( % de la charge)","description":"La rémunération des salariés est définie comme la rémunération totale, en espèces ou en nature, payable par une entreprise à un salarié en contrepa...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.COMP.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.XPN.COMP.CN","name":"Rémunération des salariés (LCU actuelle)","description":"La rémunération des salariés est définie comme la rémunération totale, en espèces ou en nature, payable par une entreprise à un salarié en contrepa...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.COMP.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"SP.REG.BRTH.ZS","name":"Exhaustivité de l'enregistrement des naissances ( %)","description":"L'exhaustivité de l'enregistrement des naissances correspond au pourcentage d'enfants de moins de 5 ans dont la naissance a été enregistrée au mome...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.REG.BRTH.ZS?locations=CI","methodology":"Methodology: Birth registration refers to the permanent and official recording of a child's existence by some administrative levels of the State that is normally coordinated by a particular branch of the government.\nBirth registration estimates are primarily drawn from nationally representative household surveys such as the Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS). Other data sources include other national surveys, censuses and vital statistics from civil registration systems, and estimated coverage of birth registration within national civil registration systems from the United Nations Statistics Division (UNSD).","theme":"demo","source_group":"wb"},{"code":"SP.REG.BRTH.FE.ZS","name":"Exhaustivité de l'enregistrement des naissances, femmes ( %)","description":"L'exhaustivité de l'enregistrement des naissances correspond au pourcentage d'enfants de moins de 5 ans dont la naissance a été enregistrée au mome...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.REG.BRTH.FE.ZS?locations=CI","methodology":"Methodology: Birth registration refers to the permanent and official recording of a child's existence by some administrative levels of the State that is normally coordinated by a particular branch of the government.\n\n\n\nBirth registration estimates are primarily drawn from nationally representative household surveys such as the Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS). Other data sources include other national surveys, censuses and vital statistics from civil registration systems, and estimated coverage of birth registration within national civil registration systems from the United Nations Statistics Division (UNSD).","theme":"demo","source_group":"wb"},{"code":"SP.REG.BRTH.MA.ZS","name":"Exhaustivité de l'enregistrement des naissances, hommes ( %)","description":"L'exhaustivité de l'enregistrement des naissances correspond au pourcentage d'enfants de moins de 5 ans dont la naissance a été enregistrée au mome...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.REG.BRTH.MA.ZS?locations=CI","methodology":"Methodology: Birth registration refers to the permanent and official recording of a child's existence by some administrative levels of the State that is normally coordinated by a particular branch of the government.\nBirth registration estimates are primarily drawn from nationally representative household surveys such as the Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS). Other data sources include other national surveys, censuses and vital statistics from civil registration systems, and estimated coverage of birth registration within national civil registration systems from the United Nations Statistics Division (UNSD).","theme":"demo","source_group":"wb"},{"code":"SP.REG.BRTH.RU.ZS","name":"Exhaustivité de l'enregistrement des naissances, régions rurales ( %)","description":"L'exhaustivité de l'enregistrement des naissances correspond au pourcentage d'enfants de moins de 5 ans dont la naissance a été enregistrée au mome...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.REG.BRTH.RU.ZS?locations=CI","methodology":"Methodology: Birth registration refers to the permanent and official recording of a child's existence by some administrative levels of the State that is normally coordinated by a particular branch of the government.\nBirth registration estimates are primarily drawn from nationally representative household surveys such as the Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS). Other data sources include other national surveys, censuses and vital statistics from civil registration systems, and estimated coverage of birth registration within national civil registration systems from the United Nations Statistics Division (UNSD).","theme":"demo","source_group":"wb"},{"code":"SP.REG.BRTH.UR.ZS","name":"Exhaustivité de l'enregistrement des naissances, zone urbaine ( %)","description":"L'exhaustivité de l'enregistrement des naissances correspond au pourcentage d'enfants de moins de 5 ans dont la naissance a été enregistrée au mome...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.REG.BRTH.UR.ZS?locations=CI","methodology":"Methodology: Birth registration refers to the permanent and official recording of a child's existence by some administrative levels of the State that is normally coordinated by a particular branch of the government.\nBirth registration estimates are primarily drawn from nationally representative household surveys such as the Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS). Other data sources include other national surveys, censuses and vital statistics from civil registration systems, and estimated coverage of birth registration within national civil registration systems from the United Nations Statistics Division (UNSD).","theme":"demo","source_group":"wb"},{"code":"SP.REG.DTHS.ZS","name":"Exhaustivité de l'enregistrement du décès avec des informations sur la cause du décès ( %)","description":"L'exhaustivité de l'enregistrement des décès est le pourcentage estimé de décès enregistrés avec leurs informations sur la cause du décès dans le s...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.REG.DTHS.ZS?locations=CI","methodology":"Methodology: The completeness of death registration is calculated by dividing the total number of deaths registered with cause-of-death information in the vital registration system for a given country-year by the total estimated deaths for that year for the national population. The national level of completeness is provided by the National Statistical Offices of all countries and areas to the United Nations Statistics Division as part of the annual data collection for the United Nations Demographic Yearbook. Currently, the threshold used for compiling the data for this indicator is 75 percent for death registration.","theme":"demo","source_group":"wb"},{"code":"SE.COM.DURS","name":"Formation obligatoire, durée (années)","description":"La durée de la scolarité obligatoire correspond au nombre d'années pendant lesquelles les enfants sont légalement tenus de fréquenter l'école.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.COM.DURS?locations=CI","methodology":"Methodology: Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Aggregate data are based on World Bank estimates.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): Compulsory education is defined as educational programs that children and young people are legally obliged to attend, usually defined in terms of a number of grades or an age range, or both (UNESCO, https://unesdoc.unesco.org/ark:/48223/pf0000141639).","theme":"education","source_group":"wb"},{"code":"TX.VAL.OTHR.ZS.WT","name":"Services informatiques, communications et autres ( % des exportations de services commerciaux)","description":"Les services informatiques, de communication et autres comprennent des activités telles que les télécommunications internationales et les services ...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.OTHR.ZS.WT?locations=CI","methodology":"Methodology: International trade in services statistics are compiled in accordance with international standards: Manual on Statistics of International Trade in Services 2010. Specific information on how countries compile their trade in service statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of international trade in services covers trade in services in the conventional sense of transactions (exports and imports) between residents and non-residents. In addition, it covers services delivered through enterprises that are locally established but foreign-controlled and cases where individuals are temporarily present abroad for the purpose of supplying a service.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.OTHR.ZS.WT","name":"Services informatiques, communications et autres ( % des importations de services commerciaux)","description":"Les services informatiques, de communication et autres comprennent des activités telles que les télécommunications internationales et les services ...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.OTHR.ZS.WT?locations=CI","methodology":"Methodology: International trade in services statistics are compiled in accordance with international standards: Manual on Statistics of International Trade in Services 2010. Specific information on how countries compile their trade in service statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of international trade in services covers trade in services in the conventional sense of transactions (exports and imports) between residents and non-residents. In addition, it covers services delivered through enterprises that are locally established but foreign-controlled and cases where individuals are temporarily present abroad for the purpose of supplying a service.","theme":"inter","source_group":"wb"},{"code":"SH.CON.1524.FE.ZS","name":"Utilisation du préservatif, population âgée de 15 à 24 ans, femmes ( % de femmes âgées de 15 à 24 ans)","description":"L'utilisation du préservatif chez les femmes est le pourcentage de la population féminine âgée de 15 à 24 ans qui a utilisé un préservatif lors de ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.CON.1524.FE.ZS?locations=CI","methodology":"Methodology: Household Surveys\nStatistical concept(s): When used the right way every time, condoms are highly effective in preventing HIV and other sexually transmitted diseases (STDs).","theme":"sante","source_group":"wb"},{"code":"SH.CON.1524.MA.ZS","name":"Utilisation du préservatif, population âgée de 15 à 24 ans, hommes ( % des hommes âgés de 15 à 24 ans)","description":"L'utilisation du préservatif chez les hommes correspond au pourcentage de la population masculine âgée de 15 à 24 ans qui a utilisé un préservatif ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.CON.1524.MA.ZS?locations=CI","methodology":"Methodology: Household Surveys\nStatistical concept(s): When used the right way every time, condoms are highly effective in preventing HIV and other sexually transmitted diseases (STDs).","theme":"sante","source_group":"wb"},{"code":"FP.CPI.TOTL","name":"Indice des prix à la consommation (2010 = 100)","description":"Indice des prix des biens et services de consommation, par rapport à une certaine période de référence (2010=100).","source_link":"https://donnees.banquemondiale.org/indicateur/FP.CPI.TOTL?locations=CI","methodology":"Methodology: Consumer Prices Indices are compiled in accordance with international standards: Consumer Price Index Manual, 2020 or 2004 version. Specific information on how countries compile their CPI statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of a consumer price index series is to measure the rate at which prices of consumption goods and services are changing from one period to another.","theme":"macro","source_group":"wb"},{"code":"SN.ITK.SALT.ZS","name":"Consommation de sel iodé ( % des ménages)","description":"Pourcentage de ménages qui ont utilisé du sel pour cuisiner qui a été testé positif (>0 ppm) pour la présence d'iode.","source_link":"https://donnees.banquemondiale.org/indicateur/SN.ITK.SALT.ZS?locations=CI","methodology":"Methodology: Most of the data on consumption of iodized salt are derived from household surveys. For the data that are from household surveys, the year refers to the survey year.","theme":"sante","source_group":"wb"},{"code":"IS.SHP.GOOD.TU","name":"Trafic portuaire de conteneurs (TEU : équivalents 20 pieds)","description":"Le trafic de conteneurs portuaires mesure le flux de conteneurs des modes de transport terrestre vers les modes de transport maritime, et vice vers...","source_link":"https://donnees.banquemondiale.org/indicateur/IS.SHP.GOOD.TU?locations=CI","methodology":"Methodology: TEU is the standard unit, referring to 20-foot equivalent units or 20-foot-long cargo container. The size of cargo containers range from 20 feet long to more than 50 feet long. The international measure is the smallest box, the 20-footer or 20-foot-equivalent unit (TEU). Two twenty-foot containers (TEUs) equal one FEU. Container vessel capacity and port throughput capacity are frequently referred to in TEUs.\n\nFor any questions related to the country data and methodology, please contact the Review of Maritime Transport team at: unctad-rmt@un.org","theme":"territory","source_group":"wb"},{"code":"SP.DYN.CONU.ZS","name":"Prévalence contraceptive, toutes méthodes confondues ( % de femmes mariées âgées de 15 à 49 ans)","description":"La prévalence contraceptive, toute méthode est le pourcentage de femmes mariées âgées de 15 à 49 ans qui pratiquent, ou dont les partenaires sexuel...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.CONU.ZS?locations=CI","methodology":"Methodology: Contraceptive prevalence rates are obtained mainly from nationally representative household surveys, including: Demographic and Health Surveys; Multiple Indicator Cluster Surveys; Contraceptive Prevalence Surveys; Gender and Generations Survey; Reproductive Health Surveys; and World Fertility Surveys.  Additional information was provided by other international survey programs and national surveys.  \nMarried women refer to women who are married (defined in relation to the marriage laws or customs of a country) and to women in a union, which refers to women living with their partner in the same household (also referred to as cohabiting unions, consensual unions, unmarried unions, or “living together”).","theme":"demo","source_group":"wb"},{"code":"SP.DYN.CONM.ZS","name":"Prévalence contraceptive, toutes méthodes modernes ( % de femmes mariées âgées de 15 à 49 ans)","description":"La prévalence contraceptive, toute méthode moderne, correspond au pourcentage de femmes mariées âgées de 15 à 49 ans qui pratiquent, ou dont les pa...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.CONM.ZS?locations=CI","methodology":"Methodology: Contraceptive prevalence rates are obtained mainly from nationally representative household surveys, including: Demographic and Health Surveys; Multiple Indicator Cluster Surveys; Contraceptive Prevalence Surveys; Gender and Generations Survey; Reproductive Health Surveys; and World Fertility Surveys.  Additional information was provided by other international survey programs and national surveys.  \n\n\n\nMarried women refer to women who are married (defined in relation to the marriage laws or customs of a country) and to women in a union, which refers to women living with their partner in the same household (also referred to as cohabiting unions, consensual unions, unmarried unions, or “living together”).","theme":"demo","source_group":"wb"},{"code":"SL.FAM.WORK.FE.ZS","name":"Travailleurs familiaux cotisants, femmes ( % de l'emploi féminin) (estimation modélisée de l'OIT)","description":"Les travailleurs familiaux contributeurs sont les travailleurs qui occupent des « emplois indépendants » en tant que travailleurs à leur propre com...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.FAM.WORK.FE.ZS?locations=CI","methodology":"Methodology: The proportion of contributing family workers to the total employed is calculated as follows: Contributing family workers/Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SL.FAM.WORK.MA.ZS","name":"Travailleurs familiaux cotisants, hommes ( % de l'emploi masculin) (estimation modélisée de l'OIT)","description":"Les travailleurs familiaux contributeurs sont les travailleurs qui occupent des « emplois indépendants » en tant que travailleurs à leur propre com...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.FAM.WORK.MA.ZS?locations=CI","methodology":"Methodology: The proportion of contributing family workers to the total employed is calculated as follows: Contributing family workers/Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SL.FAM.WORK.ZS","name":"Travailleurs familiaux cotisants, total ( % de l'emploi total) (estimation modélisée de l'OIT)","description":"Les travailleurs familiaux contributeurs sont les travailleurs qui occupent des « emplois indépendants » en tant que travailleurs à leur propre com...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.FAM.WORK.ZS?locations=CI","methodology":"Methodology: The proportion of contributing family workers to the total employed is calculated as follows: Contributing family workers/Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"CC.EST","name":"Contrôle de la corruption : estimation","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/CC.EST?locations=CI","methodology":"","theme":"politique","source_group":"wb"},{"code":"CC.NO.SRC","name":"Contrôle de la corruption : nombre de sources","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/CC.NO.SRC?locations=CI","methodology":"Methodology: The WGI compile and summarize information from over 30 existing data sources that report the views and experiences of citizens, entrepreneurs, and experts in the public, private and NGO sectors from around the world, on the quality of various aspects of governance.\n\n•\tThe data sources must provide subjective perceptions of relevant dimensions of governance, as the WGI are based exclusively on this type of data.\n•\tThe sources must provide original primary data produced using a well-defined methodology.\n•\tThe data sources must cover multiple countries, so that cross-country comparisons are possible.\n•\tThe data sources must be updated regularly, ideally every year, although some WGI data sources are updated once every two or three years.\n\nThe WGI draw on four different types of source data:\n\n•\tSurveys of households and firms, including the Afrobarometer surveys, Gallup World Poll, and Global Competitiveness Report survey,\n•\tCommercial business information providers, including the Economist Intelligence Unit, S&P Global, and Political Risk Services,\n•\tNon-governmental organizations, including Global Integrity, Freedom House, Reporters Without Borders, and\n•\tPublic sector organizations, including the Country Policy and Institutional Assessments (CPIA) assessments of World Bank and regional development banks.\n\nFor the detailed list of sources, please refer to: https://www.worldbank.org/en/publication/worldwide-governance-indicators/documentation#2  \nStatistical concept(s): Number of sources indicates the number of underlying data sources on which the aggregate estimate is based.\n\nVariables from the data sources are assigned to each of these six governance dimensions.  For example, an assessment of the quality of the bureaucracy would be assigned to Government Effectiveness, a question about confidence in the police or the courts would be assigned to Rule of Law, and a question about the perceived likelihood of having to pay a bribe would be assigned to Control of Corruption.  In some cases, a single data source will have multiple questions that can be assigned to the same dimension.  In this case, the WGI use the average across all relevant questions from that data source. In addition each question from each data source is assigned to only one of the six governance dimensions, selecting the dimension that best matches the content of the question.","theme":"politique","source_group":"wb"},{"code":"CC.PER.RNK","name":"Contrôle de la corruption : rang centile","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/CC.PER.RNK?locations=CI","methodology":"","theme":"politique","source_group":"wb"},{"code":"CC.PER.RNK.LOWER","name":"Contrôle de la corruption : rang centile, limite inférieure de l'intervalle de confiance à 90 %","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/CC.PER.RNK.LOWER?locations=CI","methodology":"Methodology: A key feature of the WGI is that all country scores are accompanied by standard errors. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether.\n\nThe standard deviations are essential to the interpretation of the WGI.  It often is more appropriate to think of the WGI methodology as identifying a statistically likely range of values for the unobserved “true” level of governance in a country.  For example, the assumption of normality tells us that there is a 90 percent probability that the true unobserved level of governance conditional on the available data for a country is in a range given by plus or minus 1.64 standard deviations around the estimate of governance. These confidence intervals are informally referred to as the “margin of error” around the estimates of governance.\n\nThese 90 percent confidence interval are also reported in percentile rank terms (the percentile rank among all country estimates of governance, of the upper and lower bounds of the 90 percent confidence interval for each country).\n\nStatistical concept(s): Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank.  Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.  \n\nPercentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.","theme":"politique","source_group":"wb"},{"code":"CC.PER.RNK.UPPER","name":"Contrôle de la corruption : rang centile, limite supérieure de l'intervalle de confiance à 90 %","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/CC.PER.RNK.UPPER?locations=CI","methodology":"Methodology: A key feature of the WGI is that all country scores are accompanied by standard errors. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether.\n\nThe standard deviations are essential to the interpretation of the WGI.  It often is more appropriate to think of the WGI methodology as identifying a statistically likely range of values for the unobserved “true” level of governance in a country.  For example, the assumption of normality tells us that there is a 90 percent probability that the true unobserved level of governance conditional on the available data for a country is in a range given by plus or minus 1.64 standard deviations around the estimate of governance. These confidence intervals are informally referred to as the “margin of error” around the estimates of governance.\n\nThese 90 percent confidence interval are also reported in percentile rank terms (the percentile rank among all country estimates of governance, of the upper and lower bounds of the 90 percent confidence interval for each country).\nStatistical concept(s): Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. \n\nPercentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.","theme":"politique","source_group":"wb"},{"code":"CC.STD.ERR","name":"Contrôle de la corruption : erreur type","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/CC.STD.ERR?locations=CI","methodology":"Methodology: The WGI are composite governance indicators based on over 30 underlying data sources. These data sources are rescaled and combined to create the six aggregate indicators using a statistical methodology known as an Unobserved Components Model (UCM). The six aggregate indicators are reported in two ways : (1) in their standard normal units, ranging from approximately -2.5 to 2.5, and (2) in percentile rank terms from 0 to 100, with higher values corresponding to better outcomes.\n\nA key feature of the WGI is that all country scores are accompanied by standard errors. These margins of error need to be taken into account when making comparisons across countries and over time. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether. \n\nPlease see more information at: https://www.worldbank.org/en/publication/worldwide-governance-indicators/documentation#1\nStatistical concept(s): Standard error indicates the precision of the estimate of governance. Larger values of the standard error indicate less precise estimates. A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.","theme":"politique","source_group":"wb"},{"code":"per_si_allsi.cov_pop_tot","name":"Couverture des programmes d'assurance sociale ( % de la population)","description":"La couverture des programmes d'assurance sociale indique le pourcentage de la population participant à des programmes qui fournissent des pensions ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_si_allsi.cov_pop_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_si_allsi.cov_q2_tot","name":"Couverture des programmes d'assurance sociale dans le 2e quintile ( % de la population)","description":"La couverture des programmes d'assurance sociale indique le pourcentage de la population participant à des programmes qui fournissent des pensions ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_si_allsi.cov_q2_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_si_allsi.cov_q3_tot","name":"Couverture des programmes d'assurance sociale dans le 3e quintile ( % de la population)","description":"La couverture des programmes d'assurance sociale indique le pourcentage de la population participant à des programmes qui fournissent des pensions ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_si_allsi.cov_q3_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_si_allsi.cov_q4_tot","name":"Couverture des programmes d'assurance sociale dans le 4e quintile ( % de la population)","description":"La couverture des programmes d'assurance sociale indique le pourcentage de la population participant à des programmes qui fournissent des pensions ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_si_allsi.cov_q4_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_si_allsi.cov_q1_tot","name":"Couverture des programmes d'assurance sociale dans le quintile le plus pauvre ( % de la population)","description":"La couverture des programmes d'assurance sociale indique le pourcentage de la population participant à des programmes qui fournissent des pensions ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_si_allsi.cov_q1_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_si_allsi.cov_q5_tot","name":"Couverture des programmes d'assurance sociale dans le quintile le plus riche ( % de la population)","description":"La couverture des programmes d'assurance sociale indique le pourcentage de la population participant à des programmes qui fournissent des pensions ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_si_allsi.cov_q5_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_allsp.cov_pop_tot","name":"Couverture des programmes de protection sociale et du travail ( % de la population)","description":"La couverture des programmes de protection sociale et de travail (SPL) montre le pourcentage de la population participant à l'assurance sociale, au...","source_link":"https://donnees.banquemondiale.org/indicateur/per_allsp.cov_pop_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_sa_allsa.cov_pop_tot","name":"Couverture des programmes de protection sociale ( % de la population)","description":"La couverture des programmes de filets de sécurité sociale montre le pourcentage de la population participant aux transferts monétaires et aux prog...","source_link":"https://donnees.banquemondiale.org/indicateur/per_sa_allsa.cov_pop_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_sa_allsa.cov_q2_tot","name":"Couverture des programmes de protection sociale dans le 2e quintile ( % de la population)","description":"La couverture des programmes de filets de sécurité sociale montre le pourcentage de la population participant aux transferts monétaires et aux prog...","source_link":"https://donnees.banquemondiale.org/indicateur/per_sa_allsa.cov_q2_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_sa_allsa.cov_q3_tot","name":"Couverture des programmes de protection sociale dans le 3e quintile ( % de la population)","description":"La couverture des programmes de filets de sécurité sociale montre le pourcentage de la population participant aux transferts monétaires et aux prog...","source_link":"https://donnees.banquemondiale.org/indicateur/per_sa_allsa.cov_q3_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_sa_allsa.cov_q4_tot","name":"Couverture des programmes de protection sociale dans le 4e quintile ( % de la population)","description":"La couverture des programmes de filets de sécurité sociale montre le pourcentage de la population participant aux transferts monétaires et aux prog...","source_link":"https://donnees.banquemondiale.org/indicateur/per_sa_allsa.cov_q4_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_sa_allsa.cov_q1_tot","name":"Couverture des programmes de protection sociale dans le quintile le plus pauvre ( % de la population)","description":"La couverture des programmes de filets de sécurité sociale montre le pourcentage de la population participant aux transferts monétaires et aux prog...","source_link":"https://donnees.banquemondiale.org/indicateur/per_sa_allsa.cov_q1_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_sa_allsa.cov_q5_tot","name":"Couverture des programmes de protection sociale dans le quintile le plus riche ( % de la population)","description":"La couverture des programmes de filets de sécurité sociale montre le pourcentage de la population participant aux transferts monétaires et aux prog...","source_link":"https://donnees.banquemondiale.org/indicateur/per_sa_allsa.cov_q5_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_lm_alllm.cov_pop_tot","name":"Prise en charge des allocations de chômage et des MTPM (en % de la population)","description":"La couverture des allocations de chômage et des programmes actifs du marché du travail (PAMT) montre le pourcentage de la population participant à ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_lm_alllm.cov_pop_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_lm_alllm.cov_q2_tot","name":"Couverture des allocations de chômage et des PAMM dans le 2e quintile ( % de la population)","description":"La couverture des allocations de chômage et des programmes actifs du marché du travail (PAMT) montre le pourcentage de la population participant à ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_lm_alllm.cov_q2_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_lm_alllm.cov_q3_tot","name":"Couverture des allocations de chômage et des PAMM dans le 3e quintile (en % de la population)","description":"La couverture des allocations de chômage et des programmes actifs du marché du travail (PAMT) montre le pourcentage de la population participant à ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_lm_alllm.cov_q3_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_lm_alllm.cov_q4_tot","name":"Couverture des allocations de chômage et des PAMT dans le 4e quintile ( % de la population)","description":"La couverture des allocations de chômage et des programmes actifs du marché du travail (PAMT) montre le pourcentage de la population participant à ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_lm_alllm.cov_q4_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_lm_alllm.cov_q1_tot","name":"Couverture des allocations de chômage et des MPT dans le quintile le plus pauvre ( % de la population)","description":"La couverture des allocations de chômage et des programmes actifs du marché du travail (PAMT) montre le pourcentage de la population participant à ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_lm_alllm.cov_q1_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"per_lm_alllm.cov_q5_tot","name":"Couverture des allocations de chômage et des PAMM dans le quintile le plus riche ( % de la population)","description":"La couverture des allocations de chômage et des programmes actifs du marché du travail (PAMT) montre le pourcentage de la population participant à ...","source_link":"https://donnees.banquemondiale.org/indicateur/per_lm_alllm.cov_q5_tot?locations=CI","methodology":"Methodology: ASPIRE performance indicators are generally based on national representative household surveys (except for Argentina where the survey is only urban representative) including household income expenditure/budget surveys, Living Standard Measurement Surveys (LSMS), Multiple Indicator Cluster Surveys (MICs), Surveys on Income and Living Conditions (SILCs), and Welfare Monitoring Surveys. Efforts are made to ensure that welfare aggregates (either income or consumption per capita) used to rank households are those harmonized by World Bank regional poverty teams and are up-to-date.\nStatistical concept(s): Population Coverage Rate","theme":"social","source_group":"wb"},{"code":"IQ.CPA.HRES.XQ","name":"Évaluation des ressources humaines de l'EPIN (1 = faible à 6 = élevée)","description":"La CPIA mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient la croissance durable et la réduction de la pauvreté, et ...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.HRES.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.BREG.XQ","name":"Cote de l'environnement réglementaire des entreprises de l'EPIN (1 = faible à 6 = élevée)","description":"La CPIA mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient la croissance durable et la réduction de la pauvreté, et ...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.BREG.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.DEBT.XQ","name":"Notation de la politique d'endettement de CPIA (1 = faible à 6 = élevée)","description":"L’évaluation politique et institutionnelle d’un pays (CPIA) mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient une c...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.DEBT.XQ?locations=CI","methodology":"All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.ECON.XQ","name":"Moyenne du groupe de gestion économique CPIA (1 = faible à 6 = élevée)","description":"L’évaluation politique et institutionnelle d’un pays (CPIA) mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient une c...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.ECON.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.REVN.XQ","name":"Évaluation de l'efficacité de la mobilisation des recettes de l'EPIN (1 = faible à 6 = élevée)","description":"L’évaluation politique et institutionnelle d’un pays (CPIA) mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient une c...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.REVN.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.PRES.XQ","name":"Évaluation de l'équité de l'utilisation des ressources publiques par l'EPIN (1 = faible à 6 = élevée)","description":"L’équité dans l’utilisation des ressources publiques évalue dans quelle mesure le modèle de dépenses publiques et de collecte des recettes affecte ...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.PRES.XQ?locations=CI","methodology":"Methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.FINS.XQ","name":"Notation du secteur financier CPIA (1 = faible à 6 = élevée)","description":"La CPIA mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient la croissance durable et la réduction de la pauvreté, et ...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.FINS.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.FISP.XQ","name":"Notation de la politique budgétaire de l'EPIN (1 = faible à 6 = élevée)","description":"La CPIA mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient la croissance durable et la réduction de la pauvreté, et ...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.FISP.XQ?locations=CI","methodology":"All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.GNDR.XQ","name":"Évaluation de l'égalité des sexes par l'EPIN (1 = faible à 6 = élevée)","description":"La CPIA mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient la croissance durable et la réduction de la pauvreté, et ...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.GNDR.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.MACR.XQ","name":"Notation de la gestion macroéconomique CPIA (1 = faible à 6 = élevée)","description":"La CPIA mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient la croissance durable et la réduction de la pauvreté, et ...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.MACR.XQ?locations=CI","methodology":"All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.SOCI.XQ","name":"Moyenne sectorielle des politiques de l'EPIN en matière d'inclusion sociale/équité (1 = faible à 6 = élevée)","description":"L’évaluation politique et institutionnelle d’un pays (CPIA) mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient une c...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.SOCI.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.ENVR.XQ","name":"Politique et institutions de l'EPIN pour l'évaluation de la durabilité environnementale (1 = faible à 6 = élevé)","description":"L’évaluation politique et institutionnelle d’un pays (CPIA) mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient une c...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.ENVR.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.PROP.XQ","name":"Droits de propriété de l'EPIN et évaluation de la gouvernance fondée sur des règles (1 = faible à 6 = élevé)","description":"L’évaluation politique et institutionnelle d’un pays (CPIA) mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient une c...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.PROP.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.PUBS.XQ","name":"Moyenne du groupe de gestion et d'institutions du secteur public de l'EPIN (1 = faible à 6 = élevée)","description":"L’évaluation politique et institutionnelle d’un pays (CPIA) mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient une c...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.PUBS.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.FINQ.XQ","name":"Évaluation de la qualité de la gestion budgétaire et financière de l'EPIN (1 = faible à 6 = élevée)","description":"La CPIA mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient la croissance durable et la réduction de la pauvreté, et ...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.FINQ.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.PADM.XQ","name":"Évaluation de la qualité de l'administration publique par l'EPIN (1 = faible à 6 = élevée)","description":"La CPIA mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient la croissance durable et la réduction de la pauvreté, et ...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.PADM.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.PROT.XQ","name":"Évaluation de la protection sociale CPIA (1 = faible à 6 = élevée)","description":"L’évaluation politique et institutionnelle d’un pays (CPIA) mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient une c...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.PROT.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.STRC.XQ","name":"Moyenne du groupe des politiques structurelles de l'EPIN (1 = faible à 6 = élevée)","description":"L’évaluation politique et institutionnelle d’un pays (CPIA) mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient une c...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.STRC.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.TRAD.XQ","name":"Cote de transaction CPIA (1 = faible à 6 = élevée)","description":"Le commerce évalue la manière dont le cadre politique favorise le commerce des marchandises.","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.TRAD.XQ?locations=CI","methodology":"Methodology: All criteria within each cluster receive equal weight, and each cluster has a 25 percent weight in the overall score, which is obtained by averaging the average scores of the four clusters. For each of the 16 criteria countries are rated on a scale of 1 (low) to 6 (high). The scores depend on the level of performance in a given year assessed against the criteria, rather than on changes in performance compared with the previous year. All 16 CPIA criteria contain a detailed description of each rating level. In assessing country performance, World Bank staff evaluate the country's performance on each of the criteria and assign a rating. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge and on relevant publicly available indicators. In interpreting the assessment scores, it should be noted that the criteria are designed in a developmentally neutral manner. Accordingly, higher scores can be attained by a country that, given its stage of development, has a policy and institutional framework that more strongly fosters growth and poverty reduction.\n\nThe country teams that prepare the ratings are very familiar with the country, and their assessments are based on country diagnostic studies prepared by the World Bank or other development organizations and on their own professional judgment. An early consultation is conducted with country authorities to make sure that the assessments are informed by up-to-date information. To ensure that scores are consistent across countries, the process involves two key phases. In the benchmarking phase a small representative sample of countries drawn from all regions is rated. Country teams prepare proposals that are reviewed first at the regional level and then in a Bankwide review process. A similar process is followed to assess the performance of the remaining countries, using the benchmark countries' scores as guideposts. The final ratings are determined following a Bankwide review. The overall numerical IRAI score and the separate criteria scores were first publicly disclosed in June 2006.","theme":"politique","source_group":"wb"},{"code":"IQ.CPA.TRAN.XQ","name":"Cote CPIA de la transparence, de la responsabilité et de la corruption dans le secteur public (1 = faible à 6 = élevé)","description":"L’évaluation politique et institutionnelle d’un pays (CPIA) mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient une c...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.TRAN.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"AG.PRD.CROP.XD","name":"Indice de la production végétale (2014-2016 = 100)","description":"L'indice de production agricole montre la production agricole pour chaque année par rapport à la période de base 2014-2016.","source_link":"https://donnees.banquemondiale.org/indicateur/AG.PRD.CROP.XD?locations=CI","methodology":"Methodology: The agricultural production index is prepared by the Food and Agriculture Organization of the United Nations (FAO). The FAO indices of agricultural production show the relative level of the aggregate volume of agricultural production for each year in comparison with the base period 2014-2016. They are based on the sum of price-weighted quantities of different agricultural commodities produced after deductions of quantities used as seed and feed weighted in a similar manner. The resulting aggregate represents, therefore, disposable production for any use except as seed and feed. All the indices at the country, regional and world levels are calculated by the Laspeyres formula*. Production quantities of each commodity are weighted by 2014-2016 average international commodity prices and summed for each year. To obtain the index, the aggregate for a given year is divided by the average aggregate for the base period 2014-2016. Since the FAO indices are based on the concept of agriculture as a single enterprise, amounts of seed and feed are subtracted from the production data to avoid double counting, once in the production data and once with the crops or livestock produced from them. Deductions for seed (in the case of eggs, for hatching) and for livestock and poultry feed apply to both domestically produced and imported commodities. They cover only primary agricultural products destined to animal feed (e.g. maize, potatoes, milk, etc.). Processed and semi-processed feed items such as bran, oilcakes, meals and molasses have been completely excluded from the calculations at all stages. It should be noted that when calculating indices of agricultural, food and nonfood production, all intermediate primary inputs of agricultural origin are deducted. However, for indices of any other commodity group, only inputs originating from within the same group are deducted; thus, only seed is removed from the group \"crops\" and from all crop subgroups, such as cereals, oil crops, etc.; and both feed and seed originating from within the livestock sector (e.g. milk feed, hatching eggs) are removed from the group \"livestock products\". For the main two livestock subgroups, namely, meat and milk, only feed originating from the respective subgroup is removed. Indices which take into account deductions for feed and seed are referred to as ''net''. Indices calculated without any deductions for feed and seed are referred to as ''gross\". The \"international commodity prices\" are used in order to avoid the use of exchange rates for obtaining continental and world aggregates, and also to improve and facilitate international comparative analysis of productivity at the national level. These\" international prices,\" expressed in so-called \"international dollars,\" are derived using a Geary-Khamis formula** for the agricultural sector. This method assigns a single \"price\" to each commodity. For example, one metric ton of wheat has the same price regardless of the country where it was produced. The currency unit in which the prices are expressed has no influence on the indices published. The commodities covered in the computation of indices of agricultural production are all crops and livestock products originating in each country. Practically all products are covered, with the main exception of fodder crops. \n\n\n\n\n\n\n\n\n\n\n\n* A Laspeyres Index is known as a \"base-weighted\" or \"fixed-weighted\" index because the price increases are weighted by the quantities in the base period. The Consumer Price Index is an example of a Laspeyres Index. http://www.usna.edu/Users/econ/rbrady/312%20Materials/LaspeyresCalc.pdf\n\n\n\n\n\n** Geary-Khamis formula is an aggregation method in which category \"international prices\" (reflecting relative category values) and country purchasing power parities (PPPs), (depicting relative country price levels) are estimated simultaneously from a system of linear equations. http://stats.oecd.org/glossary/detail.asp?ID=5528\nStatistical concept(s):","theme":"primary","source_group":"wb"},{"code":"BN.CAB.XOKA.GD.ZS","name":"Balance courante (en % du PIB)","description":"Balance des transactions courantes (transactions sur biens et services, revenus du travail et revenus de transferts) entre résidents et non-résidents.","source_link":"https://donnees.banquemondiale.org/indicateur/BN.CAB.XOKA.GD.ZS?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BN.CAB.XOKA.CD","name":"Solde du compte courant ($ US courants, BdP)","description":"Balance des transactions courantes (transactions sur biens et services, revenus du travail et revenus de transferts) entre résidents et non-résidents.","source_link":"https://donnees.banquemondiale.org/indicateur/BN.CAB.XOKA.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"SE.XPD.CPRM.ZS","name":"Dépenses courantes d'éducation dans l'enseignement primaire (en % des dépenses totales dans les établissements publics primaires)","description":"Les dépenses courantes sont exprimées en pourcentage des dépenses directes dans les établissements d'enseignement public (pédagogiques et non pédag...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.XPD.CPRM.ZS?locations=CI","methodology":"Methodology: Current expenditure, primary is calculated by dividing all current expenditure in public institutions of primary education by total expenditure (current and capital) in public institutions of primary education, and multiplying by 100. Aggregate data are based on World Bank estimates.\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe data on education spending is obtained from national governments through their responses to the annual UIS survey on formal education or the UNESCO-OECD-Eurostat (UOE) data collection initiative. The figures reported in the education expenditure questionnaire are usually derived from the annual financial reports of the Ministry of Finance or the Ministry of Education, or from the national accounts maintained by the National Statistical Office.\nStatistical concept(s): Educational expenditure in public institutions includes all staff compensation, teaching staff/non teaching staff compensation, current expenditure other than staff compensation, expenditure on school books and teaching material.","theme":"education","source_group":"wb"},{"code":"SE.XPD.CSEC.ZS","name":"Dépenses courantes d'éducation, secondaire (en % des dépenses totales dans les établissements publics secondaires)","description":"Les dépenses courantes sont exprimées en pourcentage des dépenses directes dans les établissements d'enseignement public (pédagogiques et non pédag...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.XPD.CSEC.ZS?locations=CI","methodology":"Methodology: Current expenditure, secondary is calculated by dividing all current expenditure in public institutions of secondary education by total expenditure (current and capital) in public institutions of secondary education, and multiplying by 100. Aggregate data are based on World Bank estimates.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe data on education spending is obtained from national governments through their responses to the annual UIS survey on formal education or the UNESCO-OECD-Eurostat (UOE) data collection initiative. The figures reported in the education expenditure questionnaire are usually derived from the annual financial reports of the Ministry of Finance or the Ministry of Education, or from the national accounts maintained by the National Statistical Office.\nStatistical concept(s): Educational expenditure in public institutions includes all staff compensation, teaching staff/non teaching staff compensation, current expenditure other than staff compensation, expenditure on school books and teaching material.","theme":"education","source_group":"wb"},{"code":"SE.XPD.CTER.ZS","name":"Dépenses courantes d'éducation, enseignement supérieur (en % des dépenses totales dans les établissements publics d'enseignement supérieur)","description":"Les dépenses courantes sont exprimées en pourcentage des dépenses directes dans les établissements d'enseignement public (pédagogiques et non pédag...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.XPD.CTER.ZS?locations=CI","methodology":"Methodology: Current expenditure, tertiary is calculated by dividing all current expenditure in public institutions of tertiary education by total expenditure (current and capital) in public institutions of tertiary education, and multiplying by 100. Aggregate data are based on World Bank estimates.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe data on education spending is obtained from national governments through their responses to the annual UIS survey on formal education or the UNESCO-OECD-Eurostat (UOE) data collection initiative. The figures reported in the education expenditure questionnaire are usually derived from the annual financial reports of the Ministry of Finance or the Ministry of Education, or from the national accounts maintained by the National Statistical Office.\nStatistical concept(s): Educational expenditure in public institutions includes all staff compensation, teaching staff/non teaching staff compensation, current expenditure other than staff compensation, expenditure on school books and teaching material.","theme":"education","source_group":"wb"},{"code":"SE.XPD.CTOT.ZS","name":"Dépenses courantes d'éducation, total (en % des dépenses totales dans les établissements publics)","description":"Les dépenses courantes sont exprimées en pourcentage des dépenses directes dans les établissements d'enseignement public (pédagogiques et non pédag...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.XPD.CTOT.ZS?locations=CI","methodology":"Methodology: Current expenditure, total is calculated by dividing all current expenditure in public institutions of all levels of education by total expenditure (current and capital) in public institutions of all levels of education, and multiplying by 100. Aggregate data are based on World Bank estimates.\nThe data on education spending is obtained from national governments through their responses to the annual UIS survey on formal education or the UNESCO-OECD-Eurostat (UOE) data collection initiative. The figures reported in the education expenditure questionnaire are usually derived from the annual financial reports of the Ministry of Finance or the Ministry of Education, or from the national accounts maintained by the National Statistical Office.\nStatistical concept(s): Educational expenditure in public institutions includes all staff compensation, teaching staff/non teaching staff compensation, current expenditure other than staff compensation, expenditure on school books and teaching material.","theme":"education","source_group":"wb"},{"code":"SH.XPD.CHEX.GD.ZS","name":"Dépenses courantes de santé (en % du PIB)","description":"Niveau des dépenses courantes de santé exprimé en pourcentage du PIB.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.CHEX.GD.ZS?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.CHEX.PC.CD","name":"Dépenses courantes de santé par habitant (en dollars courants des États-Unis)","description":"Dépenses courantes de santé par habitant en dollars américains courants.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.CHEX.PC.CD?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.CHEX.PP.CD","name":"Dépenses courantes de santé par habitant, PPA (en dollars internationaux courants)","description":"Dépenses courantes de santé par habitant exprimées en dollars internationaux à parité de pouvoir d'achat.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.CHEX.PP.CD?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making. WHO converted the expenditure data using PPP time series extracted from WDI (based on ICP 2017) and OECD data. Where WDI/OECD data were not available, IMF or WHO estimates were utilized. Detailed metadata are available at <https://apps.who.int/nha/database/Select/Indicators/en>.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"GC.TAX.IMPT.ZS","name":"Droits de douane et autres droits à l'importation ( % des recettes fiscales)","description":"Les impôts et droits sur les importations sont des impôts sur les biens et services qui deviennent payables au moment où les biens entrent sur le t...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.IMPT.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.TAX.IMPT.CN","name":"Droits de douane et autres droits à l'importation (LCU actuels)","description":"Les impôts et droits sur les importations sont des impôts sur les biens et services qui deviennent payables au moment où les biens entrent sur le t...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.IMPT.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"SP.DYN.CDRT.IN","name":"Taux de mortalité, brut (pour 1 000 personnes)","description":"Le taux brut de mortalité indique le nombre de décès survenus au cours de l'année, pour 1 000 habitants, estimé au milieu de l'année.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.CDRT.IN?locations=CI","methodology":"Methodology: The crude death rate is calculated as the number of deaths in a given period divided by the population exposed to risk of death in that period. For human populations the period is usually one year and, if the population changes in size over the year, the divisor is taken as the population at the mid-year. The rate is usually expressed in terms of 1,000 people: for example, a crude death rate of 9.5 (per 1000 people) in a population of 1 million would imply 9500 deaths per year in the entire population.\nStatistical concept(s): Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration. Vital rates are based on data from birth and death registration systems, censuses, and sample surveys by national statistical offices and other organizations, or on demographic analysis. Data for the most recent year for some high-income countries are provisional estimates based on vital registers. The estimates for many other countries are from the United Nations Population Division.","theme":"demo","source_group":"wb"},{"code":"DT.TDS.DPPF.XP.ZS","name":"Service de la dette à l'exportation ( %)","description":"Le service de la dette, la somme des remboursements du principal et des intérêts effectivement payés en devises, en biens ou en services, est expri...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.TDS.DPPF.XP.ZS?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.TDS.DPPG.CD","name":"Service de la dette sur la dette extérieure, publique et garantie par l'État (TDS, $ US courants)","description":"Le service de la dette publique et garantie par l'État est la somme des remboursements du principal et des intérêts effectivement payés en devises,...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.TDS.DPPG.CD?locations=CI","methodology":"Methodology: Countries that report to the World Bank’s Debtor Reporting System (DRS) submit their public and publicly guaranteed debt (PPG) and private debt with a public guarantee on a loan-by-loan basis. The World Bank Debt Data Team then compiles this information to produce this indicator.","theme":"finance","source_group":"wb"},{"code":"DT.TDS.DECT.CD","name":"Service de la dette sur la dette extérieure, total (ATD, $ US courants)","description":"Le service total de la dette est la somme des remboursements du principal et des intérêts effectivement payés en devises, biens ou services sur la ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.TDS.DECT.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"PA.NUS.ATLS","name":"Facteur de conversion alternatif DEC (LCU par dollar américain)","description":"Le facteur de conversion alternatif DEC est le taux de change annuel sous-jacent (le prix de la monnaie d’un pays par rapport à la monnaie d’un aut...","source_link":"https://donnees.banquemondiale.org/indicateur/PA.NUS.ATLS?locations=CI","methodology":"Methodology: The World Bank systematically assesses the appropriateness of official exchange rates as conversion factors. In certain countries, multiple or dual exchange rate activity exists and must be accounted for appropriately in underlying statistics. Doing so better reflects economic reality and leads to more accurate cross-country comparisons and country classifications by income level. Consequently, an alternative conversion factor is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate effectively applied to domestic transactions of foreign currencies and traded products. This applies to only a small number of countries, as shown in the country-level metadata. An alternative conversion factor is also used when the period covered by national accounts differs from the calendar year and the alternative conversion factor will then cover the same period. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Development Indicators as single-year conversion factors.\nStatistical concept(s): The World Bank systematically assesses the appropriateness of official exchange rates as conversion factors. In certain countries, multiple or dual exchange rate activity exists and must be accounted for appropriately in underlying statistics. Doing so better reflects economic reality and leads to more accurate cross-country comparisons and country classifications by income level. Consequently, an alternative conversion factor is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate effectively applied to domestic transactions of foreign currencies and traded products. This applies to only a small number of countries, as shown in the country-level metadata. An alternative conversion factor is also used when the period covered by national accounts differs from the calendar year and the alternative conversion factor will then cover the same period. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Development Indicators as single-year conversion factors.","theme":"macro","source_group":"wb"},{"code":"SH.FPL.SATM.ZS","name":"Demande de planification familiale satisfaite par les méthodes modernes ( % de femmes mariées ayant une demande de planification familiale)","description":"La demande de planification familiale satisfaite par les méthodes modernes fait référence au pourcentage de femmes mariées âgées de 15 à 49 ans don...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.FPL.SATM.ZS?locations=CI","methodology":"Methodology: This indicator is calculated from nationally-representative household survey data. Relevant data for this indicator are collected through various multi-country survey programs, including Contraceptive Prevalence Surveys (CPS), Demographic and Health Surveys (DHS), Fertility and Family Surveys (FFS), Reproductive Health Surveys (RHS), Multiple Indicator Cluster Surveys (MICS), Performance Monitoring and Accountability 2020 surveys (PMA), World Fertility Surveys (WFS), other international survey programs, and national surveys.\nData compilation involves systematic searches of websites of international survey programs, survey databases (e.g., the Integrated Household Survey Network (IHSN) database), websites of national statistical offices, SDG national reporting platforms, and ad hoc queries. Additionally, country-specific information from UNFPA country offices is utilized.","theme":"sante","source_group":"wb"},{"code":"FR.INR.DPST","name":"Taux d'intérêt des dépôts ( %)","description":"Le taux d’intérêt des dépôts est le taux payé par les banques commerciales ou similaires pour les dépôts à vue, à terme ou d’épargne.","source_link":"https://donnees.banquemondiale.org/indicateur/FR.INR.DPST?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FB.CBK.DPTR.P3","name":"Déposants auprès des banques commerciales (pour 1 000 adultes)","description":"Les déposants auprès des banques commerciales correspondent au nombre déclaré de titulaires de comptes de dépôt, y compris les sociétés non financi...","source_link":"https://donnees.banquemondiale.org/indicateur/FB.CBK.DPTR.P3?locations=CI","methodology":"Methodology: While calculating the number of depositors at each type of financial institution, the following are recommended: (a) Corporate accounts are counted as only one depositor, irrespective of the number of deposit accounts (checking, demand, saving, time deposits, etc.) held; (b) Individual accounts are counted as only one depositor, irrespective of the number of deposit accounts (checking, demand, saving, time deposits, etc.) held; (c) For joint accounts, all depositors are counted individually rather than as one depositor.\nStatistical concept(s): Depositors with commercial banks are deposit account holders at commercial banks and other resident banks functioning as commercial banks that are resident nonfinancial corporations (public and private) and households. It is calculated as (number of depositors)*1,000/adult population in the reporting country. The major types of deposits are checking accounts, savings accounts, and time deposits.","theme":"tertiary","source_group":"wb"},{"code":"SH.STA.DIAB.ZS","name":"Prévalence du diabète ( % de la population âgée de 20 à 79 ans)","description":"La prévalence du diabète fait référence au pourcentage de personnes âgées de 20 à 79 ans atteintes de diabète de type 1 ou de type 2.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.DIAB.ZS?locations=CI","methodology":"Methodology: The data used to estimate diabetes prevalence were gathered from various sources. Most of the data were extracted from peer-reviewed publications and national health surveys, including selected WHO STEPwise approach to surveillance (WHO STEPS) studies. Additionally, data from other official sources, such as registries and reports from health regulatory bodies, were utilized, provided there was sufficient information to assess their quality. Data sources with adequate methodological information on key areas of interest, such as the method of diagnosis and sample representativeness, were included. Given the significance of age as a major determinant for diabetes prevalence, only studies with at least three age-specific estimates were considered. After selecting the data sources, the reported age- and sex-specific data in each source were smoothed using a logistic regression model.","theme":"sante","source_group":"wb"},{"code":"SH.STA.ORCF.ZS","name":"Traitement de la diarrhée ( % d'enfants de moins de 5 ans recevant une réhydratation orale et une alimentation continue)","description":"Les enfants souffrant de diarrhée qui ont reçu une réhydratation orale et ont continué à s'alimenter font référence au pourcentage d'enfants de moi...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.ORCF.ZS?locations=CI","methodology":"Methodology: Mothers or caregivers of children under five years old are asked whether the child experienced diarrhea at any point in the past two weeks. If the child did have diarrhea, they are further asked whether either oral rehydration therapy or increased fluids, with continued feeding was administered. The term \"diarrhea,\" as defined by the DHS, should include all forms of diarrhea, such as bloody stools (indicative of dysentery), watery stools, and other variations. This definition encompasses both the mother's understanding and locally-used terms.","theme":"sante","source_group":"wb"},{"code":"SH.STA.ORTH","name":"Traitement de la diarrhée ( % d'enfants de moins de 5 ans ayant reçu un sachet de SRO)","description":"Pourcentage d'enfants de moins de 5 ans souffrant de diarrhée au cours des deux semaines précédant l'enquête et ayant reçu des sels de réhydratatio...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.ORTH?locations=CI","methodology":"Methodology: Mothers or caregivers of children under five years old are asked whether the child experienced diarrhea at any point in the past two weeks. If the child did have diarrhea, they are further asked whether Oral Rehydration Solution (ORS) was administered. The term \"diarrhea,\" as defined by the DHS, should include all forms of diarrhea, such as bloody stools (indicative of dysentery), watery stools, and other variations. This definition encompasses both the mother's understanding and locally-used terms.","theme":"sante","source_group":"wb"},{"code":"EN.CLC.DRSK.XQ","name":"Score de progrès en matière de réduction des risques de catastrophe (échelle de 1 à 5 ; 5 = meilleur)","description":"Le score de progrès en matière de réduction des risques de catastrophe est une moyenne des scores d’auto-évaluation, allant de 1 à 5, soumis par le...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.CLC.DRSK.XQ?locations=CI","methodology":"Methodology: Resilience is measured by the disaster risk reduction progress score, an average of self-assessment scores submitted by countries under Priority 1 of the Hyogo Framework National Progress Reports. The Hyogo Framework is a global blueprint for disaster risk reduction efforts that was adopted by 168 countries in 2005. Assessments of Priority 1 include four indicators that reflect the degree to which countries have prioritized disaster risk reduction and the strengthening of relevant institutions.","theme":"territory","source_group":"wb"},{"code":"NY.GDP.DISC.KN","name":"Écart dans l'estimation des dépenses du PIB (UCV constantes)","description":"Même si le SCN garantit une cohérence parfaite entre les trois mesures du PIB, il s’agit d’une cohérence conceptuelle qui, en général, ne ressort p...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.DISC.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.DISC.CN","name":"Écart dans l'estimation des dépenses du PIB (UCV courantes)","description":"Même si le SCN garantit une cohérence parfaite entre les trois mesures du PIB, il s’agit d’une cohérence conceptuelle qui, en général, ne ressort p...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.DISC.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"FS.AST.DOMS.GD.ZS","name":"Crédit intérieur fourni par le secteur financier ( % du PIB)","description":"Le crédit intérieur accordé par le secteur financier comprend tous les crédits accordés aux divers secteurs sur une base brute, à l'exception du cr...","source_link":"https://donnees.banquemondiale.org/indicateur/FS.AST.DOMS.GD.ZS?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FS.AST.PRVT.GD.ZS","name":"Crédit intérieur au secteur privé ( % du PIB)","description":"Le crédit intérieur au secteur privé fait référence aux ressources financières fournies au secteur privé par les sociétés financières, par exemple ...","source_link":"https://donnees.banquemondiale.org/indicateur/FS.AST.PRVT.GD.ZS?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FD.AST.PRVT.GD.ZS","name":"Crédit intérieur au secteur privé par les banques ( % du PIB)","description":"Le crédit intérieur au secteur privé par les banques fait référence aux ressources financières fournies au secteur privé par d'autres sociétés de d...","source_link":"https://donnees.banquemondiale.org/indicateur/FD.AST.PRVT.GD.ZS?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"SH.XPD.GHED.CH.ZS","name":"Dépenses de santé des administrations publiques nationales (en % des dépenses courantes de santé)","description":"Part des dépenses de santé actuelles financées par des sources publiques nationales pour la santé.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.GHED.CH.ZS?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.GHED.GD.ZS","name":"Dépenses de santé des administrations publiques nationales (en % du PIB)","description":"Dépenses publiques de santé provenant de sources nationales en part de l'économie, mesurée par le PIB.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.GHED.GD.ZS?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.GHED.GE.ZS","name":"Dépenses de santé des administrations publiques nationales (en % des dépenses des administrations publiques)","description":"Dépenses publiques de santé provenant de sources nationales en pourcentage des dépenses publiques totales.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.GHED.GE.ZS?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.GHED.PC.CD","name":"Dépenses de santé des administrations publiques nationales par habitant (en dollars courants)","description":"Dépenses publiques de santé provenant de sources nationales par habitant, exprimées en dollars américains courants.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.GHED.PC.CD?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.GHED.PP.CD","name":"Dépenses de santé des administrations publiques nationales par habitant, PPA (en dollars internationaux courants)","description":"Dépenses publiques de santé provenant de sources nationales par habitant, exprimées en dollars internationaux à parité de pouvoir d'achat.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.GHED.PP.CD?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making. WHO converted the expenditure data using PPP time series extracted from WDI (based on ICP 2017) and OECD data. Where WDI/OECD data were not available, IMF or WHO estimates were utilized. Detailed metadata are available at <https://apps.who.int/nha/database/Select/Indicators/en>.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.PVTD.CH.ZS","name":"Dépenses privées de santé domestiques ( % des dépenses courantes de santé)","description":"Part des dépenses de santé actuelles financées par des sources privées nationales.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.PVTD.CH.ZS?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.PVTD.PC.CD","name":"Dépenses intérieures de santé privées par habitant (en dollars courants)","description":"Dépenses privées actuelles de santé par habitant exprimées en dollars américains courants.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.PVTD.PC.CD?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.PVTD.PP.CD","name":"Dépenses intérieures privées de santé par habitant, PPA (en dollars internationaux courants)","description":"Dépenses privées actuelles de santé par habitant exprimées en dollars internationaux à parité de pouvoir d'achat.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.PVTD.PP.CD?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making. WHO converted the expenditure data using PPP time series extracted from WDI (based on ICP 2017) and OECD data. Where WDI/OECD data were not available, IMF or WHO estimates were utilized. Detailed metadata are available at <https://apps.who.int/nha/database/Select/Indicators/en>.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"EN.CLC.MDAT.ZS","name":"Sécheresses, inondations, températures extrêmes ( % de la population, moyenne 1990-2009)","description":"Les sécheresses, les inondations et les températures extrêmes représentent le pourcentage annuel moyen de la population touchée par des catastrophe...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.CLC.MDAT.ZS?locations=CI","methodology":"Methodology: This indicator measures vulnerability of population affected by droughts, floods, and extreme temperature. A drought is an extended period of deficiency in a region's water supply as a result of below average precipitation.","theme":"territory","source_group":"wb"},{"code":"SE.TER.CUAT.BA.FE.ZS","name":"Niveau d'éducation, au moins baccalauréat ou équivalent, population 25+, femmes ( %) (cumulé)","description":"Le pourcentage de la population âgée de 25 ans et plus qui a atteint ou terminé un baccalauréat ou l'équivalent.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.CUAT.BA.FE.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Bachelor's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.TER.CUAT.BA.MA.ZS","name":"Niveau d'éducation, au moins baccalauréat ou équivalent, population 25+, hommes ( %) (cumulatif)","description":"Le pourcentage de la population âgée de 25 ans et plus qui a atteint ou terminé un baccalauréat ou l'équivalent.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.CUAT.BA.MA.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Bachelor's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.TER.CUAT.BA.ZS","name":"Niveau d'éducation, au moins Baccalauréat ou équivalent, population 25+, total ( %) (cumulatif)","description":"Le pourcentage de la population âgée de 25 ans et plus qui a atteint ou terminé un baccalauréat ou l'équivalent.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.CUAT.BA.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Bachelor's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.SEC.CUAT.LO.FE.ZS","name":"Niveau d'éducation, au moins diplôme du premier cycle de l'enseignement secondaire, population 25+, femmes ( %) (cumulé)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou terminé le premier cycle de l'enseignement secondaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.CUAT.LO.FE.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed lower secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.SEC.CUAT.LO.MA.ZS","name":"Niveau d'éducation, au moins terminé le premier cycle de l'enseignement secondaire, population 25+, hommes ( %) (cumulé)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou terminé le premier cycle de l'enseignement secondaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.CUAT.LO.MA.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed lower secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.SEC.CUAT.LO.ZS","name":"Niveau d'éducation, au moins diplôme du premier cycle de l'enseignement secondaire, population 25+, total ( %) (cumulé)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou terminé le premier cycle de l'enseignement secondaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.CUAT.LO.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed lower secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.SEC.CUAT.PO.FE.ZS","name":"Niveau d'éducation, au moins terminé études postsecondaires, population 25+, femmes ( %) (cumulatif)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou terminé des études postsecondaires non supérieures.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.CUAT.PO.FE.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed post-secondary non-tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.SEC.CUAT.PO.MA.ZS","name":"Niveau de scolarité, au moins terminé études postsecondaires, population de 25 ans et +, hommes ( %) (cumulatif)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou terminé des études postsecondaires non supérieures.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.CUAT.PO.MA.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed post-secondary non-tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.SEC.CUAT.PO.ZS","name":"Niveau de scolarité, au moins terminé études postsecondaires, population 25+, total ( %) (cumulatif)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou terminé des études postsecondaires non supérieures.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.CUAT.PO.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed post-secondary non-tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.PRM.CUAT.FE.ZS","name":"Niveau d'éducation, au moins à l'issue de l'enseignement primaire, population de 25 ans et +, femmes ( %) (cumulé)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou terminé l'enseignement primaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.CUAT.FE.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed primary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.PRM.CUAT.MA.ZS","name":"Niveau d'instruction, au moins à l'issue de l'enseignement primaire, population de 25 ans et +, hommes ( %) (cumulé)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou terminé l'enseignement primaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.CUAT.MA.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed primary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.PRM.CUAT.ZS","name":"Niveau d'instruction, au moins terminé l'enseignement primaire, population 25+ ans, total ( %) (cumulé)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou terminé l'enseignement primaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.CUAT.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed primary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.TER.CUAT.ST.FE.ZS","name":"Niveau d'éducation, au moins diplômé de l'enseignement supérieur court, population 25+, femmes ( %) (cumulé)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou achevé un enseignement supérieur de cycle court.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.CUAT.ST.FE.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed short-cycle tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.TER.CUAT.ST.MA.ZS","name":"Niveau d'éducation, au moins diplômé de l'enseignement supérieur de cycle court, population 25+, hommes ( %) (cumulé)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou achevé un enseignement supérieur de cycle court.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.CUAT.ST.MA.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed short-cycle tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.TER.CUAT.ST.ZS","name":"Niveau d'éducation, au moins terminé dans l'enseignement supérieur de cycle court, population 25+, total ( %) (cumulé)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou achevé un enseignement supérieur de cycle court.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.CUAT.ST.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed short-cycle tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.SEC.CUAT.UP.FE.ZS","name":"Niveau d'éducation, au moins diplômé du deuxième cycle de l'enseignement secondaire, population 25+, femmes ( %) (cumulé)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou terminé le deuxième cycle de l'enseignement secondaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.CUAT.UP.FE.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed upper secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.SEC.CUAT.UP.MA.ZS","name":"Niveau d'éducation, au moins diplôme du deuxième cycle de l'enseignement secondaire, population 25+, hommes ( %) (cumulé)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou terminé le deuxième cycle de l'enseignement secondaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.CUAT.UP.MA.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed upper secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.SEC.CUAT.UP.ZS","name":"Niveau d'éducation, au moins diplôme du deuxième cycle de l'enseignement secondaire, population 25+, total ( %) (cumulé)","description":"Pourcentage de la population âgée de 25 ans et plus ayant atteint ou terminé le deuxième cycle de l'enseignement secondaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.CUAT.UP.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed upper secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.TER.CUAT.MS.FE.ZS","name":"Niveau d'éducation, au moins Master ou équivalent, population 25+, femmes ( %) (cumulé)","description":"Le pourcentage de la population âgée de 25 ans et plus qui a atteint ou terminé une maîtrise ou l'équivalent.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.CUAT.MS.FE.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Master's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.TER.CUAT.MS.MA.ZS","name":"Niveau d'éducation, au moins Master ou équivalent, population 25+, hommes ( %) (cumulé)","description":"Le pourcentage de la population âgée de 25 ans et plus qui a atteint ou terminé une maîtrise ou l'équivalent.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.CUAT.MS.MA.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Master's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.TER.CUAT.MS.ZS","name":"Niveau d'éducation, au moins Master ou équivalent, population 25+, total ( %) (cumulatif)","description":"Le pourcentage de la population âgée de 25 ans et plus qui a atteint ou terminé une maîtrise ou l'équivalent.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.CUAT.MS.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Master's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.TER.CUAT.DO.FE.ZS","name":"Niveau d'éducation, doctorat ou équivalent, population de 25 ans et +, femmes ( %) (cumulatif)","description":"Le pourcentage de la population âgée de 25 ans et plus qui a atteint ou terminé un doctorat ou l'équivalent.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.CUAT.DO.FE.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Doctoral or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.TER.CUAT.DO.MA.ZS","name":"Niveau d'éducation, doctorat ou équivalent, population 25+, hommes ( %) (cumulatif)","description":"Le pourcentage de la population âgée de 25 ans et plus qui a atteint ou terminé un doctorat ou l'équivalent.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.CUAT.DO.MA.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Doctoral or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero..\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"SE.TER.CUAT.DO.ZS","name":"Niveau d'éducation, doctorat ou équivalent, population 25+, total ( %) (cumulatif)","description":"Le pourcentage de la population âgée de 25 ans et plus qui a atteint ou terminé un doctorat ou l'équivalent.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.CUAT.DO.ZS?locations=CI","methodology":"Methodology: It is calculated by dividing the number of population ages 25 and older who attained or completed Doctoral or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\nStatistical concept(s): Educational attainment indicators by education level, serve as a measure of the accumulated stock of knowledge, skills, and competencies that are typically associated with the completion of each level. These indicators not only shed light on the disparities in educational achievement among various demographic groups, thereby offering insights into the present and past efficacy of the education system in ensuring equitable access to education, but they also mirror the structure and performance of the education system itself. Furthermore, such indicators are instrumental in guiding policy decisions aimed at expanding educational opportunities.","theme":"education","source_group":"wb"},{"code":"EG.USE.ELEC.KH.PC","name":"Consommation électrique (kWh par habitant)","description":"La consommation d'énergie électrique mesure la production des centrales électriques et des centrales de cogénération, moins les pertes de transport...","source_link":"https://donnees.banquemondiale.org/indicateur/EG.USE.ELEC.KH.PC?locations=CI","methodology":"Methodology: Electric power consumption per capita (kWh ) is the production of power plants and combined heat and power plants less transmission, distribution, and transformation losses and own use by heat and power plants, divided by midyear population. Energy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. Electricity consumption is equivalent to production less power plants' own use and transmission, distribution, and transformation losses less exports plus imports. It includes consumption by auxiliary stations, losses in transformers that are considered integral parts of those stations, and electricity produced by pumping installations. Where data are available, it covers electricity generated by primary sources of energy - coal, oil, gas, nuclear, hydro, geothermal, wind, tide and wave, and combustible renewables. Neither production nor consumption data capture the reliability of supplies, including breakdowns, load factors, and frequency of outages.","theme":"secondary","source_group":"wb"},{"code":"EG.ELC.LOSS.ZS","name":"Pertes de transport et de distribution d'énergie électrique ( % de la production)","description":"Les pertes de transport et de distribution d’énergie électrique comprennent les pertes de transport entre les sources d’approvisionnement et les po...","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.LOSS.ZS?locations=CI","methodology":"Methodology: Data on electric power production and consumption are collected from national energy agencies by the International Energy Agency (IEA) and adjusted by the IEA to meet international definitions. Electric power transmission and distribution losses percentage of output is the share of electric power transmission and distribution losses to electricity production which is the total number of GWh generated by power plants separated into electricity plants and combined heat and power (CHP) plants.","theme":"secondary","source_group":"wb"},{"code":"EG.ELC.COAL.ZS","name":"Production d'électricité à partir de sources charbonnières ( % du total)","description":"La part de la production d’électricité à partir de sources de charbon dans la production totale d’électricité.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.COAL.ZS?locations=CI","methodology":"Methodology: Electricity production is total number of kilowatt-hours (kWh) generated by power plants separated into electricity plants and combined heat and power (CHP) plants. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.\nStatistical concept(s): Electricity production is the total amount of electricity generated by power plants in an economy.","theme":"secondary","source_group":"wb"},{"code":"EG.ELC.HYRO.ZS","name":"Production d'électricité à partir de sources hydroélectriques ( % du total)","description":"La part de la production d’électricité à partir de sources hydroélectriques dans la production totale d’électricité.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.HYRO.ZS?locations=CI","methodology":"Methodology: Electricity production is total number of kilowatt-hours (kWh) generated by power plants separated into electricity plants and combined heat and power (CHP) plants. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.\nStatistical concept(s): Electricity production is the total amount of electricity generated by power plants in an economy.","theme":"secondary","source_group":"wb"},{"code":"EG.ELC.NGAS.ZS","name":"Production d'électricité à partir de sources de gaz naturel ( % du total)","description":"La part de la production d’électricité à partir de sources de gaz naturel dans la production totale d’électricité.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.NGAS.ZS?locations=CI","methodology":"Methodology: Electricity production from natural gas sources (% of total) is the share of natural gas, which is natural gas but not natural gas liquids, in total electricity production which is the total number of Gigawattt-hours (GWh) generated by power plants separated into electricity plants and combined heat and power (CHP) plants. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.\nStatistical concept(s): Electricity production is the total amount of electricity generated by power plants in an economy.","theme":"secondary","source_group":"wb"},{"code":"EG.ELC.NUCL.ZS","name":"Production d'électricité à partir de sources nucléaires ( % du total)","description":"La part de la production d’électricité à partir de sources nucléaires dans la production totale d’électricité.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.NUCL.ZS?locations=CI","methodology":"Methodology: Electricity production from nuclear sources (% of total) is the share of electricity produced by nuclear power plants in total electricity production which is the total number of Gigawattt-hours (GWh) generated by power plants separated into electricity plants and combined heat and power (CHP) plants. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.\nStatistical concept(s): Electricity production is the total amount of electricity generated by power plants in an economy.","theme":"secondary","source_group":"wb"},{"code":"EG.ELC.PETR.ZS","name":"Production d'électricité à partir de sources pétrolières ( % du total)","description":"La part de la production d’électricité à partir de sources pétrolières dans la production totale d’électricité.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.PETR.ZS?locations=CI","methodology":"Methodology: Electricity production from oil sources (% of total) is the share of electricity produced by oil and petroleum products in total electricity production which is the total number of Gigawattt-hours (GWh) generated by power plants separated into electricity plants and combined heat and power (CHP) plants. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.\nStatistical concept(s): Electricity production is the total amount of electricity generated by power plants in an economy.","theme":"secondary","source_group":"wb"},{"code":"EG.ELC.FOSL.ZS","name":"Production d'électricité à partir de pétrole, de gaz et de charbon ( % du total)","description":"La part de la production d’électricité à partir du pétrole.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.FOSL.ZS?locations=CI","methodology":"Methodology: Electricity production from oil, gas and coal sources (% of total) is the share of electricity produced by oil and petroleum products, natural gas, which is natural gas but not natural gas liquids, and coal in total electricity production which is the total number of Gigawattt-hours (GWh) generated by power plants separated into electricity plants and combined heat and power (CHP) plants. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.\nStatistical concept(s): Electricity production is the total amount of electricity generated by power plants in an economy.","theme":"secondary","source_group":"wb"},{"code":"EG.ELC.RNWX.ZS","name":"Production d'électricité à partir de sources renouvelables, à l'exclusion de l'hydroélectricité ( % du total)","description":"La part de la production d’électricité à partir de sources renouvelables dans la production totale d’électricité.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.RNWX.ZS?locations=CI","methodology":"Methodology: Electricity production from renewable sources (% of total) is the share of electricity produced by geothermal, solar photovoltaic, solar thermal, tide, wind, industrial waste, municipal waste, primary solid biofuels, biogases, biogasoline, biodiesels, other liquid biofuels, nonspecified primary biofuels and waste, and charcoal in total electricity production which is the total number of Gigawattt-hours (GWh) generated by power plants separated into electricity plants and CHP plants. Hydropower is excluded. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.\nStatistical concept(s): Electricity production is the total amount of electricity generated by power plants in an economy.","theme":"secondary","source_group":"wb"},{"code":"EG.ELC.RNWX.KH","name":"Production d'électricité à partir de sources renouvelables, à l'exclusion de l'hydroélectricité (kWh)","description":"La production d'électricité à partir de sources renouvelables en kilowattheures (kWh), à l'exclusion de l'hydroélectricité, comprend la géothermie,...","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.RNWX.KH?locations=CI","methodology":"Methodology: Electricity production from renewable sources in kilowatt-hour (kWh) is the amount of electricity produced by geothermal, solar photovoltaic, solar thermal, tide, wind, industrial waste, municipal waste, primary solid biofuels, biogases, biogasoline, biodiesels, other liquid biofuels, nonspecified primary biofuels and waste, and charcoal in total electricity production which is the total number of GWh generated by power plants separated into electricity plants and combined heat power (CHP) plants. Hydropower is excluded. The International Energy Agency (IEA) compiles data on energy inputs used to generate electricity. IEA data for countries that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. In addition, estimates are sometimes made to complete major aggregates from which key data are missing, and adjustments are made to compensate for differences in definitions. The IEA makes these estimates in consultation with national statistical offices, oil companies, electric utilities, and national energy experts.\nStatistical concept(s): Electricity production is the total amount of electricity generated by power plants in an economy.","theme":"secondary","source_group":"wb"},{"code":"SL.EMP.MPYR.FE.ZS","name":"Employeurs, femmes ( % de l'emploi féminin) (estimation modélisée de l'OIT)","description":"Les employeurs sont les travailleurs qui, travaillant pour leur propre compte ou avec un ou plusieurs partenaires, occupent le type d'emplois défin...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.MPYR.FE.ZS?locations=CI","methodology":"Methodology: The proportion of employers to the total employed is calculated as follows: Employers/Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.MPYR.MA.ZS","name":"Employeurs, hommes ( % de l'emploi masculin) (estimation modélisée de l'OIT)","description":"Les employeurs sont les travailleurs qui, travaillant pour leur propre compte ou avec un ou plusieurs partenaires, occupent le type d'emplois défin...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.MPYR.MA.ZS?locations=CI","methodology":"Methodology: The proportion of employers to the total employed is calculated as follows: Employers/Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.MPYR.ZS","name":"Employeurs, total ( % de l'emploi total) (estimation modélisée de l'OIT)","description":"Les employeurs sont les travailleurs qui, travaillant pour leur propre compte ou avec un ou plusieurs partenaires, occupent le type d'emplois défin...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.MPYR.ZS?locations=CI","methodology":"Methodology: The proportion of employers to the total employed is calculated as follows: Employers/Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SL.AGR.EMPL.ZS","name":"Emploi dans l'agriculture ( % de l'emploi total) (estimation modélisée de l'OIT)","description":"L'emploi est défini comme les personnes en âge de travailler qui étaient engagées dans une activité visant à produire des biens ou à fournir des se...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.AGR.EMPL.ZS?locations=CI","methodology":"Methodology: The series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.","theme":"emploi","source_group":"wb"},{"code":"SL.AGR.EMPL.FE.ZS","name":"Emploi des femmes dans l'agriculture ( % de l'emploi féminin) (estimation modélisée de l'OIT)","description":"L'emploi est défini comme les personnes en âge de travailler qui étaient engagées dans une activité visant à produire des biens ou à fournir des se...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.AGR.EMPL.FE.ZS?locations=CI","methodology":"Methodology: The series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.","theme":"emploi","source_group":"wb"},{"code":"SL.AGR.EMPL.MA.ZS","name":"Emploi dans l'agriculture, hommes ( % de l'emploi masculin) (estimation modélisée de l'OIT)","description":"L'emploi est défini comme les personnes en âge de travailler qui étaient engagées dans une activité visant à produire des biens ou à fournir des se...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.AGR.EMPL.MA.ZS?locations=CI","methodology":"Methodology: The series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.","theme":"emploi","source_group":"wb"},{"code":"SL.IND.EMPL.ZS","name":"Emploi dans l'industrie (en % de l'emploi total) (estimation modélisée de l'OIT)","description":"L'emploi est défini comme les personnes en âge de travailler qui étaient engagées dans une activité visant à produire des biens ou à fournir des se...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.IND.EMPL.ZS?locations=CI","methodology":"Methodology: The series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.","theme":"emploi","source_group":"wb"},{"code":"SL.IND.EMPL.FE.ZS","name":"Emploi dans l'industrie, femmes ( % de l'emploi féminin) (estimation modélisée de l'OIT)","description":"L'emploi est défini comme les personnes en âge de travailler qui étaient engagées dans une activité visant à produire des biens ou à fournir des se...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.IND.EMPL.FE.ZS?locations=CI","methodology":"Methodology: The series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.","theme":"emploi","source_group":"wb"},{"code":"SL.IND.EMPL.MA.ZS","name":"Emploi dans l'industrie, hommes ( % de l'emploi masculin) (estimation modélisée de l'OIT)","description":"L'emploi est défini comme les personnes en âge de travailler qui étaient engagées dans une activité visant à produire des biens ou à fournir des se...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.IND.EMPL.MA.ZS?locations=CI","methodology":"Methodology: The series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.","theme":"emploi","source_group":"wb"},{"code":"SL.SRV.EMPL.ZS","name":"Emploi dans les services ( % de l'emploi total) (estimation modélisée de l'OIT)","description":"L'emploi est défini comme les personnes en âge de travailler qui étaient engagées dans une activité visant à produire des biens ou à fournir des se...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.SRV.EMPL.ZS?locations=CI","methodology":"Methodology: The series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.","theme":"emploi","source_group":"wb"},{"code":"SL.SRV.EMPL.FE.ZS","name":"Emploi des femmes dans les services ( % de l'emploi féminin) (estimation modélisée de l'OIT)","description":"L'emploi est défini comme les personnes en âge de travailler qui étaient engagées dans une activité visant à produire des biens ou à fournir des se...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.SRV.EMPL.FE.ZS?locations=CI","methodology":"Methodology: The series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.","theme":"emploi","source_group":"wb"},{"code":"SL.SRV.EMPL.MA.ZS","name":"Emploi dans les services, hommes ( % de l'emploi masculin) (estimation modélisée de l'OIT)","description":"L'emploi est défini comme les personnes en âge de travailler qui étaient engagées dans une activité visant à produire des biens ou à fournir des se...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.SRV.EMPL.MA.ZS?locations=CI","methodology":"Methodology: The series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.TOTL.SP.FE.ZS","name":"Rapport emploi/population, 15+, femmes ( %) (estimation modélisée de l'OIT)","description":"Le ratio emploi/population est la proportion de la population d’un pays qui a un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.TOTL.SP.FE.ZS?locations=CI","methodology":"Methodology: The employment-to-population ratio (EPR) is calculated as follows:\n\nEPR (%) = 100 x Persons employed / Working-age population\n\nFor a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:\n\nEPRw (%) = 100 x Employed women / Working-age women\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.TOTL.SP.FE.NE.ZS","name":"Rapport emploi/population, 15+, femmes ( %) (estimation nationale)","description":"Le ratio emploi/population est la proportion de la population d’un pays qui a un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.TOTL.SP.FE.NE.ZS?locations=CI","methodology":"Methodology: The employment-to-population ratio (EPR) is calculated as follows:\n\nEPR (%) = 100 x Persons employed / Working-age population\n\nFor a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:\n\nEPRw (%) = 100 x Employed women / Working-age women\nStatistical concept(s): Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.TOTL.SP.MA.ZS","name":"Rapport emploi/population, 15+, hommes ( %) (estimation modélisée de l'OIT)","description":"Le ratio emploi/population est la proportion de la population d’un pays qui a un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.TOTL.SP.MA.ZS?locations=CI","methodology":"Methodology: The employment-to-population ratio (EPR) is calculated as follows:\n\nEPR (%) = 100 x Persons employed / Working-age population\n\nFor a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:\n\nEPRw (%) = 100 x Employed women / Working-age women\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.TOTL.SP.MA.NE.ZS","name":"Rapport emploi/population, 15+, hommes ( %) (estimation nationale)","description":"Le ratio emploi/population est la proportion de la population d’un pays qui a un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.TOTL.SP.MA.NE.ZS?locations=CI","methodology":"Methodology: The employment-to-population ratio (EPR) is calculated as follows:\n\nEPR (%) = 100 x Persons employed / Working-age population\n\nFor a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:\n\nEPRw (%) = 100 x Employed women / Working-age women\nStatistical concept(s): Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.TOTL.SP.ZS","name":"Ratio emploi/population, 15+, total ( %) (estimation modélisée de l'OIT)","description":"Le ratio emploi/population est la proportion de la population d’un pays qui a un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.TOTL.SP.ZS?locations=CI","methodology":"Methodology: The employment-to-population ratio (EPR) is calculated as follows:\n\nEPR (%) = 100 x Persons employed / Working-age population\n\nFor a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:\n\nEPRw (%) = 100 x Employed women / Working-age women\n\n\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.TOTL.SP.NE.ZS","name":"Rapport emploi/population, 15+, total ( %) (estimation nationale)","description":"Le ratio emploi/population est la proportion de la population d’un pays qui a un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.TOTL.SP.NE.ZS?locations=CI","methodology":"Methodology: The employment-to-population ratio (EPR) is calculated as follows:\n\nEPR (%) = 100 x Persons employed / Working-age population\n\nFor a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:\n\nEPRw (%) = 100 x Employed women / Working-age women\nStatistical concept(s): Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15 and older are generally considered the working-age population.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.1524.SP.FE.ZS","name":"Rapport emploi/population, 15-24 ans, femmes ( %) (estimation modélisée de l'OIT)","description":"Le ratio emploi/population est la proportion de la population d’un pays qui a un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.1524.SP.FE.ZS?locations=CI","methodology":"Methodology: The employment-to-population ratio (EPR) is calculated as follows:\n\nEPR (%) = 100 x Persons employed / Working-age population\n\nFor a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:\n\nEPRw (%) = 100 x Employed women / Working-age women\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.1524.SP.FE.NE.ZS","name":"Rapport emploi/population, 15-24 ans, femmes ( %) (estimation nationale)","description":"Le ratio emploi/population est la proportion de la population d’un pays qui a un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.1524.SP.FE.NE.ZS?locations=CI","methodology":"Methodology: The employment-to-population ratio (EPR) is calculated as follows:\n\nEPR (%) = 100 x Persons employed / Working-age population\n\nFor a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:\n\nEPRw (%) = 100 x Employed women / Working-age women\nStatistical concept(s): Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.1524.SP.MA.ZS","name":"Rapport emploi/population, 15-24 ans, hommes ( %) (estimation modélisée de l'OIT)","description":"Le ratio emploi/population est la proportion de la population d’un pays qui a un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.1524.SP.MA.ZS?locations=CI","methodology":"Methodology: The employment-to-population ratio (EPR) is calculated as follows:\n\nEPR (%) = 100 x Persons employed / Working-age population\n\nFor a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:\n\nEPRw (%) = 100 x Employed women / Working-age women\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.1524.SP.MA.NE.ZS","name":"Rapport emploi/population, 15-24 ans, hommes ( %) (estimation nationale)","description":"Le ratio emploi/population est la proportion de la population d’un pays qui a un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.1524.SP.MA.NE.ZS?locations=CI","methodology":"Methodology: The employment-to-population ratio (EPR) is calculated as follows:\n\nEPR (%) = 100 x Persons employed / Working-age population\n\nFor a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:\n\nEPRw (%) = 100 x Employed women / Working-age women\nStatistical concept(s): Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.1524.SP.ZS","name":"Rapport emploi/population, 15-24 ans, total ( %) (estimation modélisée de l'OIT)","description":"Le ratio emploi/population est la proportion de la population d’un pays qui a un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.1524.SP.ZS?locations=CI","methodology":"Methodology: The employment-to-population ratio (EPR) is calculated as follows:\n\nEPR (%) = 100 x Persons employed / Working-age population\n\nFor a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:\n\nEPRw (%) = 100 x Employed women / Working-age women\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.1524.SP.NE.ZS","name":"Rapport emploi/population, 15-24 ans, total ( %) (estimation nationale)","description":"Le ratio emploi/population est la proportion de la population d’un pays qui a un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.1524.SP.NE.ZS?locations=CI","methodology":"Methodology: The employment-to-population ratio (EPR) is calculated as follows:\n\nEPR (%) = 100 x Persons employed / Working-age population\n\nFor a given component group of the working-age population, the EPR is the percentage of this group that is employed. For example, the EPR for women would be calculated as:\n\nEPRw (%) = 100 x Employed women / Working-age women\nStatistical concept(s): Employment is defined as persons of working age who, during a short reference period, were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period (i.e. who worked in a job for at least one hour) or not at work due to temporary absence from a job, or to working-time arrangements. Ages 15-24 are generally considered the youth population.","theme":"emploi","source_group":"wb"},{"code":"EG.IMP.CONS.ZS","name":"Importations d'énergie, nettes ( % de la consommation d'énergie)","description":"Les importations nettes d’énergie sont estimées comme les importations brutes moins les exportations brutes, toutes deux mesurées en tonnes d’équiv...","source_link":"https://donnees.banquemondiale.org/indicateur/EG.IMP.CONS.ZS?locations=CI","methodology":"Methodology: Energy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments.\n\nA negative value in energy imports indicates that the country is a net exporter. Energy use refers to use of primary energy before transformation to other end-use fuels, which is equal to indigenous production plus imports and stock changes, minus exports and fuels supplied to ships and aircraft engaged in international transport.","theme":"secondary","source_group":"wb"},{"code":"EG.EGY.PRIM.PP.KD","name":"Niveau d'intensité énergétique de l'énergie primaire (MJ/PIB PPA de 2017)","description":"Le niveau d’intensité énergétique de l’énergie primaire est le rapport entre l’approvisionnement énergétique et le produit intérieur brut mesuré à ...","source_link":"https://donnees.banquemondiale.org/indicateur/EG.EGY.PRIM.PP.KD?locations=CI","methodology":"Methodology: This indicator is obtained by dividing total primary energy supply over gross domestic product measured in constant 2017 US dollars at purchasing power parity.","theme":"secondary","source_group":"wb"},{"code":"EG.USE.PCAP.KG.OE","name":"Consommation d'énergie (kg d'équivalent pétrole par habitant)","description":"La consommation d’énergie fait référence à l’utilisation de l’énergie primaire avant transformation en d’autres carburants d’utilisation finale, qu...","source_link":"https://donnees.banquemondiale.org/indicateur/EG.USE.PCAP.KG.OE?locations=CI","methodology":"Methodology: Total energy use refers to the use of primary energy before transformation to other end-use fuels (such as electricity and refined petroleum products). It includes energy from combustible renewables and waste - solid biomass and animal products, gas and liquid from biomass, and industrial and municipal waste. Biomass is any plant matter used directly as fuel or converted into fuel, heat, or electricity. World Bank population estimates are used to calculate per capita data.\nEnergy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments.\n\n\n\n\n\n\n\n\n\n\n\nData for combustible renewables and waste are often based on small surveys or other incomplete information and thus give only a broad impression of developments and are not strictly comparable across countries. The IEA reports include country notes that explain some of these differences. All forms of energy - primary energy and primary electricity - are converted into oil equivalents. A notional thermal efficiency of 33 percent is assumed for converting nuclear electricity into oil equivalents and 100 percent efficiency for converting hydroelectric power.\nStatistical concept(s):","theme":"secondary","source_group":"wb"},{"code":"EG.USE.COMM.GD.PP.KD","name":"Consommation d'énergie (kg d'équivalent pétrole) par 1 000 $ de PIB (PPA constante de 2017)","description":"La consommation d’énergie par PIB PPA est le kilogramme d’équivalent pétrole de consommation d’énergie par PIB PPA constant.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.USE.COMM.GD.PP.KD?locations=CI","methodology":"Methodology: The indicator is calculated by dividing the total energy use (in kg of oil equivalent) by the total GDP (in constant 2017 PPP dollars) and then multiplying by 1000, to express the energy use per $1,000 of GDP.","theme":"secondary","source_group":"wb"},{"code":"SH.STA.BFED.ZS","name":"Allaitement maternel exclusif ( % d'enfants de moins de 6 mois)","description":"L'allaitement maternel exclusif fait référence au pourcentage d'enfants de moins de six mois qui ont été nourris uniquement au lait maternel (sans ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.BFED.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by dividing the number of infants aged 0–5 months who received only breast milk during the previous day by the total number of infants aged 0–5 months, then multiplying the result by 100.\nData collection involves Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), which include questions about liquids and foods given the previous day, as well as the number of milk feeds the previous day, to determine if the child is being exclusively breastfed. WHO and UNICEF jointly collect data on infant and young child feeding, pooling information from national surveys. Additionally, the WHO Programme of Nutrition, Physical Activity, and Obesity at the Regional Office for Europe independently compiles country-specific information on exclusive breastfeeding.","theme":"sante","source_group":"wb"},{"code":"SE.XPD.PRIM.ZS","name":"Dépenses consacrées à l'enseignement primaire (en % des dépenses publiques consacrées à l'éducation)","description":"Les dépenses consacrées à l'enseignement primaire sont exprimées en pourcentage des dépenses totales des administrations publiques en matière d'édu...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.XPD.PRIM.ZS?locations=CI","methodology":"Methodology: The share of expenditure on primary education to total government expenditure on education is calculated by dividing government expenditure on primary education by total government expenditure on education (all levels combined), and multiplying by 100. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.XPD.SECO.ZS","name":"Dépenses consacrées à l'enseignement secondaire (en % des dépenses publiques consacrées à l'éducation)","description":"Les dépenses consacrées à l'enseignement secondaire sont exprimées en pourcentage des dépenses totales des administrations publiques en matière d'é...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.XPD.SECO.ZS?locations=CI","methodology":"Methodology: The share of expenditure on secondary education to total government expenditure on education is calculated by dividing government expenditure on secondary education by total government expenditure on education (all levels combined), and multiplying by 100. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.XPD.TERT.ZS","name":"Dépenses consacrées à l'enseignement supérieur (en % des dépenses publiques consacrées à l'éducation)","description":"Les dépenses consacrées à l’enseignement supérieur sont exprimées en pourcentage du total des dépenses publiques consacrées à l’éducation.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.XPD.TERT.ZS?locations=CI","methodology":"Methodology: The share of expenditure on tertiary education to total government expenditure on education is calculated by dividing government expenditure on tertiary education by total government expenditure on education (all levels combined), and multiplying by 100. Aggregate data are based on World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"GC.XPN.TOTL.GD.ZS","name":"Charges ( % du PIB)","description":"La dépense est une diminution de la valeur nette résultant d’une transaction.","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.TOTL.GD.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.XPN.TOTL.CN","name":"Charges (LCU courantes)","description":"La dépense est une diminution de la valeur nette résultant d’une transaction.","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.TOTL.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"TX.UVI.MRCH.XD.WD","name":"Indice de valeur unitaire des exportations (2015 = 100)","description":"Les indices de valeur unitaire des exportations proviennent de la base de données sur le commerce de la CNUCED.","source_link":"https://donnees.banquemondiale.org/indicateur/TX.UVI.MRCH.XD.WD?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.XD.WD","name":"Indice de valeur des exportations (2015 = 100)","description":"La valeur des exportations est la valeur actuelle des exportations (f.a.b.) convertie en dollars américains et exprimée en pourcentage de la moyenn...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.XD.WD?locations=CI","methodology":"Methodology: The value indices show the current value of exports (f.o.b.) for an economy, after conversion to United States dollars and with the reference year =100. Thus it is simply derived from monetary values from the total trade series or from the trade matrix and exchange rates.","theme":"inter","source_group":"wb"},{"code":"TX.QTY.MRCH.XD.WD","name":"Indice du volume des exportations (2015 = 100)","description":"Les indices de volume des exportations sont dérivés des séries d'indices de volume de la CNUCED et correspondent au rapport entre les indices de va...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.QTY.MRCH.XD.WD?locations=CI","methodology":"Methodology: The Export Volume Index (base year 2015 = 100) measures changes in the physical volume of merchandise exports over time, adjusting for price effects. By The Export Volume Index (base year 2015 = 100) measures changes in the physical volume of merchandise exports over time, adjusting for price effects. By removing the influence of price changes, this index isolates real growth or contraction in exported quantities. A value above 100 indicates that the volume of exports has increased relative to the base year, while a value below 100 signals a reduction.\n\nTo calculate the index, nominal export values are deflated using export price indices or unit value series, depending on the availability of data. These deflated values are then compared to the base year to produce an index that is normalized to 100 in 2015. The index covers all merchandise exports, and values are aggregated at the national level across products and partner economies.\n\nThe Export Volume Index helps distinguish between growth due to increased trade activity and growth driven solely by price inflation. It is particularly relevant for monitoring export performance in real terms, analyzing supply chain trends, and identifying structural shifts in trade composition. This index can inform decisions on industrial policy, export diversification, and investment in production capacity. It may also support economic modeling exercises requiring real trade variables.","theme":"inter","source_group":"wb"},{"code":"NY.EXP.CAPM.KN","name":"Exportations en tant que capacité d'importation (UCV constante)","description":"Les exportations en tant que capacité d’importation sont égales à la valeur des prix courants des exportations de biens et services déflatée par l’...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.EXP.CAPM.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"NE.EXP.GNFS.ZS","name":"Exportations de biens et de services (en % du PIB)","description":"Les exportations de biens incluent les changements dans la propriété économique des biens des résidents de l’économie déclarante vers les non-résid...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.EXP.GNFS.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"NE.EXP.GNFS.KD.ZG","name":"Exportations de biens et de services (croissance annuelle en %)","description":"Les exportations de biens incluent les changements dans la propriété économique des biens des résidents de l’économie déclarante vers les non-résid...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.EXP.GNFS.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"BX.GSR.GNFS.CD","name":"Exportations de biens et de services ($ US courants, BdP)","description":"Les exportations de biens incluent les changements dans la propriété économique des biens des résidents de l’économie déclarante vers les non-résid...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GSR.GNFS.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"NE.EXP.GNFS.KD","name":"Exportations de biens et de services (en dollars constants de 2015)","description":"Les exportations de biens incluent les changements dans la propriété économique des biens des résidents de l’économie déclarante vers les non-résid...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.EXP.GNFS.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"NE.EXP.GNFS.KN","name":"Exportations de biens et de services (UCT constantes)","description":"Les exportations de biens incluent les changements dans la propriété économique des biens des résidents de l’économie déclarante vers les non-résid...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.EXP.GNFS.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"NE.EXP.GNFS.CN","name":"Exportations de biens et de services (UCL courantes)","description":"Les exportations de biens incluent les changements dans la propriété économique des biens des résidents de l’économie déclarante vers les non-résid...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.EXP.GNFS.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"NE.EXP.GNFS.CD","name":"Exportations de biens et de services (en dollars américains courants)","description":"Les exportations de biens incluent les changements dans la propriété économique des biens des résidents de l’économie déclarante vers les non-résid...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.EXP.GNFS.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"BX.GSR.TOTL.CD","name":"Exportations de biens, de services et de revenus primaires ($ US courants, BdP)","description":"Les exportations de biens incluent les changements dans la propriété économique des biens des résidents de l’économie déclarante vers les non-résid...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GSR.TOTL.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"NE.RSB.GNFS.ZS","name":"Solde extérieur des biens et services (en % du PIB)","description":"La balance du commerce international des biens et services est la différence entre les exportations et les importations de biens et services.","source_link":"https://donnees.banquemondiale.org/indicateur/NE.RSB.GNFS.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"NE.RSB.GNFS.KN","name":"Solde extérieur des biens et services (UCL constantes)","description":"La balance du commerce international des biens et services est la différence entre les exportations et les importations de biens et services.","source_link":"https://donnees.banquemondiale.org/indicateur/NE.RSB.GNFS.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"NE.RSB.GNFS.CN","name":"Solde extérieur des biens et services (UCL courante)","description":"La balance du commerce international des biens et services est la différence entre les exportations et les importations de biens et services.","source_link":"https://donnees.banquemondiale.org/indicateur/NE.RSB.GNFS.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"NE.RSB.GNFS.CD","name":"Solde extérieur des biens et services (en dollars courants des États-Unis)","description":"La balance du commerce international des biens et services est la différence entre les exportations et les importations de biens et services.","source_link":"https://donnees.banquemondiale.org/indicateur/NE.RSB.GNFS.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"DT.DOD.DECT.GN.ZS","name":"Encours de la dette extérieure ( % du RNB)","description":"Encours total de la dette extérieure par rapport au revenu national brut.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.DECT.GN.ZS?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.DOD.DLXF.CD","name":"Encours de la dette extérieure, à long terme (DOD, $ US courants)","description":"La dette à long terme est une dette dont l’échéance initiale ou prolongée est supérieure à un an.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.DLXF.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.DOD.DPNG.CD","name":"Encours de la dette extérieure privée non garantie (PNG) (DOD, dollars américains courants)","description":"La dette extérieure privée non garantie comprend les obligations extérieures à long terme des débiteurs privés dont le remboursement n'est pas gara...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.DPNG.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.DOD.DPPG.CD","name":"Encours de la dette extérieure, publique et garantie par l'État (DOD, $ US courants)","description":"La dette publique et garantie par l'État comprend les obligations extérieures à long terme des débiteurs publics, notamment le gouvernement nationa...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.DPPG.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.DOD.DSTC.CD","name":"Encours de la dette extérieure, à court terme (DOD, $ US courants)","description":"La dette extérieure à court terme est définie comme une dette dont l’échéance initiale est d’un an ou moins.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.DSTC.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.DOD.DECT.CD","name":"Encours de la dette extérieure, total (DOD, $ US courants)","description":"La dette extérieure totale est la dette due aux non-résidents et remboursable en devises, en biens ou en services.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.DECT.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"SH.XPD.EHEX.CH.ZS","name":"Dépenses externes de santé (en % des dépenses de santé courantes)","description":"Part des dépenses de santé courantes financées par des sources externes.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.EHEX.CH.ZS?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.EHEX.PC.CD","name":"Dépenses externes de santé par habitant (en dollars courants des États-Unis)","description":"Dépenses extérieures courantes de santé par habitant exprimées en dollars américains courants.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.EHEX.PC.CD?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.EHEX.PP.CD","name":"Dépenses externes de santé par habitant, PPA (en dollars internationaux courants)","description":"Dépenses extérieures courantes de santé par habitant exprimées en dollars internationaux à parité de pouvoir d'achat.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.EHEX.PP.CD?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making. WHO converted the expenditure data using PPP time series extracted from WDI (based on ICP 2017) and OECD data. Where WDI/OECD data were not available, IMF or WHO estimates were utilized. Detailed metadata are available at <https://apps.who.int/nha/database/Select/Indicators/en>.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.STA.FGMS.ZS","name":"Prévalence des mutilations génitales féminines ( %)","description":"Pourcentage de femmes âgées de 15 à 49 ans ayant subi une ablation partielle ou totale des organes génitaux externes féminins ou une autre blessure...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.FGMS.ZS?locations=CI","methodology":"Methodology: The indicator is calculated by the number of women ages 15-49 who have undergone FGM divided by the total number of women ages 15-49 in the population multiplied by 100.   The primary sources for this indicator are the Multiple Indicator Cluster Surveys (MICS) and the Demographic and Health Surveys (DHS).  The majority of the data are compiled by UNICEF, which coordinates with countries to gather the information.\nStatistical concept(s): Female genital mutilation (FGM) encompasses all practices that involve the partial or total removal of the external female genitalia, or other injury to the female genital organs, for non-medical reasons. Typically, this procedure is carried out on minors.","theme":"sante","source_group":"wb"},{"code":"SP.HOU.FEMA.ZS","name":"Ménages dirigés par des femmes ( % des ménages)","description":"Les ménages dirigés par une femme font référence au pourcentage de ménages dirigés par une femme.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.HOU.FEMA.ZS?locations=CI","methodology":"Methodology: The indicator is calculated by the number of households headed by women divided by the total number of households.  \nThe definition of a household is a person or group of related or unrelated persons who live together in the same dwelling unit(s), who acknowledge one adult male or female as the head of the household, who share the same housekeeping arrangements and who are considered a single unit.\nStatistical concept(s): The information on the characteristics of household head (e.g., sex, age) is collected the household questionnaire in the Demographic and Health Surveys (DHS). Typically, this data is obtained by detailing the connection of each member of the household to a designated central figure, who is considered the primary reference for the household.","theme":"social","source_group":"wb"},{"code":"SE.LPV.PRIM.SD.FE","name":"Filles en âge de fréquenter l'école primaire non scolarisées ( %)","description":"La proportion de filles en âge d’aller à l’école primaire qui ne sont pas scolarisées ou qui sont privées de scolarité.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.LPV.PRIM.SD.FE?locations=CI","methodology":"Methodology: Schooling Deprivation is derived using enrollment rates computed by UIS using administrative records and follows the SDG 4.1.4 indicator. To ensure country coverage of data, we consider other enrollment definitions to use for learning poverty, if the first-best option is not available. \nWe construct an enrollment dataset from 1990 to the year of the current release, relying on multiple enrollment definitions. Our dataset is constructed from UIS (UNESCO Institute of Statistics), and other sources suggested by World Bank regional or country education specialists. Data sources are typically from administrative records (school registers or school censuses) for data on enrolment by age, and UNPD population estimates for school-age population (UIS). Enrolment by single years of age in all levels of education and the total primary-school-age population are used to compute enrollment rates.\nWe follow this hierarchy of enrollment definitions: Country specialist validated data > Adjusted Net Enrollment Rate (ANER) > Total Net Enrollment Rate (TNER) > Net enrollment rate (NER) > Gross Enrollment Rate (GER; if the gross enrollment rate is higher than 100%, it is adjusted to be 100%).\nOur preferred measure of school participation is ANER, because it accounts for some primary school aged children who might enter primary school early and advance to secondary school before they reach the official upper age limit of primary education. Adjusted net enrollment is a measure of both “stock” and “flow” and accounts for both age- and grade-based distortions, as it is the percent of primary school age children enrolled either in primary or secondary education, as opposed to gross enrollment which is the share of children of any age that are enrolled in primary school, or net enrollment which is the share of primary school age children that are enrolled in primary school. The next-best indicator is used if ANER is unavailable. In some cases, country specialists will provide a data point that reflects enrollment in the country better than UIS statistics which is used. In future Learning Poverty releases, the enrollment hierarchy may be adjusted as availability of indicator definitions change. \nThe enrollment year used is the one that best pairs with the assessment year used to compute Learning Deprivation. The year of the preferred assessment is the base. If the same enrollment year is not available, we use a step function to fill the data in with the value of the closest year. If there is data available for two years equally close to the year to fill, the older value is used. This procedure to extrapolate enrollment for missing values is required for us to pair the proficiency measure with enrollment measures from the same year, or its best proxy when enrollment is not available for the same year of the assessment.\nStatistical concept(s): Minimum Proficiency Level (MPL) in Reading","theme":"education","source_group":"wb"},{"code":"SE.LPV.PRIM.LD.FE","name":"Élèves de sexe féminin ayant des compétences minimales en lecture à la fin de l'enseignement primaire ( %). Seuil GAML bas","description":"La proportion d'élèves de sexe féminin à la fin de l'école primaire qui se situent en dessous du niveau minimum de compétence (MPL) en lecture ou e...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.LPV.PRIM.LD.FE?locations=CI","methodology":"Methodology: Learning assessments used to calculate Learning Poverty have a minimum proficiency level (MPL) benchmarked by Global Alliance to Monitor Learning (GAML) under the leadership of the UNESCO Institute of Statistics (UIS), which occurred within the reporting window. To operationalize this concept, the current SDG monitoring process is followed by defining “proficiency” as reaching at least the Low International Benchmark on the international PIRLS literacy assessment. \nPIRLS is the major global primary-age assessment focused on reading, and if all countries participated in it, the task of constructing global estimates of minimum proficiency would be trivial, as it would require aggregating results from a single cross-national assessment. However, most countries participating in PIRLS are high-income, and only a small minority of low- and middle-income countries participate in the assessment. One of the main contributions of the GAML process is that it has overcome this data gap by benchmarking several major cross-national assessments—and increasingly national learning assessments as well—against the standard. \nThe MPL for each learning assessment is used to calculate the reading proficiency rate for that country, which is the share of students scoring at or above the minimum proficiency level, and conversely to calculate the learning deprivation.\nThe Proficiency and Grade Levels used for each assessment is as follows: PIRLS (grade 4) - Level 2 (Low international benchmark, 400 points); TIMSS (grade 4) - Level 2 (Low international benchmark, 400 points); LLECE (SERCE, grade 6) - Level 3 (513.66 points); PASEC (grades 5 and 6) - Level 4 (595.1 points); SEA-PLM (grade 5) - Level 6 and above; National Learning Assessment (grade 4, 5 and 6) - Varies by country. \nWhen a given country had administered multiple types of learning assessments, a hierarchy is applied in the order listed below to ensure best comparability across countries: International or Regional Learning Assessment for Reading (PIRLS, LLECE, PASEC, SEA-PLM) > TIMSS Science > Statistical or Pairwise Linking Exercises > AMPL-bs, Policy Linked National Learning Assessments or Policy Linked Service Delivery Indicators (SDIs) > Non-Policy Linked NLAs (Interim Reporting).\nNote that as the GAML and joint coalitions continue their efforts to improve learning data coverage, the hierarchy may be revised.\nStatistical concept(s): Minimum Proficiency Level (MPL) in Reading","theme":"education","source_group":"wb"},{"code":"SL.EMP.SMGT.FE.ZS","name":"Part des femmes dans l'emploi des cadres supérieurs et intermédiaires ( %)","description":"La part des femmes dans l'emploi des cadres supérieurs et intermédiaires traduit le nombre de femmes occupant des postes d'encadrement en pourcenta...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.SMGT.FE.ZS?locations=CI","methodology":"Methodology: The data for this indicator is collected through labor force surveys or any other household survey which collects such data through a module on employment. Establishment/firm surveys or administrative records can also provide useful data on female-occupied management positions by ISCO groups. Surveys are conducted by national statistical offices or ministries of labor in countries.\nStatistical concept(s): Employment comprises all persons of working age who, during a short reference period (one week), were engaged in any activity to produce goods or provide services for pay or profit. For further clarification, see: Resolution concerning statistics of work, employment and labor underutilization (2013).\n\nEmployment in management is determined according to the categories of the latest version of the International Standard Classification of Occupations (ISCO-08), which organizes jobs into a clearly defined set of groups based on the tasks and duties undertaken in the job. For the purposes of this indicator, it is preferable to refer separately to senior and middle management only on one hand, and to total management (including junior management) on the other. Senior and middle management correspond to sub-major groups 11, 12 and 13 in ISCO-08 and sub-major groups 11 and 12 in ISCO-88. If statistics are not available disaggregated at the sub-major group level (two-digit level of ISCO), then major group 1 of ISCO-88 and ISCO-08 can be used as a proxy and the indicator would then refer only to total management (including junior management).","theme":"emploi","source_group":"wb"},{"code":"SP.DYN.TFRT.IN","name":"Taux de fécondité, total (naissances par femme)","description":"L'indice synthétique de fécondité représente le nombre d'enfants qui naîtraient d'une femme si elle vivait jusqu'à la fin de ses années de procréat...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.TFRT.IN?locations=CI","methodology":"Methodology: Total fertility rate is the sum of the age-specific fertility rates (multiplied by five, if the age-specific fertility rates are for 5-year age groups).\nStatistical concept(s): Total fertility rates are based on data on registered live births from vital registration systems or, in the absence of such systems, from censuses or sample surveys. The estimated rates are generally considered reliable measures of fertility in the recent past. Where no empirical information on age-specific fertility rates is available, a model is used to estimate the share of births to adolescents. For countries without reliable vital registration systems fertility rates are generally based on extrapolations from trends observed in censuses or surveys from earlier years.","theme":"demo","source_group":"wb"},{"code":"AG.CON.FERT.PT.ZS","name":"Consommation d'engrais ( % de la production d'engrais)","description":"La consommation d'engrais mesure la quantité d'éléments nutritifs utilisés par les plantes par unité de terre arable.","source_link":"https://donnees.banquemondiale.org/indicateur/AG.CON.FERT.PT.ZS?locations=CI","methodology":"Methodology: Fertilizer consumption measures the quantity of plant nutrients, and is calculated as production plus imports minus exports. Because some chemical compounds used for fertilizers have other industrial applications, the consumption data may overstate the quantity available for crops. Fertilizer consumption as a share of production shows the agriculture sector's vulnerability to import and energy price fluctuation.\nMost fertilizers that are commonly used in agriculture contain the three basic plant nutrients - nitrogen, phosphorus, and potassium. Some fertilizers also contain certain \"micronutrients,\" such as zinc and other metals that are necessary for plant growth. Materials that are applied to the land primarily to enhance soil characteristics (rather than as plant food) are commonly referred to as soil amendments. Fertilizers and soil amendments are largely derived from raw material, composts and other organic matter, and wastes, such as sewage sludge and certain industrial wastes.\n\n\n\n\n\n\n\n\n\n\n\nFAO defines arable land as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow; land abandoned as a result of shifting cultivation is excluded.\nStatistical concept(s):","theme":"primary","source_group":"wb"},{"code":"AG.CON.FERT.ZS","name":"Consommation d'engrais (kilogrammes par hectare de terres arables)","description":"La consommation d'engrais mesure la quantité d'éléments nutritifs utilisés par les plantes par unité de terre arable.","source_link":"https://donnees.banquemondiale.org/indicateur/AG.CON.FERT.ZS?locations=CI","methodology":"Methodology: Fertilizer consumption measures the quantity of plant nutrients, and is calculated as production plus imports minus exports. Because some chemical compounds used for fertilizers have other industrial applications, the consumption data may overstate the quantity available for crops. Fertilizer consumption as a share of production shows the agriculture sector's vulnerability to import and energy price fluctuation.\nMost fertilizers that are commonly used in agriculture contain the three basic plant nutrients - nitrogen, phosphorus, and potassium. Some fertilizers also contain certain \"micronutrients,\" such as zinc and other metals that are necessary for plant growth. Materials that are applied to the land primarily to enhance soil characteristics (rather than as plant food) are commonly referred to as soil amendments. Fertilizers and soil amendments are largely derived from raw material, composts and other organic matter, and wastes, such as sewage sludge and certain industrial wastes.\n\n\n\n\n\n\n\n\n\n\n\nFAO defines arable land as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow; land abandoned as a result of shifting cultivation is excluded.\nStatistical concept(s):","theme":"primary","source_group":"wb"},{"code":"EN.GHG.FGAS.IP.MT.CE.AR5","name":"Émissions de gaz à effet de serre fluorés (gaz fluorés) provenant des procédés industriels (Mt CO2e)","description":"Une mesure des émissions annuelles de gaz fluorés (hydrofluorocarbures (HFC), perfluorocarbures (PFC) et hexafluorure de soufre (SF6)), provenant d...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.FGAS.IP.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"NE.CON.TOTL.ZS","name":"Dépenses de consommation finale (en % du PIB)","description":"Les dépenses de consommation finale sont les dépenses en biens et services effectuées par les unités institutionnelles résidentes pour la satisfact...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.TOTL.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.TOTL.KD.ZG","name":"Dépenses de consommation finale ( % de croissance annuelle)","description":"Les dépenses de consommation finale sont les dépenses en biens et services effectuées par les unités institutionnelles résidentes pour la satisfact...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.TOTL.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.TOTL.KD","name":"Dépenses de consommation finale (en dollars constants de 2015)","description":"Les dépenses de consommation finale sont les dépenses en biens et services effectuées par les unités institutionnelles résidentes pour la satisfact...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.TOTL.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.TOTL.KN","name":"Dépense de consommation finale (UCT constantes)","description":"Les dépenses de consommation finale sont les dépenses en biens et services effectuées par les unités institutionnelles résidentes pour la satisfact...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.TOTL.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.TOTL.CN","name":"Dépenses de consommation finale (UCL courantes)","description":"Les dépenses de consommation finale sont les dépenses en biens et services effectuées par les unités institutionnelles résidentes pour la satisfact...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.TOTL.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.TOTL.CD","name":"Dépenses de consommation finale (en dollars américains courants)","description":"Les dépenses de consommation finale sont les dépenses en biens et services effectuées par les unités institutionnelles résidentes pour la satisfact...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.TOTL.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NV.FSM.TOTL.KN","name":"Services d'intermédiaires financiers mesurés indirectement (SIFIM) (UCV constantes)","description":"Services d'intermédiation financière qui sont implicitement facturés sous la forme soit de la différence entre un taux de référence et le taux d'in...","source_link":"https://donnees.banquemondiale.org/indicateur/NV.FSM.TOTL.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"tertiary","source_group":"wb"},{"code":"NV.FSM.TOTL.CN","name":"Services d'intermédiaires financiers indirectement mesurés (SIFIM) (LCU courante)","description":"Services d'intermédiation financière qui sont implicitement facturés sous la forme soit de la différence entre un taux de référence et le taux d'in...","source_link":"https://donnees.banquemondiale.org/indicateur/NV.FSM.TOTL.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"tertiary","source_group":"wb"},{"code":"IC.FRM.ENGM.ZS","name":"Entreprises adoptant des mesures de gestion de l'énergie pour réduire les émissions, les déchets ou la pollution ( % des entreprises)","description":"Le pourcentage d'entreprises ayant adopté des mesures de gestion de l'énergie pour réduire les émissions au cours des trois dernières années.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.ENGM.ZS?locations=CI","methodology":"The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.\n\nSince 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"IC.FRM.CMPU.ZS","name":"Entreprises en concurrence avec des entreprises non enregistrées ( % des entreprises)","description":"Pourcentage d'entreprises en concurrence avec des entreprises non enregistrées ou informelles.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.CMPU.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.TAX.GIFT.ZS","name":"Entreprises censées offrir des cadeaux lors de réunions avec des agents des impôts ( % des entreprises)","description":"Pourcentage d'entreprises censées offrir des cadeaux ou des paiements informels lors de réunions avec des agents du fisc.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.TAX.GIFT.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.ELC.OUTG.ZS","name":"Entreprises ayant subi des pannes d'électricité ( % des entreprises)","description":"Pourcentage d'entreprises qui ont connu des pannes de courant au cours du dernier exercice complet.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.ELC.OUTG.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.FRM.EXS.ZS","name":"Entreprises exportant directement au moins 10 % de leurs ventes ( % des entreprises)","description":"Le pourcentage d'entreprises qui exportent directement au moins 10 % de leurs ventes annuelles totales.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.EXS.ZS?locations=CI","methodology":"The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.\n\nSince 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"IC.FRM.TAXE.ZS","name":"Entreprises remplissant leurs impôts par voie électronique ( % des entreprises)","description":"Le pourcentage d'entreprises payant leurs impôts par voie électronique.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.TAXE.ZS?locations=CI","methodology":"The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.\n\nSince 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"IC.FRM.FREG.ZS","name":"Entreprises officiellement enregistrées au début de leurs activités ( % des entreprises)","description":"Pourcentage d’entreprises officiellement enregistrées lorsqu’elles ont démarré leurs activités dans le pays.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.FREG.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.FRM.CO2.ZS","name":"Entreprises surveillant leurs propres émissions de CO2 ( % des entreprises)","description":"Le pourcentage d'entreprises surveillant leurs propres émissions de CO2 au cours des 3 dernières années.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.CO2.ZS?locations=CI","methodology":"The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.\n\nSince 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"IC.FRM.TRNG.ZS","name":"Entreprises offrant une formation formelle ( % des entreprises)","description":"Pourcentage d'entreprises proposant des programmes de formation formels à leurs employés permanents à temps plein.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.TRNG.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.FRM.CRDC.FL.ZS","name":"Entreprises qui sont entièrement limitées en matière de crédit ( % des entreprises)","description":"Les entreprises sont considérées comme totalement contraintes de crédit si elles n’ont pas accès au financement externe et si l’une des deux condit...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.CRDC.FL.ZS?locations=CI","methodology":"The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.\n\nSince 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"IC.FRM.CRDC.PT.ZS","name":"Entreprises partiellement contraintes en matière de crédit ( % des entreprises)","description":"Les entreprises sont classées comme partiellement contraintes de crédit si l’une des conditions suivantes est remplie : (1) l’entreprise a demandé ...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.CRDC.PT.ZS?locations=CI","methodology":"The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.\n\nSince 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"IC.FRM.INFM.ZS","name":"Entreprises qui ne déclarent pas toutes les ventes aux fins de l'impôt ( % des entreprises)","description":"Les entreprises qui ne déclarent pas toutes leurs ventes à des fins fiscales correspondent au pourcentage d'entreprises qui ont déclaré qu'une entr...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.INFM.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.FRM.NPRD.ZS","name":"Entreprises qui ont lancé un nouveau produit, un nouveau service et un nouveau processus, et qui ont dépensé en R-D","description":"Pourcentage d'entreprises qui ont introduit un nouveau produit/service et processus au cours des trois dernières années et qui ont dépensé en R&D a...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.NPRD.ZS?locations=CI","methodology":"The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.\n\nSince 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"IC.FRM.CDP.ZS","name":"Entreprises qui font appel à un tiers pour résoudre des litiges commerciaux ( % des entreprises)","description":"Pourcentage d'entreprises qui recourent aux tribunaux, à l'arbitrage, à la médiation ou à la conciliation pour résoudre ou tenter de résoudre leurs...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.CDP.ZS?locations=CI","methodology":"The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.\n\nSince 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"IC.FRM.BNKS.ZS","name":"Entreprises ayant recours aux banques pour financer leurs investissements ( % des entreprises)","description":"Pourcentage d'entreprises ayant recours aux banques pour financer leurs achats d'immobilisations.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.BNKS.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.FRM.BKWC.ZS","name":"Entreprises ayant recours à la banque pour financer leur fonds de roulement ( % des entreprises)","description":"Pourcentage d'entreprises utilisant des prêts bancaires pour financer leur fonds de roulement.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.BKWC.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.FRM.METG.ZS","name":"Entreprises ayant visité des agents du fisc ou ayant demandé à rencontrer des agents du fisc ( % des entreprises)","description":"Pourcentage d'entreprises qui ont été visitées ou inspectées par des agents du fisc ou qui ont dû les rencontrer au cours de l'année écoulée.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.METG.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.FRM.LOTM.ZS","name":"Entreprises dont le principal propriétaire est également le cadre supérieur ( % des entreprises)","description":"Pourcentage d'entreprises dont le plus grand propriétaire est également le plus haut dirigeant.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.LOTM.ZS?locations=CI","methodology":"The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.\n\nSince 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"IC.FRM.BNKL.ZS","name":"Entreprises disposant d'un prêt ou d'une marge de crédit bancaire ( % des entreprises)","description":"Le pourcentage d'entreprises disposant d'une marge de crédit ou d'un prêt auprès d'une institution financière.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.BNKL.ZS?locations=CI","methodology":"The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.\n\nSince 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"IC.FRM.FO.ZS","name":"Entreprises détenues à au moins 10 % par des étrangers","description":"Le pourcentage d'entreprises dont au moins 10 % sont détenues par des particuliers, des entreprises ou des organisations étrangères.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.FO.ZS?locations=CI","methodology":"The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.\n\nSince 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"IC.FRM.FEMO.ZS","name":"Entreprises avec participation féminine ( % des entreprises)","description":"Pourcentage d'entreprises comptant des femmes parmi les propriétaires.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.FEMO.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.FRM.FEMM.ZS","name":"Entreprises dirigées par des femmes ( % des entreprises)","description":"Pourcentage d'entreprises dont les dirigeants sont des femmes.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.FEMM.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"EN.FSH.THRD.NO","name":"Espèces de poissons menacées","description":"Les espèces de poissons sont basées sur Froese, R.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.FSH.THRD.NO?locations=CI","methodology":"Methodology: Species assessed as Critically Endangered (CR), Endangered (EN) or Vulnerable (VU) are referred to as \"threatened\" species. The International Union for Conservation of Nature (IUCN) Red List of Threatened Species collects and disseminates information on the global threated species.\nProportion of threatened species is only reported for the more completely evaluated groups (i.e., >90% of species evaluated). Also, the reported percentage of threatened species for each group is presented as a best estimate within a range of possible values bounded by lower and upper estimates:\nLower estimate = % threatened extant species if all Data Deficient species are not threatened, i.e., (CR + EN + VU) / (total assessed - EX)\nBest estimate = % threatened extant species if Data Deficient species are equally threatened as data sufficient species, i.e., (CR + EN + VU) / (total assessed - EX - DD)\nUpper estimate = % threatened extant species if all Data Deficient species are threatened, i.e., (CR + EN + VU + DD) / (total assessed - EX)\nAdditional information on ecology and habitat preferences, threats, and conservation action are also collated and assessed as part of Red List process.","theme":"territory","source_group":"wb"},{"code":"IT.NET.BBND","name":"Abonnements haut débit fixe","description":"Les abonnements haut débit fixe désignent les abonnements fixes à un accès haut débit à l'Internet public (une connexion TCP/IP), à des débits desc...","source_link":"https://donnees.banquemondiale.org/indicateur/IT.NET.BBND?locations=CI","methodology":"Methodology: The data can be collected by asking all ISPs in the country to provide the number of their fixed -broadband subscriptions (by type – cable, DSL, optical fiber, other, satellite, and terrestrial fixed wireless broadband).\nStatistical concept(s): The data can be collected by asking all ISPs in the country to provide the number of their fixed -broadband subscriptions (by type – cable, DSL, optical fiber, other, satellite, and terrestrial fixed wireless broadband).","theme":"tertiary","source_group":"wb"},{"code":"IT.NET.BBND.P2","name":"Abonnements au haut débit fixe (pour 100 personnes)","description":"Les abonnements haut débit fixe désignent les abonnements fixes à un accès haut débit à l'Internet public (une connexion TCP/IP), à des débits desc...","source_link":"https://donnees.banquemondiale.org/indicateur/IT.NET.BBND.P2?locations=CI","methodology":"Methodology: Data refer to subscriptions to high-speed access to the public Internet (a TCP/IP connection), at downstream speeds equal to, or greater than, 256 kbit/s. This includes cable modem, DSL, fibre-to-the-home/building and other fixed (wired)-broadband subscriptions. This total is measured irrespective of the method of payment. It excludes subscriptions that have access to data communications (including the Internet) via mobile-cellular networks. It excludes technologies listed under the wireless-broadband category.\n\nFixed broadband Internet subscribers per 100 people is obtained by dividing the number of fixed broadband Internet subscribers by the population and then multiplying by 100. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx\nStatistical concept(s): The data can be collected by asking all ISPs in the country to provide the number of their fixed -broadband subscriptions (by type – cable, DSL, optical fiber, other, satellite, and terrestrial fixed wireless broadband). This indicator can be divided by the population and multiplied by 100 to obtain fixed-broadband subscriptions per 100 people.","theme":"tertiary","source_group":"wb"},{"code":"IT.MLT.MAIN","name":"Abonnements à la téléphonie fixe","description":"Les abonnements à la téléphonie fixe font référence à la somme du nombre actif de lignes téléphoniques fixes analogiques, des abonnements à la voix...","source_link":"https://donnees.banquemondiale.org/indicateur/IT.MLT.MAIN?locations=CI","methodology":"Methodology: A fixed telephone line (previously called main telephone line in operation) is an active line connecting the subscriber's terminal equipment to the public switched telephone network (PSTN) and which has a dedicated port in the telephone exchange equipment. This term is synonymous with the terms main station or Direct Exchange Line (DEL) that are commonly used in telecommunication documents. It may not be the same as an access line or a subscriber. This should include the active number of analog fixed telephone lines, ISDN channels, fixed wireless, public payphones and VoIP subscriptions. Active lines are those that have registered an activity in the past three months.\n\nData on fixed telephone lines are derived using administrative data that countries (usually the regulatory telecommunication authority or the Ministry in charge of telecommunications) regularly, and at least annually, collect from telecommunications operators. Data are considered to be very reliable, timely, and complete.\n\nData for this indicator are readily available for approximately 90 percent of countries, either through ITU's World Telecommunication Indicators questionnaires or from official information available on the Ministry or Regulator's website. For the rest, information can be aggregated through operators' data (mainly through annual reports) and complemented by market research reports. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx\nStatistical concept(s): Data can be collected and aggregated at the country level by asking all licensed fixed-telephone line operators how many fixed-telephone subscriptions they have.","theme":"tertiary","source_group":"wb"},{"code":"IT.MLT.MAIN.P2","name":"Abonnements à la téléphonie fixe (pour 100 personnes)","description":"Les abonnements à la téléphonie fixe font référence à la somme du nombre actif de lignes téléphoniques fixes analogiques, des abonnements à la voix...","source_link":"https://donnees.banquemondiale.org/indicateur/IT.MLT.MAIN.P2?locations=CI","methodology":"Methodology: A fixed telephone line (previously called main telephone line in operation) is an active line connecting the subscriber's terminal equipment to the public switched telephone network (PSTN) and which has a dedicated port in the telephone exchange equipment. This term is synonymous with the terms main station or Direct Exchange Line (DEL) that are commonly used in telecommunication documents. It may not be the same as an access line or a subscriber. This should include the active number of analog fixed telephone lines, ISDN channels, fixed wireless, public payphones and VoIP subscriptions. Active lines are those that have registered an activity in the past three months.\n\nData on fixed telephone lines are derived using administrative data that countries (usually the regulatory telecommunication authority or the Ministry in charge of telecommunications) regularly, and at least annually, collect from telecommunications operators. Data are considered to be very reliable, timely, and complete.\n\nData for this indicator are readily available for approximately 90 percent of countries, either through ITU's World Telecommunication Indicators questionnaires or from official information available on the Ministry or Regulator's website. For the rest, information can be aggregated through operators' data (mainly through annual reports) and complemented by market research reports.\n\nTelephone lines (per 100 people) indicator is derived by all telephone lines divided by the country's population and multiplied by 100. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx\nStatistical concept(s): Data can be collected and aggregated at the country level by asking all licensed fixed-telephone line operators how many fixed-telephone subscriptions they have. This indicator can be divided by the population and multiplied by 100 to obtain fixed telephone subscriptions per 100 people.","theme":"tertiary","source_group":"wb"},{"code":"TX.VAL.FOOD.ZS.UN","name":"Exportations de produits alimentaires ( % des exportations de marchandises)","description":"Les produits alimentaires comprennent les produits des sections 0 (aliments et animaux vivants), 1 (boissons et tabac) et 4 (huiles et graisses ani...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.FOOD.ZS.UN?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.FOOD.ZS.UN","name":"Importations de produits alimentaires ( % des importations de marchandises)","description":"Les produits alimentaires comprennent les produits des sections 0 (aliments et animaux vivants), 1 (boissons et tabac) et 4 (huiles et graisses ani...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.FOOD.ZS.UN?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"AG.PRD.FOOD.XD","name":"Indice de la production alimentaire (2014-2016 = 100)","description":"L'indice de production alimentaire couvre les cultures vivrières considérées comme comestibles et contenant des nutriments.","source_link":"https://donnees.banquemondiale.org/indicateur/AG.PRD.FOOD.XD?locations=CI","methodology":"Methodology: The agricultural production index is prepared by the Food and Agriculture Organization of the United Nations (FAO). The FAO indices of agricultural production show the relative level of the aggregate volume of agricultural production for each year in comparison with the base period 2014-2016. They are based on the sum of price-weighted quantities of different agricultural commodities produced after deductions of quantities used as seed and feed weighted in a similar manner. The resulting aggregate represents, therefore, disposable production for any use except as seed and feed. All the indices at the country, regional and world levels are calculated by the Laspeyres formula*. Production quantities of each commodity are weighted by 2014-2016 average international commodity prices and summed for each year. To obtain the index, the aggregate for a given year is divided by the average aggregate for the base period 2014-2016. Since the FAO indices are based on the concept of agriculture as a single enterprise, amounts of seed and feed are subtracted from the production data to avoid double counting, once in the production data and once with the crops or livestock produced from them. Deductions for seed (in the case of eggs, for hatching) and for livestock and poultry feed apply to both domestically produced and imported commodities. They cover only primary agricultural products destined to animal feed (e.g. maize, potatoes, milk, etc.). Processed and semi-processed feed items such as bran, oilcakes, meals and molasses have been completely excluded from the calculations at all stages. It should be noted that when calculating indices of agricultural, food and nonfood production, all intermediate primary inputs of agricultural origin are deducted. However, for indices of any other commodity group, only inputs originating from within the same group are deducted; thus, only seed is removed from the group \"crops\" and from all crop subgroups, such as cereals, oil crops, etc.; and both feed and seed originating from within the livestock sector (e.g. milk feed, hatching eggs) are removed from the group \"livestock products\". For the main two livestock subgroups, namely, meat and milk, only feed originating from the respective subgroup is removed. Indices which take into account deductions for feed and seed are referred to as ''net''. Indices calculated without any deductions for feed and seed are referred to as ''gross\". The \"international commodity prices\" are used in order to avoid the use of exchange rates for obtaining continental and world aggregates, and also to improve and facilitate international comparative analysis of productivity at the national level. These\" international prices,\" expressed in so-called \"international dollars,\" are derived using a Geary-Khamis formula** for the agricultural sector. This method assigns a single \"price\" to each commodity. For example, one metric ton of wheat has the same price regardless of the country where it was produced. The currency unit in which the prices are expressed has no influence on the indices published. The commodities covered in the computation of indices of agricultural production are all crops and livestock products originating in each country. Practically all products are covered, with the main exception of fodder crops. \n\n\n\n\n\n\n\n\n\n\n\n* A Laspeyres Index is known as a \"base-weighted\" or \"fixed-weighted\" index because the price increases are weighted by the quantities in the base period. The Consumer Price Index is an example of a Laspeyres Index. http://www.usna.edu/Users/econ/rbrady/312%20Materials/LaspeyresCalc.pdf\n\n\n\n\n\n** Geary-Khamis formula is an aggregation method in which category \"international prices\" (reflecting relative category values) and country purchasing power parities (PPPs), (depicting relative country price levels) are estimated simultaneously from a system of linear equations. http://stats.oecd.org/glossary/detail.asp?ID=5528\nStatistical concept(s):","theme":"primary","source_group":"wb"},{"code":"NV.MNF.FBTO.ZS.UN","name":"Produits alimentaires, boissons et tabac ( % de la valeur ajoutée dans l'industrie manufacturière)","description":"La fabrication d'aliments, de boissons et de tabac comprend les industries classées dans les divisions 15 et 16 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.MNF.FBTO.ZS.UN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"SM.POP.FDIP","name":"Personnes déplacées de force","description":"Les personnes déplacées de force sont représentées par la somme de (1) les réfugiés (et les personnes se trouvant dans une situation assimilable à ...","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.FDIP?locations=CI","methodology":"Methodology: Data collection on forcibly displaced people combines information on five key population groups: (1) refugees (and people in a refugee-like situation) under the mandate of the United Nations High Commissioner for Refugees (UNHCR), (2) refugees under the mandate of the United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), (3) asylum-seekers, (4) other people in need of international protection, and (5) internally displaced people (IDPs). The primary data sources include administrative records, population censuses, and household surveys, as well as operational data from humanitarian organizations such as UNHCR, UNRWA, and the Internal Displacement Monitoring Centre (IDMC). Data is reported as stock data at specific points in time, typically the end of the calendar year, providing a snapshot of forcibly displaced populations globally. Each category follows established international methodologies to ensure consistency and comparability.\n\n\n\nAt the end of 2023, the UNRWA estimates that 70 per cent of the 1.7 million IDPs in the Gaza Strip at end-2023 were Palestine refugees under its mandate. These internally displaced refugees under the mandate of UNRWA are only counted once in the forcibly displaced total (i.e. deducted once from the total amount to avoid double counting). The forcibly displaced population category provides a comprehensive and standardized picture of displacement dynamics across different contexts and regions. Statistics for the indicator are included from 2010 onwards, as at this time data on internal displacement situations became more available and more consistent.","theme":"demo","source_group":"wb"},{"code":"BN.KLT.DINV.CD","name":"Investissements directs étrangers, nets ($ US courants, BdP)","description":"L'investissement direct étranger est une catégorie d'investissement transfrontalier associée au fait qu'un résident d'une économie contrôle ou exer...","source_link":"https://donnees.banquemondiale.org/indicateur/BN.KLT.DINV.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BX.KLT.DINV.WD.GD.ZS","name":"Investissements directs étrangers, entrées nettes ( % du PIB)","description":"Les investissements directs étrangers correspondent aux entrées nettes d’investissements visant à acquérir une participation de gestion durable (10...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.KLT.DINV.WD.GD.ZS?locations=CI","methodology":"Methodology: Data on equity flows are based on balance of payments data reported by the International Monetary Fund (IMF). Foreign direct investment (FDI) data are supplemented by the World Bank staff estimates using data from the United Nations Conference on Trade and Development (UNCTAD) and official national sources.\n\nThe internationally accepted definition of FDI (from the sixth edition of the IMF's Balance of Payments Manual [2009]), includes the following components: equity investment, including investment associated with equity that gives rise to control or influence; investment in indirectly influenced or controlled enterprises; investment in fellow enterprises; debt (except selected debt); and reverse investment. The Framework for Direct Investment Relationships provides criteria for determining whether cross-border ownership results in a direct investment relationship, based on control and influence. Distinguished from other kinds of international investment, FDI is made to establish a lasting interest in or effective management control over an enterprise in another country. A lasting interest in an investment enterprise typically involves establishing warehouses, manufacturing facilities, and other permanent or long-term organizations abroad. Direct investments may take the form of greenfield investment, where the investor starts a new venture in a foreign country by constructing new operational facilities; joint venture, where the investor enters into a partnership agreement with a company abroad to establish a new enterprise; or merger and acquisition, where the investor acquires an existing enterprise abroad. The IMF suggests that investments should account for at least 10 percent of voting stock to be counted as FDI. In practice many countries set a higher threshold. Many countries fail to report reinvested earnings, and the definition of long-term loans differs among countries. BoP refers to Balance of Payments.","theme":"inter","source_group":"wb"},{"code":"BX.KLT.DINV.CD.WD","name":"Investissements directs étrangers, entrées nettes (BdP, dollar américain courant)","description":"L’investissement direct étranger fait référence aux flux de capitaux propres d’investissement direct dans l’économie déclarante.","source_link":"https://donnees.banquemondiale.org/indicateur/BX.KLT.DINV.CD.WD?locations=CI","methodology":"Methodology: Data on equity flows are based on balance of payments data reported by the International Monetary Fund (IMF). Foreign direct investment (FDI) data are supplemented by the World Bank staff estimates using data from the United Nations Conference on Trade and Development (UNCTAD) and official national sources.\n\nThe internationally accepted definition of FDI (from the sixth edition of the IMF's Balance of Payments Manual [2009]), includes the following components: equity investment, including investment associated with equity that gives rise to control or influence; investment in indirectly influenced or controlled enterprises; investment in fellow enterprises; debt (except selected debt); and reverse investment. The Framework for Direct Investment Relationships provides criteria for determining whether cross-border ownership results in a direct investment relationship, based on control and influence. Distinguished from other kinds of international investment, FDI is made to establish a lasting interest in or effective management control over an enterprise in another country. A lasting interest in an investment enterprise typically involves establishing warehouses, manufacturing facilities, and other permanent or long-term organizations abroad. Direct investments may take the form of greenfield investment, where the investor starts a new venture in a foreign country by constructing new operational facilities; joint venture, where the investor enters into a partnership agreement with a company abroad to establish a new enterprise; or merger and acquisition, where the investor acquires an existing enterprise abroad. The IMF suggests that investments should account for at least 10 percent of voting stock to be counted as FDI. In practice many countries set a higher threshold. Many countries fail to report reinvested earnings, and the definition of long-term loans differs among countries. BoP refers to Balance of Payments.","theme":"inter","source_group":"wb"},{"code":"BM.KLT.DINV.WD.GD.ZS","name":"Investissements directs étrangers, sorties nettes ( % du PIB)","description":"L’investissement direct étranger fait référence aux flux de capitaux propres d’investissement direct dans une économie.","source_link":"https://donnees.banquemondiale.org/indicateur/BM.KLT.DINV.WD.GD.ZS?locations=CI","methodology":"Methodology: Data on equity flows are based on balance of payments data reported by the International Monetary Fund (IMF). Foreign direct investment (FDI) data are supplemented by the World Bank staff estimates using data from the United Nations Conference on Trade and Development (UNCTAD) and official national sources.\n\nThe internationally accepted definition of FDI (from the sixth edition of the IMF's Balance of Payments Manual [2009]), includes the following components: equity investment, including investment associated with equity that gives rise to control or influence; investment in indirectly influenced or controlled enterprises; investment in fellow enterprises; debt (except selected debt); and reverse investment. The Framework for Direct Investment Relationships provides criteria for determining whether cross-border ownership results in a direct investment relationship, based on control and influence. Distinguished from other kinds of international investment, FDI is made to establish a lasting interest in or effective management control over an enterprise in another country. A lasting interest in an investment enterprise typically involves establishing warehouses, manufacturing facilities, and other permanent or long-term organizations abroad. Direct investments may take the form of greenfield investment, where the investor starts a new venture in a foreign country by constructing new operational facilities; joint venture, where the investor enters into a partnership agreement with a company abroad to establish a new enterprise; or merger and acquisition, where the investor acquires an existing enterprise abroad. The IMF suggests that investments should account for at least 10 percent of voting stock to be counted as FDI. In practice many countries set a higher threshold. Many countries fail to report reinvested earnings, and the definition of long-term loans differs among countries. BoP refers to Balance of Payments.","theme":"inter","source_group":"wb"},{"code":"BM.KLT.DINV.CD.WD","name":"Investissements directs étrangers, sorties nettes (BdP, $ US courants)","description":"L’investissement direct étranger fait référence aux flux de capitaux propres d’investissement direct dans une économie.","source_link":"https://donnees.banquemondiale.org/indicateur/BM.KLT.DINV.CD.WD?locations=CI","methodology":"Methodology: Data on equity flows are based on balance of payments data reported by the International Monetary Fund (IMF). Foreign direct investment (FDI) data are supplemented by the World Bank staff estimates using data from the United Nations Conference on Trade and Development (UNCTAD) and official national sources.\n\nThe internationally accepted definition of FDI (from the sixth edition of the IMF's Balance of Payments Manual [2009]), includes the following components: equity investment, including investment associated with equity that gives rise to control or influence; investment in indirectly influenced or controlled enterprises; investment in fellow enterprises; debt (except selected debt); and reverse investment. The Framework for Direct Investment Relationships provides criteria for determining whether cross-border ownership results in a direct investment relationship, based on control and influence. Distinguished from other kinds of international investment, FDI is made to establish a lasting interest in or effective management control over an enterprise in another country. A lasting interest in an investment enterprise typically involves establishing warehouses, manufacturing facilities, and other permanent or long-term organizations abroad. Direct investments may take the form of greenfield investment, where the investor starts a new venture in a foreign country by constructing new operational facilities; joint venture, where the investor enters into a partnership agreement with a company abroad to establish a new enterprise; or merger and acquisition, where the investor acquires an existing enterprise abroad. The IMF suggests that investments should account for at least 10 percent of voting stock to be counted as FDI. In practice many countries set a higher threshold. Many countries fail to report reinvested earnings, and the definition of long-term loans differs among countries. BoP refers to Balance of Payments.","theme":"inter","source_group":"wb"},{"code":"AG.LND.FRST.ZS","name":"Superficie forestière ( % de la superficie terrestre)","description":"La superficie forestière (% de la superficie terrestre) est la part de la superficie totale des terres qui se trouve sous des peuplements naturels ...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.FRST.ZS?locations=CI","methodology":"Methodology: Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should reach a minimum height of 5 meters in situ. Areas under reforestation that have not yet reached but are expected to reach a canopy cover of 10 percent and a tree height of 5 meters are included, as are temporarily unstocked areas, resulting from human intervention or natural causes, which are expected to regenerate.\nThe Food and Agriculture Organization (FAO) provides detail information on forest cover, and adjusted estimates of forest cover. The survey uses a uniform definition of forest. Although FAO provides a breakdown of forest cover between natural forest and plantation for developing countries, forest data used to derive this indictor data does not reflect that breakdown. Total land area does not include inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area. \nThe indictor is derived by dividing total area under forest of a country by country's total land area, and multiplying by 100.\nStatistical concept(s): Forest - Forests are lands of more than 0.5 hectares, with a tree canopy cover of more than 10 percent, which are not primarily under agricultural or urban land use. Forests are determined both by the presence of trees and the absence of other predominant land uses. The trees should be able to reach a minimum height of 5 meters in situ. Areas under reforestation which have yet to reach a crown density of 10 percent or tree height of 5 m are included, as are temporarily unstocked areas, resulting from human intervention or natural causes, that are expected to regenerate. The term specifically includes: forest nurseries and seed orchards that constitute an integral part of the forest; forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific scientific, historical, cultural or spiritual interest; windbreaks and shelterbelts of trees with an area of more than 0.5 ha and width of more than 20 m; plantations primarily used for forestry purposes, including rubberwood plantations and cork oak stands. The term specifically excludes trees planted primarily for agricultural production, for example in fruit plantations and agroforestry systems.","theme":"primary","source_group":"wb"},{"code":"AG.LND.FRST.K2","name":"Superficie forestière (km²)","description":"La superficie forestière est une terre située sous des peuplements naturels ou plantés d'arbres d'au moins 5 mètres in situ, qu'ils soient producti...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.FRST.K2?locations=CI","methodology":"Methodology: Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should reach a minimum height of 5 meters in situ. Areas under reforestation that have not yet reached but are expected to reach a canopy cover of 10 percent and a tree height of 5 meters are included, as are temporarily unstocked areas, resulting from human intervention or natural causes, which are expected to regenerate.\nFAO provides detail information on forest cover, and adjusted estimates of forest cover. The current survey uses a uniform definition of forest. Although FAO provides a breakdown of forest cover between natural forest and plantation for developing countries, this indictor data does not reflect that breakdown. Thus the deforestation data may underestimate the rate at which natural forest is disappearing in some countries.\nStatistical concept(s): Forest - Forests are lands of more than 0.5 hectares, with a tree canopy cover of more than 10 percent, which are not primarily under agricultural or urban land use. Forests are determined both by the presence of trees and the absence of other predominant land uses. The trees should be able to reach a minimum height of 5 meters in situ. Areas under reforestation which have yet to reach a crown density of 10 percent or tree height of 5 m are included, as are temporarily unstocked areas, resulting from human intervention or natural causes, that are expected to regenerate. The term specifically includes: forest nurseries and seed orchards that constitute an integral part of the forest; forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific scientific, historical, cultural or spiritual interest; windbreaks and shelterbelts of trees with an area of more than 0.5 ha and width of more than 20 m; plantations primarily used for forestry purposes, including rubberwood plantations and cork oak stands. The term specifically excludes trees planted primarily for agricultural production, for example in fruit plantations and agroforestry systems.","theme":"primary","source_group":"wb"},{"code":"NY.GDP.FRST.RT.ZS","name":"Rentes forestières ( % du PIB)","description":"Les rentes forestières correspondent au temps de récolte du bois rond, produit des prix régionaux et d'un taux de location régional.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.FRST.RT.ZS?locations=CI","methodology":"Methodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).","theme":"primary","source_group":"wb"},{"code":"EG.USE.COMM.FO.ZS","name":"Consommation d'énergie fossile ( % du total)","description":"Les combustibles fossiles comprennent le charbon, le pétrole, les produits pétroliers et le gaz naturel.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.USE.COMM.FO.ZS?locations=CI","methodology":"Methodology: Energy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments.\nData for combustible renewables and waste are often based on small surveys or other incomplete information and thus give only a broad impression of developments and are not strictly comparable across countries. The IEA reports include country notes that explain some of these differences. All forms of energy - primary energy and primary electricity - are converted into oil equivalents. A notional thermal efficiency of 33 percent is assumed for converting nuclear electricity into oil equivalents and 100 percent efficiency for converting hydroelectric power.","theme":"secondary","source_group":"wb"},{"code":"TX.VAL.FUEL.ZS.UN","name":"Exportations de combustibles ( % des exportations de marchandises)","description":"Les carburants comprennent les produits de la section 3 de la CTCI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.FUEL.ZS.UN?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.FUEL.ZS.UN","name":"Importations de combustibles ( % des importations de marchandises)","description":"Les carburants comprennent les produits de la section 3 de la CTCI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.FUEL.ZS.UN?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"NY.GDP.MKTP.KD","name":"PIB (en dollars constants de 2015)","description":"Le produit intérieur brut est le revenu total gagné grâce à la production de biens et de services sur un territoire économique au cours d'une pério...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.MKTP.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.MKTP.KN","name":"PIB (UCL constantes)","description":"Le produit intérieur brut est le revenu total gagné grâce à la production de biens et de services sur un territoire économique au cours d'une pério...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.MKTP.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.MKTP.CN","name":"PIB (UCL courante)","description":"Le produit intérieur brut est le revenu total gagné grâce à la production de biens et de services sur un territoire économique au cours d'une pério...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.MKTP.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.MKTP.CD","name":"PIB (en dollars américains courants)","description":"Le produit intérieur brut est le revenu total gagné grâce à la production de biens et de services sur un territoire économique au cours d'une pério...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.MKTP.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.DEFL.ZS","name":"Déflateur du PIB (l'année de base varie selon les pays)","description":"Le déflateur implicite du PIB est le rapport entre le PIB en monnaie locale courante et le PIB en monnaie locale constante.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.DEFL.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.DEFL.ZS.AD","name":"Déflateur du PIB, séries liées (l'année de référence varie selon le pays)","description":"Le déflateur implicite du PIB est le rapport entre le PIB en monnaie locale courante et le PIB en monnaie locale constante.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.DEFL.ZS.AD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.MKTP.KD.ZG","name":"PIB (croissance annuelle en %)","description":"Le produit intérieur brut est le revenu total gagné grâce à la production de biens et de services sur un territoire économique au cours d'une pério...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.MKTP.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.PCAP.KD","name":"PIB par habitant (en dollars constants de 2015)","description":"Le produit intérieur brut est le revenu total gagné grâce à la production de biens et de services sur un territoire économique au cours d'une pério...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.PCAP.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.PCAP.KN","name":"PIB par habitant (UCL constantes)","description":"Le produit intérieur brut est le revenu total gagné grâce à la production de biens et de services sur un territoire économique au cours d'une pério...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.PCAP.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.PCAP.CN","name":"PIB par habitant (UCL courante)","description":"Le produit intérieur brut est le revenu total gagné grâce à la production de biens et de services sur un territoire économique au cours d'une pério...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.PCAP.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.PCAP.CD","name":"PIB par habitant (en dollars américains courants)","description":"Le produit intérieur brut est le revenu total gagné grâce à la production de biens et de services sur un territoire économique au cours d'une pério...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.PCAP.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.PCAP.KD.ZG","name":"PIB par habitant (croissance annuelle en %)","description":"Le produit intérieur brut est le revenu total gagné grâce à la production de biens et de services sur un territoire économique au cours d'une pério...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.PCAP.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.PCAP.PP.KD","name":"PIB par habitant, PPA (en dollars internationaux constants de 2017)","description":"Cet indicateur fournit des valeurs du produit intérieur brut (PIB) exprimées en dollars internationaux constants, converties en parités de pouvoir ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.PCAP.PP.KD?locations=CI","methodology":"Methodology: The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The recent 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model. ICP estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years. For the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. \n\nNational accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\n\nStatistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency.  In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. PPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures. \n\nThe  conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.PCAP.PP.CD","name":"PIB par habitant, PPA (en dollars internationaux courants)","description":"Cet indicateur fournit des valeurs du produit intérieur brut (PIB) exprimées en dollars internationaux courants, converties en parités de pouvoir d...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.PCAP.PP.CD?locations=CI","methodology":"Methodology: The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The recent 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model. ICP estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years. For the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. \n\nNational accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\n\nStatistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency.  In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. PPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures. \n\nThe  conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"SL.GDP.PCAP.EM.KD","name":"PIB par personne occupée (en dollars PPA constants de 2017)","description":"Le PIB par personne employée correspond au produit intérieur brut (PIB) divisé par l'emploi total dans l'économie.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.GDP.PCAP.EM.KD?locations=CI","methodology":"Methodology: Estimates are based on employment, population, GDP, and PPP data obtained from International Labour Organization, United Nations Population Division, Eurostat, OECD, and World Bank. The employment rates are part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): GDP per person employed represents labor productivity—output per unit of labor input. To compare labor productivity levels across countries, GDP is converted to international dollars using purchasing power parity rates which take account of differences in relative prices between countries.","theme":"emploi","source_group":"wb"},{"code":"EG.GDP.PUSE.KO.PP.KD","name":"PIB par unité d'énergie utilisée (en dollars PPA constants de 2017 par kg d'équivalent pétrole)","description":"Le PIB par unité de consommation d’énergie est le PIB en PPA par kilogramme d’équivalent pétrole consommé en énergie.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.GDP.PUSE.KO.PP.KD?locations=CI","methodology":"Methodology: The ratio of gross domestic product (GDP) to energy use indicates energy efficiency. To produce comparable and consistent estimates of real GDP across economies relative to physical inputs to GDP - that is, units of energy use - GDP is converted to 2017 international dollars using purchasing power parity (PPP) rates. Differences in this ratio over time and across economies reflect structural changes in an economy, changes in sectoral energy efficiency, and differences in fuel mixes. Total energy use refers to the use of primary energy before transformation to other end-use fuels (such as electricity and refined petroleum products). It includes energy from combustible renewables and waste - solid biomass and animal products, gas and liquid from biomass, and industrial and municipal waste. Biomass is any plant matter used directly as fuel or converted into fuel, heat, or electricity. Energy data are compiled by the International Energy Agency (IEA). IEA data for economies that are not members of the Organisation for Economic Co-operation and Development (OECD) are based on national energy data adjusted to conform to annual questionnaires completed by OECD member governments. GDP data are from World Bank's national accounts files.","theme":"secondary","source_group":"wb"},{"code":"EG.GDP.PUSE.KO.PP","name":"PIB par unité d'énergie utilisée ($ PPA par kg d'équivalent pétrole)","description":"Le PIB par unité de consommation d’énergie est le PIB en PPA par kilogramme d’équivalent pétrole consommé en énergie.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.GDP.PUSE.KO.PP?locations=CI","methodology":"Methodology: GDP per unit of energy use, measured as PPP $ per kg of oil equivalent, is calculated by dividing the gross domestic product (PPP) by the total energy consumption, expressed in kilograms of oil equivalent.","theme":"secondary","source_group":"wb"},{"code":"NY.GDP.MKTP.PP.KD","name":"PIB, PPA (en dollars internationaux constants de 2017)","description":"Cet indicateur fournit des valeurs du produit intérieur brut (PIB) exprimées en dollars internationaux constants, converties en parités de pouvoir ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.MKTP.PP.KD?locations=CI","methodology":"Methodology: The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The recent 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model. ICP estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years. For the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. \n\nNational accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\n\nStatistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency.  In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. PPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures. \n\nThe  conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.MKTP.PP.CD","name":"PIB, PPA (en dollars internationaux courants)","description":"Cet indicateur fournit des valeurs du produit intérieur brut (PIB) exprimées en dollars internationaux courants, converties en parités de pouvoir d...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.MKTP.PP.CD?locations=CI","methodology":"Methodology: The  International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The recent 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model. ICP estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years. For the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. \n\nNational accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases. \n\nStatistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency.  In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. PPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures. \n\nThe  conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.MKTP.CN.AD","name":"PIB, séries liées (UCL courantes)","description":"Le produit intérieur brut est le revenu total gagné grâce à la production de biens et de services sur un territoire économique au cours d'une pério...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.MKTP.CN.AD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.GOVT.ZS","name":"Dépenses de consommation finale des administrations publiques (en % du PIB)","description":"Les dépenses de consommation finale sont les dépenses en biens et services effectuées par les unités institutionnelles résidentes pour la satisfact...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.GOVT.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.GOVT.KD.ZG","name":"Dépenses de consommation finale des administrations publiques (croissance annuelle en %)","description":"Les dépenses de consommation finale sont les dépenses en biens et services effectuées par les unités institutionnelles résidentes pour la satisfact...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.GOVT.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.GOVT.KD","name":"Dépenses de consommation finale des administrations publiques (en dollars constants de 2015)","description":"Les dépenses de consommation finale sont les dépenses en biens et services effectuées par les unités institutionnelles résidentes pour la satisfact...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.GOVT.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.GOVT.KN","name":"Dépenses de consommation finale des administrations publiques (UCT constantes)","description":"Les dépenses de consommation finale sont les dépenses en biens et services effectuées par les unités institutionnelles résidentes pour la satisfact...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.GOVT.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.GOVT.CN","name":"Dépenses de consommation finale des administrations publiques (UCT courantes)","description":"Les dépenses de consommation finale sont les dépenses en biens et services effectuées par les unités institutionnelles résidentes pour la satisfact...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.GOVT.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.GOVT.CD","name":"Dépenses de consommation finale des administrations publiques (en dollars courants des États-Unis)","description":"Les dépenses de consommation finale sont les dépenses en biens et services effectuées par les unités institutionnelles résidentes pour la satisfact...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.GOVT.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"SI.POV.GINI","name":"Indice de Gini","description":"L'indice de Gini mesure dans quelle mesure la répartition des revenus (ou, dans certains cas, des dépenses de consommation) entre les individus ou ...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.POV.GINI?locations=CI","methodology":"Methodology: The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.\nThe Gini index provides a convenient summary measure of the degree of inequality. Data on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption. \nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\nStatistical concept(s): The Gini index is the average of all pairwise absolute differences between individual consumption or income, normalized by twice the mean. More intuitively, the Gini index is the average share of mean consumption or income that needs to be transferred between two randomly selected individuals to achieve equality. A Gini index of 1 represents perfect inequality, in which total consumption or income goes to one individual. A Gini index of 0 indicates represents perfect equality, in which all individuals have the same level of consumption or income.","theme":"social","source_group":"wb"},{"code":"NY.GNP.MKTP.KD","name":"RNB (en dollars américains constants de 2015)","description":"Le revenu national brut est le revenu total gagné par tous les résidents d'un territoire économique au cours d'une période comptable.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.MKTP.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.MKTP.KN","name":"RNB (LCU constant)","description":"Le revenu national brut est le revenu total gagné par tous les résidents d'un territoire économique au cours d'une période comptable.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.MKTP.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.MKTP.CN","name":"RNB (LCU actuel)","description":"Le revenu national brut est le revenu total gagné par tous les résidents d'un territoire économique au cours d'une période comptable.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.MKTP.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.MKTP.CD","name":"RNB ($ US courants)","description":"Le revenu national brut est le revenu total gagné par tous les résidents d'un territoire économique au cours d'une période comptable.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.MKTP.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.MKTP.KD.ZG","name":"RNB (croissance annuelle en %)","description":"Le revenu national brut est le revenu total gagné par tous les résidents d'un territoire économique au cours d'une période comptable.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.MKTP.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.PCAP.KD","name":"RNB par habitant (en dollars constants de 2015)","description":"Le revenu national brut est le revenu total gagné par tous les résidents d'un territoire économique au cours d'une période comptable.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.PCAP.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.PCAP.KN","name":"RNB par habitant (UCM constantes)","description":"Le revenu national brut est le revenu total gagné par tous les résidents d'un territoire économique au cours d'une période comptable.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.PCAP.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.PCAP.CN","name":"RNB par habitant (UCL actuelle)","description":"Le revenu national brut est le revenu total gagné par tous les résidents d'un territoire économique au cours d'une période comptable.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.PCAP.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.PCAP.KD.ZG","name":"RNB par habitant (croissance annuelle en %)","description":"Le revenu national brut est le revenu total gagné par tous les résidents d'un territoire économique au cours d'une période comptable.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.PCAP.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.PCAP.CD","name":"RNB par habitant, méthode Atlas (en dollars américains courants)","description":"Le revenu national brut est le revenu total gagné par tous les résidents d'un territoire économique au cours d'une période comptable.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.PCAP.CD?locations=CI","methodology":"Methodology: The World Bank's official estimates of the size of economies and country classifications by income level are based on Gross National Income (GNI) per capita. For cross-national comparisons, estimates are converted from local currency units (LCU) to current U.S. dollars using the Atlas method, referring to a former World Bank publication called the Atlas of Global Development. The Atlas method smooths exchange rate fluctuations using a three-year moving average, price-adjusted conversion factor. The USD estimate of GNI per capita is derived by applying the Atlas conversion factor to estimates measured in LCU.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.PCAP.PP.KD","name":"RNB par habitant, PPA (en dollars internationaux constants de 2017)","description":"Cet indicateur fournit des valeurs du revenu national brut (RNB) par personne exprimées en dollars internationaux constants, converties en parités ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.PCAP.PP.KD?locations=CI","methodology":"Methodology: The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The recent 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model. ICP estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years. For the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. \n\nNational accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\n\nStatistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency.  In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. PPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures. \n\nThe conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.PCAP.PP.CD","name":"RNB par habitant, PPA (en dollars internationaux courants)","description":"Cet indicateur fournit des valeurs du revenu national brut (RNB) par personne exprimées en dollars internationaux courants, converties en parités d...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.PCAP.PP.CD?locations=CI","methodology":"Methodology: The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The recent 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model. ICP estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years. For the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. \n\nNational accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\nStatistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency.  In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. PPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures. \n\nThe conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.ATLS.CD","name":"RNB, méthode Atlas ($ US courants)","description":"Le revenu national brut est le revenu total gagné par tous les résidents d'un territoire économique au cours d'une période comptable.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.ATLS.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.MKTP.PP.KD","name":"RNB, PPA (en dollars internationaux constants de 2017)","description":"Cet indicateur fournit des valeurs du revenu national brut (RNB) exprimées en dollars internationaux constants, converties en parités de pouvoir d'...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.MKTP.PP.KD?locations=CI","methodology":"Methodology: The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The recent 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model. ICP estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years. For the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. \n\nNational accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\nStatistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency.  In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. PPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures. \n\nThe conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.MKTP.PP.CD","name":"RNB, PPA (en dollars internationaux courants)","description":"Cet indicateur fournit des valeurs du revenu national brut (RNB) exprimées en dollars internationaux courants, converties en parités de pouvoir d'a...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.MKTP.PP.CD?locations=CI","methodology":"Methodology: The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The recent 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model. ICP estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years. For the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. \n\nNational accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\nStatistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency.  In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. PPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures. \n\nThe conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNP.MKTP.CN.AD","name":"RNB, séries liées (UCL actuelles)","description":"Le revenu national brut est le revenu total gagné par tous les résidents d'un territoire économique au cours d'une période comptable.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNP.MKTP.CN.AD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"GC.XPN.GSRV.ZS","name":"Charges de biens et services ( % de la dépense)","description":"Les biens et services comprennent tous les paiements gouvernementaux en échange de biens et services utilisés pour la production de biens et servic...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.GSRV.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.XPN.GSRV.CN","name":"Charges de biens et services (LCU courantes)","description":"Les biens et services comprennent tous les paiements gouvernementaux en échange de biens et services utilisés pour la production de biens et servic...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.GSRV.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"BX.GSR.MRCH.CD","name":"Exportations de biens ($ US courants, BdP)","description":"Les exportations de biens se produisent lorsqu’il y a des changements dans la propriété économique des biens des résidents de l’économie déclarante...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GSR.MRCH.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BM.GSR.MRCH.CD","name":"Importations de biens ($ US courants, BdP)","description":"Les importations de biens se produisent lorsqu'il y a des changements dans la propriété économique des biens des non-résidents aux résidents de l'é...","source_link":"https://donnees.banquemondiale.org/indicateur/BM.GSR.MRCH.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"GE.EST","name":"Efficacité du gouvernement : estimation","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/GE.EST?locations=CI","methodology":"","theme":"politique","source_group":"wb"},{"code":"GE.NO.SRC","name":"Efficacité du gouvernement : nombre de sources","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/GE.NO.SRC?locations=CI","methodology":"Methodology: The WGI compile and summarize information from over 30 existing data sources that report the views and experiences of citizens, entrepreneurs, and experts in the public, private and NGO sectors from around the world, on the quality of various aspects of governance.\n\n•\tThe data sources must provide subjective perceptions of relevant dimensions of governance, as the WGI are based exclusively on this type of data.\n•\tThe sources must provide original primary data produced using a well-defined methodology.\n•\tThe data sources must cover multiple countries, so that cross-country comparisons are possible.\n•\tThe data sources must be updated regularly, ideally every year, although some WGI data sources are updated once every two or three years.\n\nThe WGI draw on four different types of source data:\n\n•\tSurveys of households and firms, including the Afrobarometer surveys, Gallup World Poll, and Global Competitiveness Report survey,\n•\tCommercial business information providers, including the Economist Intelligence Unit, S&P Global, and Political Risk Services,\n•\tNon-governmental organizations, including Global Integrity, Freedom House, Reporters Without Borders, and\n•\tPublic sector organizations, including the Country Policy and Institutional Assessments (CPIA) assessments of World Bank and regional development banks.\n\nFor the detailed list of sources, please refer to: https://www.worldbank.org/en/publication/worldwide-governance-indicators/documentation#2  \nStatistical concept(s): Number of sources indicates the number of underlying data sources on which the aggregate estimate is based.\n\nVariables from the data sources are assigned to each of these six governance dimensions.  For example, an assessment of the quality of the bureaucracy would be assigned to Government Effectiveness, a question about confidence in the police or the courts would be assigned to Rule of Law, and a question about the perceived likelihood of having to pay a bribe would be assigned to Control of Corruption.  In some cases, a single data source will have multiple questions that can be assigned to the same dimension.  In this case, the WGI use the average across all relevant questions from that data source. In addition each question from each data source is assigned to only one of the six governance dimensions, selecting the dimension that best matches the content of the question.","theme":"politique","source_group":"wb"},{"code":"GE.PER.RNK","name":"Efficacité du gouvernement : rang centile","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/GE.PER.RNK?locations=CI","methodology":"","theme":"politique","source_group":"wb"},{"code":"GE.PER.RNK.LOWER","name":"Efficacité du gouvernement : rang centile, limite inférieure de l'intervalle de confiance à 90 %","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/GE.PER.RNK.LOWER?locations=CI","methodology":"Methodology: A key feature of the WGI is that all country scores are accompanied by standard errors. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether.\n\nThe standard deviations are essential to the interpretation of the WGI.  It often is more appropriate to think of the WGI methodology as identifying a statistically likely range of values for the unobserved “true” level of governance in a country.  For example, the assumption of normality tells us that there is a 90 percent probability that the true unobserved level of governance conditional on the available data for a country is in a range given by plus or minus 1.64 standard deviations around the estimate of governance. These confidence intervals are informally referred to as the “margin of error” around the estimates of governance.\n\nThese 90 percent confidence interval are also reported in percentile rank terms (the percentile rank among all country estimates of governance, of the upper and lower bounds of the 90 percent confidence interval for each country).\nStatistical concept(s): Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank.  Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.  \n\nPercentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.","theme":"politique","source_group":"wb"},{"code":"GE.PER.RNK.UPPER","name":"Efficacité du gouvernement : rang centile, limite supérieure de l'intervalle de confiance à 90 %","description":"La bonne gouvernance est essentielle au développement.","source_link":"https://donnees.banquemondiale.org/indicateur/GE.PER.RNK.UPPER?locations=CI","methodology":"Methodology: A key feature of the WGI is that all country scores are accompanied by standard errors. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether.\n\nThe standard deviations are essential to the interpretation of the WGI.  It often is more appropriate to think of the WGI methodology as identifying a statistically likely range of values for the unobserved “true” level of governance in a country.  For example, the assumption of normality tells us that there is a 90 percent probability that the true unobserved level of governance conditional on the available data for a country is in a range given by plus or minus 1.64 standard deviations around the estimate of governance. These confidence intervals are informally referred to as the “margin of error” around the estimates of governance.\n\nThese 90 percent confidence interval are also reported in percentile rank terms (the percentile rank among all country estimates of governance, of the upper and lower bounds of the 90 percent confidence interval for each country).\nStatistical concept(s): Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. \n\nPercentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.","theme":"politique","source_group":"wb"},{"code":"GE.STD.ERR","name":"Efficacité du gouvernement : Erreur-type","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/GE.STD.ERR?locations=CI","methodology":"Methodology: The WGI are composite governance indicators based on over 30 underlying data sources. These data sources are rescaled and combined to create the six aggregate indicators using a statistical methodology known as an Unobserved Components Model (UCM). The six aggregate indicators are reported in two ways : (1) in their standard normal units, ranging from approximately -2.5 to 2.5, and (2) in percentile rank terms from 0 to 100, with higher values corresponding to better outcomes.\n\nA key feature of the WGI is that all country scores are accompanied by standard errors. These margins of error need to be taken into account when making comparisons across countries and over time. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether. \n\nPlease see more information at: https://www.worldbank.org/en/publication/worldwide-governance-indicators/documentation#1\nStatistical concept(s): Standard error indicates the precision of the estimate of governance. Larger values of the standard error indicate less precise estimates. A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.","theme":"politique","source_group":"wb"},{"code":"SE.XPD.TOTL.GD.ZS","name":"Dépenses publiques consacrées à l'éducation, total ( % du PIB)","description":"Les dépenses publiques consacrées à l'éducation (courantes, en capital et transferts) sont exprimées en pourcentage du PIB.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.XPD.TOTL.GD.ZS?locations=CI","methodology":"Methodology: Government expenditure on education, total (% of GDP) is calculated by dividing total government expenditure for all levels of education by the GDP, and multiplying by 100. Aggregate data are based on World Bank estimates.\nInformation pertaining to educational expenditures is sourced from national governments, which provide the data in response to the annual survey conducted by the UNESCO Institute for Statistics (UIS) or through the joint UNESCO-OECD-Eurostat (UOE) data collection initiative. The responses to the questionnaire regarding educational spending are typically derived from the annual financial statements issued by either the Ministry of Finance or the Ministry of Education, or from the national accounts maintained by the National Statistical Office. Additionally, data concerning GDP and overall government expenditure are accessible via the IMF’s World Economic Outlook database, which is updated annually.\nStatistical concept(s): Generally, elevated levels of the indicator suggest that a government places a high priority on educational policy. Values ranging from 4% to 6% are indicative of a country achieving the benchmark set forth by the Education 2030 Framework for Action (https://uis.unesco.org/sites/default/files/documents/education-2030-incheon-framework-for-action-implementation-of-sdg4-2016-en_2.pdf).\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nEducational expenditure encompasses spending on fundamental educational goods and services, including teaching personnel, school infrastructure, textbooks, and instructional materials, as well as on ancillary educational goods and services such as support services, general administration, and other related activities.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nFunding for education may originate from public sources, encompassing all government ministries and agencies that finance or support educational programs within the country, as well as from international and private sources, such as household contributions.","theme":"education","source_group":"wb"},{"code":"SE.XPD.TOTL.GB.ZS","name":"Dépenses publiques consacrées à l'éducation, total ( % des dépenses publiques)","description":"Les dépenses publiques générales d'éducation (courantes, en capital et transferts) sont exprimées en pourcentage des dépenses publiques totales dan...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.XPD.TOTL.GB.ZS?locations=CI","methodology":"Methodology: Expenditure on education, total (% of government expenditure) is calculated by dividing total government expenditure on education by the total government expenditure on all sectors and multiplying by 100. Aggregate data are based on World Bank estimates.\nInformation regarding educational expenditures is obtained from national governments through their responses to the annual survey on formal education conducted by the UNESCO Institute for Statistics (UIS). The data provided for this questionnaire often originates from the annual financial reports of the Ministry of Finance or the Ministry of Education, or from the national accounts compiled by the National Statistical Office. Additionally, comprehensive data on general government expenditure across all sectors are sourced from the International Monetary Fund's (IMF) World Economic Outlook database, which undergoes an annual update.\nStatistical concept(s): A greater allocation of government funds towards education reflects a significant emphasis on educational priorities in comparison to other public sector investments. It is important to consider, however, that the capacity of governments to spend varies, resulting in differing budget sizes. Additionally, demographic factors such as the age distribution within a country can influence the proportion of spending on education versus other areas like health or social security.","theme":"education","source_group":"wb"},{"code":"SE.XPD.PRIM.PC.ZS","name":"Dépenses publiques par élève, primaire ( % du PIB par habitant)","description":"Les dépenses publiques par étudiant sont les dépenses publiques moyennes (courantes, en capital et transferts) par étudiant dans un niveau d'enseig...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.XPD.PRIM.PC.ZS?locations=CI","methodology":"Methodology: General government expenditure per student in primary education is calculated by dividing total government expenditure on primary education by the number of students at primary level, expressed as a percentage of GDP per capita. Aggregate data are World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Data on GDP per capita come from the World Bank. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.XPD.SECO.PC.ZS","name":"Dépenses publiques par élève du secondaire (en % du PIB par habitant)","description":"Les dépenses publiques par étudiant sont les dépenses publiques moyennes (courantes, en capital et transferts) par étudiant dans un niveau d'enseig...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.XPD.SECO.PC.ZS?locations=CI","methodology":"Methodology: General government expenditure per student in secondary education is calculated by dividing total government expenditure on secondary education by the number of students at secondary level, expressed as a percentage of GDP per capita. Aggregate data are World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Data on GDP per capita come from the World Bank. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.XPD.TERT.PC.ZS","name":"Dépenses publiques par étudiant, enseignement supérieur ( % du PIB par habitant)","description":"Les dépenses publiques par étudiant sont les dépenses publiques moyennes (courantes, en capital et transferts) par étudiant dans un niveau d'enseig...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.XPD.TERT.PC.ZS?locations=CI","methodology":"Methodology: General government expenditure per student in tertiary education is calculated by dividing total government expenditure on tertiary education by the number of students at tertiary level, expressed as a percentage of GDP per capita. Aggregate data are World Bank estimates.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Data on GDP per capita come from the World Bank. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"GC.REV.GOTR.ZS","name":"Subventions et autres revenus ( % des revenus)","description":"Les subventions sont des transferts à recevoir par des unités gouvernementales, d'autres unités gouvernementales résidentes ou non résidentes ou d'...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.REV.GOTR.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.REV.GOTR.CN","name":"Subventions et autres revenus (LCU actuels)","description":"Les subventions sont des transferts à recevoir par des unités gouvernementales, d'autres unités gouvernementales résidentes ou non résidentes ou d'...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.REV.GOTR.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"BX.GRT.EXTA.CD.WD","name":"Dons, à l'exclusion de la coopération technique (BoP, en dollars courants des États-Unis)","description":"Les subventions sont des transferts effectués en espèces, en biens ou en services pour lesquels aucun remboursement n'est requis.","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GRT.EXTA.CD.WD?locations=CI","methodology":"Methodology: Grants are transfers in cash or in kind for which no legal debt is incurred by the recipient. For ODA reporting purposes, they also include forgiveness of non-military debt, support to non-governmental organisations, certain interest subsidies, and certain costs incurred in the implementation of aid. Grants to multilateral agencies intended to soften the terms of the latter’s lending are a direct resource outflow and should also be recorded as ODA grants. For OOF reporting purposes, grants for commercial purposes such as subsidies to national private investors, and grants to forgive military debt, are also included. Grant-like flows are assimilated to grants. They comprise a) loans for which the service payments are to be made into an account in the borrowing country and used in the borrowing country for its own benefit, and b) provision of commodities for sale in the recipient’s currency the proceeds of which are used in the recipient country for its own benefit. \n\nData are in current U.S. dollars.\n\nFor more information, please refer to the Converged Statistical Reporting Directives for the Creditor Reporting System (CRS) and the Annual DAC Questionnaire at https://one.oecd.org/document/DCD/DAC/STAT(2023)9/FINAL/en/pdf.\n\nStatistical concept(s): Grants are wholly concessional by definition. All grants are reported as flows from the sector providing the funds for development or relief purposes. For their grant equivalents to be counted as official development assistance (ODA), the loans must be concessional i.e. bear a grant element of at least:\n\n• 45 per cent in the case of bilateral loans to the official sector of least developed countries (LDCs) and other low-income countries (LICs).\n• 15 per cent in the case of bilateral loans to the official sector of lower middle-income countries (LMICs).\n• 10 per cent in the case of bilateral loans to the official sector of upper middle-income countries (UMICs), loans to multilateral institutions and loans to international non-governmental organizations (INGOs).\n\nLoans whose terms are not consistent with the IMF Debt Limits Policy and/or the World Bank’s Non-Concessional Borrowing Policy/Sustainable Development Finance Policy are not reportable as ODA.\n\nLoans committed before 2018, qualifying under the rules valid at the time (25% threshold calculated at a 10% discount rate) but not qualifying under the new rules (new concessionality thresholds calculated using the new discount rates) is reportable as ODA. Loans committed before 2018, not qualifying under the rules valid at the time but qualifying under the new rules are reportable as OOF over their life time. Future reporting on repayments of those loans are recorded as OOF too, not as ODA.","theme":"inter","source_group":"wb"},{"code":"NE.GDI.TOTL.ZS","name":"Formation brute de capital ( % du PIB)","description":"La formation brute de capital comprend les acquisitions moins les cessions d'actifs produits à des fins de formation de capital fixe, de stocks ou ...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.TOTL.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.TOTL.KD.ZG","name":"Formation brute de capital ( % de croissance annuelle)","description":"La formation brute de capital comprend les acquisitions moins les cessions d'actifs produits à des fins de formation de capital fixe, de stocks ou ...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.TOTL.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.TOTL.KD","name":"Formation brute de capital (en dollars constants de 2015)","description":"La formation brute de capital comprend les acquisitions moins les cessions d'actifs produits à des fins de formation de capital fixe, de stocks ou ...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.TOTL.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.TOTL.KN","name":"Formation brute de capital (UCT constantes)","description":"La formation brute de capital comprend les acquisitions moins les cessions d'actifs produits à des fins de formation de capital fixe, de stocks ou ...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.TOTL.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.TOTL.CN","name":"Formation brute de capital (UCL courante)","description":"La formation brute de capital comprend les acquisitions moins les cessions d'actifs produits à des fins de formation de capital fixe, de stocks ou ...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.TOTL.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.TOTL.CD","name":"Formation brute de capital (en dollars américains courants)","description":"La formation brute de capital comprend les acquisitions moins les cessions d'actifs produits à des fins de formation de capital fixe, de stocks ou ...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.TOTL.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDY.TOTL.KN","name":"Revenu intérieur brut (UCT constantes)","description":"Le revenu intérieur brut réel (RDB réel) mesure le pouvoir d'achat du revenu total généré par la production nationale.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDY.TOTL.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDS.TOTL.ZS","name":"Épargne intérieure brute (en % du PIB)","description":"L’épargne intérieure brute est calculée comme étant le PIB moins les dépenses de consommation finale (consommation totale).","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDS.TOTL.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDS.TOTL.CN","name":"Épargne intérieure brute (UCL courante)","description":"L’épargne intérieure brute est calculée comme étant le PIB moins les dépenses de consommation finale (consommation totale).","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDS.TOTL.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDS.TOTL.CD","name":"Épargne intérieure brute (en dollars américains courants)","description":"L’épargne intérieure brute est calculée comme étant le PIB moins les dépenses de consommation finale (consommation totale).","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDS.TOTL.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.FTOT.ZS","name":"Formation brute de capital fixe ( % du PIB)","description":"La formation brute de capital fixe comprend les acquisitions moins les cessions d'actifs fixes au cours de la période comptable, y compris certaine...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.FTOT.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.FTOT.KD.ZG","name":"Formation brute de capital fixe ( % de croissance annuelle)","description":"La formation brute de capital fixe comprend les acquisitions moins les cessions d'actifs fixes au cours de la période comptable, y compris certaine...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.FTOT.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.FTOT.KD","name":"Formation brute de capital fixe (en dollars constants de 2015)","description":"La formation brute de capital fixe comprend les acquisitions moins les cessions d'actifs fixes au cours de la période comptable, y compris certaine...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.FTOT.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.FTOT.KN","name":"Formation brute de capital fixe (UCT constantes)","description":"La formation brute de capital fixe comprend les acquisitions moins les cessions d'actifs fixes au cours de la période comptable, y compris certaine...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.FTOT.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.FTOT.CN","name":"Formation brute de capital fixe (UCL courante)","description":"La formation brute de capital fixe comprend les acquisitions moins les cessions d'actifs fixes au cours de la période comptable, y compris certaine...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.FTOT.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.FTOT.CD","name":"Formation brute de capital fixe (en dollars américains courants)","description":"La formation brute de capital fixe comprend les acquisitions moins les cessions d'actifs fixes au cours de la période comptable, y compris certaine...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.FTOT.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.FPRV.ZS","name":"Formation brute de capital fixe, secteur privé ( % du PIB)","description":"L'investissement privé couvre les dépenses du secteur privé (y compris les agences privées à but non lucratif) pour augmenter ses actifs fixes nati...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.FPRV.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.GDI.FPRV.CN","name":"Formation brute de capital fixe, secteur privé (UCL courante)","description":"L'investissement privé couvre les dépenses du secteur privé (y compris les agences privées à but non lucratif) pour augmenter ses actifs fixes nati...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.GDI.FPRV.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"SE.PRM.GINT.FE.ZS","name":"Taux brut d'admission en première année de l'enseignement primaire, filles ( % de la tranche d'âge concernée)","description":"Le taux brut d'admission en première année de l'enseignement primaire est le nombre de nouveaux inscrits en première année de l'enseignement primai...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.GINT.FE.ZS?locations=CI","methodology":"Methodology: Gross intake ratio in the first grade of primary education is calculated by dividing the number of new entrants (enrollments minus repeaters) in the first grade of primary education, regardless of age, by the population of the official primary entrance age and multiplying the result by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.PRM.GINT.MA.ZS","name":"Taux brut d'admission en première année de l'enseignement primaire, garçons ( % de la tranche d'âge concernée)","description":"Le taux brut d'admission en première année de l'enseignement primaire est le nombre de nouveaux inscrits en première année de l'enseignement primai...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.GINT.MA.ZS?locations=CI","methodology":"Methodology: Gross intake ratio in the first grade of primary education is calculated by dividing the number of new entrants (enrollments minus repeaters) in the first grade of primary education, regardless of age, by the population of the official primary entrance age and multiplying the result by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.PRM.GINT.ZS","name":"Taux brut d'admission en première année de l'enseignement primaire, total (en % du groupe d'âge concerné)","description":"Le taux brut d'admission en première année de l'enseignement primaire est le nombre de nouveaux inscrits en première année de l'enseignement primai...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.GINT.ZS?locations=CI","methodology":"Methodology: Gross intake ratio in the first grade of primary education is calculated by dividing the number of new entrants (enrollments minus repeaters) in the first grade of primary education, regardless of age, by the population of the official primary entrance age and multiplying the result by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"NE.DAB.TOTL.ZS","name":"Dépenses nationales brutes (en % du PIB)","description":"La dépense nationale brute est la somme des dépenses de consommation finale des ménages, des dépenses de consommation finale des administrations pu...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.DAB.TOTL.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.DAB.TOTL.KD","name":"Dépense nationale brute (en dollars constants de 2015)","description":"La dépense nationale brute est la somme des dépenses de consommation finale des ménages, des dépenses de consommation finale des administrations pu...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.DAB.TOTL.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.DAB.TOTL.KN","name":"Dépense nationale brute (UCV constantes)","description":"La dépense nationale brute est la somme des dépenses de consommation finale des ménages, des dépenses de consommation finale des administrations pu...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.DAB.TOTL.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.DAB.TOTL.CN","name":"Dépenses nationales brutes (UCL courantes)","description":"La dépense nationale brute est la somme des dépenses de consommation finale des ménages, des dépenses de consommation finale des administrations pu...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.DAB.TOTL.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.DAB.TOTL.CD","name":"Dépense nationale brute (en dollars courants des États-Unis)","description":"La dépense nationale brute est la somme des dépenses de consommation finale des ménages, des dépenses de consommation finale des administrations pu...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.DAB.TOTL.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.DAB.DEFL.ZS","name":"Déflateur de la dépense nationale brute (l'année de base varie selon les pays)","description":"La dépense nationale brute est la somme des dépenses de consommation finale des ménages, des dépenses de consommation finale des administrations pu...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.DAB.DEFL.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNS.ICTR.ZS","name":"Épargne brute ( % du PIB)","description":"L'épargne est un montant qui représente la part du revenu disponible (ajusté du\n\n\nmodification des droits à pension) qui ne sont pas consacrés à la...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNS.ICTR.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNS.ICTR.GN.ZS","name":"Épargne brute ( % du RNB)","description":"L'épargne est un montant qui représente la part du revenu disponible (ajusté du\n\n\nmodification des droits à pension) qui ne sont pas consacrés à la...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNS.ICTR.GN.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNS.ICTR.CN","name":"Epargne brute (LCU courante)","description":"L'épargne est un montant qui représente la part du revenu disponible (ajusté du\n\n\nmodification des droits à pension) qui ne sont pas consacrés à la...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNS.ICTR.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GNS.ICTR.CD","name":"Épargne brute (en dollars américains courants)","description":"L'épargne est un montant qui représente la part du revenu disponible (ajusté du\n\n\nmodification des droits à pension) qui ne sont pas consacrés à la...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GNS.ICTR.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.FCST.KD","name":"Valeur ajoutée brute (VAB) aux prix de base (en dollars constants de 2015)","description":"La valeur ajoutée brute aux prix de base reflète le prix des produits à recevoir par le producteur hors taxes à payer sur les produits et y compris...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.FCST.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.FCST.KN","name":"Valeur ajoutée brute (VAB) aux prix de base (UCM constantes)","description":"La valeur ajoutée brute aux prix de base reflète le prix des produits à recevoir par le producteur hors taxes à payer sur les produits et y compris...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.FCST.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.FCST.CN","name":"Valeur ajoutée brute (VAB) aux prix de base (UCL courante)","description":"La valeur ajoutée brute aux prix de base reflète le prix des produits à recevoir par le producteur hors taxes à payer sur les produits et y compris...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.FCST.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.FCST.CD","name":"Valeur ajoutée brute (VAB) aux prix de base (en dollars courants des États-Unis)","description":"La valeur ajoutée brute aux prix de base reflète le prix des produits à recevoir par le producteur hors taxes à payer sur les produits et y compris...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.FCST.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"TX.VAL.TECH.MF.ZS","name":"Exportations de haute technologie ( % des exportations de produits manufacturés)","description":"Les exportations de haute technologie sont des produits à forte intensité de R&D, comme dans les domaines de l'aérospatiale, des ordinateurs, des p...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.TECH.MF.ZS?locations=CI","methodology":"Methodology: The method for determining high-technology exports was developed by the Organisation for Economic Co-operation and Development in collaboration with Eurostat. It takes a \"product approach\" (rather than a \"sectoral approach\") based on R&D intensity (expenditure divided by total sales) for groups of products from Germany, Italy, Japan, the Netherlands, Sweden, and the United States.\n\nThe original high-tech products classification is based on SITC Rev. 3 and is taken from Table 4 of Annex 2 of the 1997 working paper of Thomas Hatzichronouglou, OECD. The methodology used to determine high-tech exports takes the \"product approach\" based on R&D intensity on products from Germany, Italy, Japan, the Netherlands, Sweden, and the United States.\n\nHigh Technology Products List - SITC Rev. 3:\n1 Aerospace 7921+7922+7923+7924+7925+79291+79293+(714-71489-71499)+87411\n2 Computers-office machines 75113+75131+75132+75134+(752-7529)+75997\n3 Electronics-telecommunications 76381+76383+(764-76493-76499)\n+7722+77261+77318+77625+77627+7763+7764+7768+89879\n4 Pharmacy 5413+5415+5416+5421+5422\n5 Scientific instruments 774+8711+8713+8714+8719+87211+(874-87411-8742)\n+88111+88121+88411+88419+89961+89963+89966+89967\n6 Electrical machinery 77862+77863+77864+77865+7787+77884\n7 Chemistry 52222+52223+52229+52269+525+531+57433+591\n8 Non-electrical machinery 71489+71499+71871+71877+71878+72847+7311+73131+73135\n+73142+73144+73151+73153+73161+73163+73165\n+73312+73314+73316+7359+73733+73735\n9 Armament 891","theme":"inter","source_group":"wb"},{"code":"TX.VAL.TECH.CD","name":"Exportations de haute technologie (en dollars courants EU)","description":"Les exportations de haute technologie sont des produits à forte intensité de R&D, tels que l'aérospatiale, les ordinateurs, les produits pharmaceut...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.TECH.CD?locations=CI","methodology":"Methodology: High technology products are defined according to SITC Rev.4 as the sum of the following products: Aerospace, Computers-office machines, Electronics-telecommunications, Pharmacy, Scientific instruments, Electrical machinery, Chemistry, Non-electrical machinery, Armament. The following product codes are used: Aerospace: (714 – 71489 -71499)+7921+7922+7924+7925+79291+79293+87411; Computers-office machines: 75194+75195+752+75997; Electronics-communication: 76331+7638+(764-76493-76499)+7722+77261+77318+77625+77627+7763+7764+7768+89844+89846; Pharmacy: 5413+5415+5416+5421+5422; Scientific instruments: 774+871+87211+(874-87411-8742)+88111+88121+88411+88419+(8996-89965-89969); Electrical machinery: (7786-77861-777866-77869)+7787+77884; Chemistry: 52222+52223+52229+52269+525+531+57433+591; Non-electrical machinery: 71489+71499+7187+72847+7311+73131+73135+73142+73144+73151+73153+73161+73163+73165+73312+73314+73316+7359+73733+73735; Armament: 891\nThe list can also be accessed on the Eurostat website. This list, based on the OECD definition, contains technical products of which the manufacturing involved a high intensity of R&D. The original high-tech products classification is based on SITC Rev. 3 and is taken from Table 4 of Annex 2 of the 1997 working paper of Thomas Hatzichronouglou, OECD. In September 2019 the definition in the World Development Indicators database was updated to SITC Rev.4 from SITC Rev. 3.  The data are in current U.S. dollars and are sourced from the UN's Comtrade database.\n\nNote: The definition of high technology exports in WDI was modified as of October 2024. Specifically the list of SITC Rev.4 high technology product codes now includes product code 776 in its entirety and that all data in its sub-categories is incorporated. This means that products codes 776.11, 776.12, 776.21, 776.23, 776.29 have been added to the high-tech list of products, which does not comply with OECD’s 2008 definition of high-tech.\n\nThis change was implemented to address the problem of missing data which occurs during the data conversion process from HS2022 to SITC4. This happens if a country submits export data in the HS2022 coding system and is no longer in HS2017. Specifically, the HS2022-to-SITC4 conversion table (downloaded from COMTRADE) does not break down product code 776.4+ into sub-categories, and the export data of these sub-categories has been subsumed into 776. Since there is no break down for 776.4+, extracting data from the SITC4 dataset in the COMTRADE database will yield zero value for SITC4 codes 776.4, 776.42, 776.44, 776.46, and 776.49 as defined in the OECD high-tech definition. Hence, when calculating high-tech export values using the forward method of summing up data from these five SITC4 codes will result in missing data caused by the conversion process. This can result in a significant year-on-year decline in high-tech export values for affected countries.","theme":"inter","source_group":"wb"},{"code":"SH.MED.BEDS.ZS","name":"Lits d'hôpitaux (pour 1 000 personnes)","description":"Les lits d'hôpitaux comprennent les lits d'hospitalisation disponibles dans les hôpitaux et centres de réadaptation publics, privés, généraux et sp...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.MED.BEDS.ZS?locations=CI","methodology":"Methodology: Data were compiled from the WHO Regional offices and country sources other (e.g. ministry of health, national statistical office) and modified to standardize the unit of measure of per 10 000 population by WHO.\nStatistical concept(s): Health systems - the combined arrangements of institutions and actions whose primary purpose is to promote, restore, or maintain health (World Health Organization, World Health Report 2000) - are increasingly being recognized as key to combating disease and improving the health status of populations. The World Bank's Healthy Development: Strategy for Health, Nutrition, and Population Results emphasizes the need to strengthen health systems, which are weak in many countries, in order to increase the effectiveness of programs aimed at reducing specific diseases and further reduce morbidity and mortality. To evaluate health systems, the World Health Organization (WHO) has recommended that key components - such as financing, service delivery, workforce, governance, and information - be monitored using several key indicators. The data are a subset of the key indicators. Monitoring health systems allows the effectiveness, efficiency, and equity of different health system models to be compared. Health system data also help identify weaknesses and strengths and areas that need investment, such as additional health facilities, better health information systems, or better trained human resources.\nAvailability and use of health services, such as hospital beds per 1,000 people, reflect both demand- and supply-side factors. In the absence of a consistent definition this is a crude indicator of the extent of physical, financial, and other barriers to health care.","theme":"sante","source_group":"wb"},{"code":"NE.CON.PRVT.ZS","name":"Dépenses de consommation finale des ménages et des ISBLSM (en % du PIB)","description":"Ce domaine comprend les dépenses en biens et services du secteur des ménages et des ISBLSM pour la satisfaction directe des besoins ou des désirs h...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.PRVT.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.PRVT.KD.ZG","name":"Dépenses de consommation finale des ménages et des ISBLSM (croissance annuelle en %)","description":"Ce domaine comprend les dépenses en biens et services du secteur des ménages et des ISBLSM pour la satisfaction directe des besoins ou des désirs h...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.PRVT.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.PRVT.KD","name":"Dépenses de consommation finale des ménages et des ISBLSM (en dollars constants de 2015)","description":"Ce domaine comprend les dépenses en biens et services du secteur des ménages et des ISBLSM pour la satisfaction directe des besoins ou des désirs h...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.PRVT.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.PRVT.KN","name":"Dépenses de consommation finale des ménages et des ISBLSM (UCL constantes)","description":"Ce domaine comprend les dépenses en biens et services du secteur des ménages et des ISBLSM pour la satisfaction directe des besoins ou des désirs h...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.PRVT.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.PRVT.CN","name":"Dépenses de consommation finale des ménages et des ISBLSM (UCL courantes)","description":"Ce domaine comprend les dépenses en biens et services du secteur des ménages et des ISBLSM pour la satisfaction directe des besoins ou des désirs h...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.PRVT.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.PRVT.CD","name":"Dépenses de consommation finale des ménages et des ISBLSM (en dollars américains courants)","description":"Ce domaine comprend les dépenses en biens et services du secteur des ménages et des ISBLSM pour la satisfaction directe des besoins ou des désirs h...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.PRVT.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.PRVT.PC.KD","name":"Dépenses de consommation finale par habitant des ménages et des ISBLSM (en dollars constants de 2015)","description":"Ce domaine comprend les dépenses en biens et services du secteur des ménages et des ISBLSM pour la satisfaction directe des besoins ou des désirs h...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.PRVT.PC.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.PRVT.PC.KD.ZG","name":"Dépenses de consommation finale des ménages par habitant (croissance annuelle en %)","description":"Ce domaine comprend les dépenses en biens et services du secteur des ménages et des ISBLSM pour la satisfaction directe des besoins ou des désirs h...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.PRVT.PC.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Per capita estimates are divided by the total population.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.PRVT.PP.KD","name":"Ménages et ISBLSM Dépenses de consommation finale, PPA (en dollars internationaux constants de 2017)","description":"Cet indicateur fournit des valeurs pour les dépenses de consommation finale exprimées en dollars internationaux constants, converties en parités de...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.PRVT.PP.KD?locations=CI","methodology":"Methodology: The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The recent 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model. ICP estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years. For the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. \n\nNational accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\n\nStatistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency.  In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. PPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures. \n\nThe conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.PRVT.PP.CD","name":"Ménages et ISBLSM Dépenses de consommation finale, PPA (en dollars internationaux courants)","description":"Cet indicateur fournit des valeurs pour les dépenses de consommation finale exprimées en dollars internationaux courants, converties en parités de ...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.PRVT.PP.CD?locations=CI","methodology":"Methodology: The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The recent 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model. ICP estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years. For the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. \n\nNational accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\n\nStatistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency.  In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. PPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures. \n\nThe conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NE.CON.PRVT.CN.AD","name":"Dépenses de consommation finale des ménages et des ISBLSM, séries liées (UCL courantes)","description":"Ce domaine comprend les dépenses en biens et services du secteur des ménages et des ISBLSM pour la satisfaction directe des besoins ou des désirs h...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.CON.PRVT.CN.AD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"HD.HCI.OVRL","name":"Indice de capital humain (IHM) (échelle 0-1)","description":"Le HCI calcule les contributions de la santé et de l’éducation à la productivité des travailleurs.","source_link":"https://donnees.banquemondiale.org/indicateur/HD.HCI.OVRL?locations=CI","methodology":"Methodology: The index is a summary measure of the amount of human capital that a child born today can expect to acquire by age 18, given the risks of poor health and poor education that prevail in the country where she lives. A full accounting of the HCI methodology is available on the World Bank’s Open Knowledge Repository.\n\nA signi?cant innovation is that the index measures the contribution of health and education to the productivity of individuals and countries, anchored in rigorous micro-econometric studies.\n\nRanging between 0 and 1, the index takes the value 1 only if a child born today can expect to achieve full health (de?ned as no stunting and survival up to at least age 60) and achieve her formal education potential (de?ned as 14 years of high-quality school by age 18).\n\nA country’s score is its distance to the “frontier” of complete education and full health. If it scores 0.70 in the Human Capital Index, this indicates that the future earnings potential of children born today will be 70% of what they could have been with complete education and full health.\n\nThe index can directly be linked to scenarios for the future income of countries as well as individuals. If a country has a score of 0.50, then future GDP per worker could be twice as high if the country reached the benchmark of complete education and full health.\n\nThe index is presented as a country average and includes a breakdown by gender for countries where data is available. \nStatistical concept(s): Composite Health & Education Measure","theme":"education","source_group":"wb"},{"code":"HD.HCI.OVRL.FE","name":"Indice du capital humain (IHM), femmes (échelle 0-1)","description":"Le HCI calcule les contributions de la santé et de l’éducation à la productivité des travailleurs.","source_link":"https://donnees.banquemondiale.org/indicateur/HD.HCI.OVRL.FE?locations=CI","methodology":"Methodology: The index is a summary measure of the amount of human capital that a child born today can expect to acquire by age 18, given the risks of poor health and poor education that prevail in the country where she lives. A full accounting of the HCI methodology is available on the World Bank’s Open Knowledge Repository.\n\nA signi?cant innovation is that the index measures the contribution of health and education to the productivity of individuals and countries, anchored in rigorous micro-econometric studies.\n\nRanging between 0 and 1, the index takes the value 1 only if a child born today can expect to achieve full health (de?ned as no stunting and survival up to at least age 60) and achieve her formal education potential (de?ned as 14 years of high-quality school by age 18).\n\nA country’s score is its distance to the “frontier” of complete education and full health. If it scores 0.70 in the Human Capital Index, this indicates that the future earnings potential of children born today will be 70% of what they could have been with complete education and full health.\n\nThe index can directly be linked to scenarios for the future income of countries as well as individuals. If a country has a score of 0.50, then future GDP per worker could be twice as high if the country reached the benchmark of complete education and full health.\n\nThe index is presented as a country average and includes a breakdown by gender for countries where data is available. \n\nStatistical concept(s): Composite Health & Education Measure","theme":"education","source_group":"wb"},{"code":"HD.HCI.OVRL.LB.FE","name":"Indice du capital humain (IHM), femmes, borne inférieure (échelle 0-1)","description":"La limite inférieure du HCI reflète l’incertitude dans la mesure des composants et de l’indice global.","source_link":"https://donnees.banquemondiale.org/indicateur/HD.HCI.OVRL.LB.FE?locations=CI","methodology":"Methodology: The index is a summary measure of the amount of human capital that a child born today can expect to acquire by age 18, given the risks of poor health and poor education that prevail in the country where she lives. A full accounting of the HCI methodology is available on the World Bank’s Open Knowledge Repository.\n\nA signi?cant innovation is that the index measures the contribution of health and education to the productivity of individuals and countries, anchored in rigorous micro-econometric studies.\n\nRanging between 0 and 1, the index takes the value 1 only if a child born today can expect to achieve full health (de?ned as no stunting and survival up to at least age 60) and achieve her formal education potential (de?ned as 14 years of high-quality school by age 18).\n\nA country’s score is its distance to the “frontier” of complete education and full health. If it scores 0.70 in the Human Capital Index, this indicates that the future earnings potential of children born today will be 70% of what they could have been with complete education and full health.\n\nThe index can directly be linked to scenarios for the future income of countries as well as individuals. If a country has a score of 0.50, then future GDP per worker could be twice as high if the country reached the benchmark of complete education and full health.\n\nThe index is presented as a country average and includes a breakdown by gender for countries where data is available. \n\nStatistical concept(s): Composite Health & Education Measure","theme":"education","source_group":"wb"},{"code":"HD.HCI.OVRL.UB.FE","name":"Indice du capital humain (IHM), féminin, limite supérieure (échelle 0-1)","description":"La limite supérieure du HCI reflète l’incertitude dans la mesure des composants et de l’indice global.","source_link":"https://donnees.banquemondiale.org/indicateur/HD.HCI.OVRL.UB.FE?locations=CI","methodology":"Methodology: The index is a summary measure of the amount of human capital that a child born today can expect to acquire by age 18, given the risks of poor health and poor education that prevail in the country where she lives. A full accounting of the HCI methodology is available on the World Bank’s Open Knowledge Repository.\n\nA signi?cant innovation is that the index measures the contribution of health and education to the productivity of individuals and countries, anchored in rigorous micro-econometric studies.\n\nRanging between 0 and 1, the index takes the value 1 only if a child born today can expect to achieve full health (de?ned as no stunting and survival up to at least age 60) and achieve her formal education potential (de?ned as 14 years of high-quality school by age 18).\n\nA country’s score is its distance to the “frontier” of complete education and full health. If it scores 0.70 in the Human Capital Index, this indicates that the future earnings potential of children born today will be 70% of what they could have been with complete education and full health.\n\nThe index can directly be linked to scenarios for the future income of countries as well as individuals. If a country has a score of 0.50, then future GDP per worker could be twice as high if the country reached the benchmark of complete education and full health.\n\nThe index is presented as a country average and includes a breakdown by gender for countries where data is available. \n\nStatistical concept(s): Composite Health & Education Measure","theme":"education","source_group":"wb"},{"code":"HD.HCI.OVRL.LB","name":"Indice du capital humain (IHM), borne inférieure (échelle 0-1)","description":"La limite inférieure du HCI reflète l’incertitude dans la mesure des composants et de l’indice global.","source_link":"https://donnees.banquemondiale.org/indicateur/HD.HCI.OVRL.LB?locations=CI","methodology":"Methodology: The index is a summary measure of the amount of human capital that a child born today can expect to acquire by age 18, given the risks of poor health and poor education that prevail in the country where she lives. A full accounting of the HCI methodology is available on the World Bank’s Open Knowledge Repository.\n\nA signi?cant innovation is that the index measures the contribution of health and education to the productivity of individuals and countries, anchored in rigorous micro-econometric studies.\n\nRanging between 0 and 1, the index takes the value 1 only if a child born today can expect to achieve full health (de?ned as no stunting and survival up to at least age 60) and achieve her formal education potential (de?ned as 14 years of high-quality school by age 18).\n\nA country’s score is its distance to the “frontier” of complete education and full health. If it scores 0.70 in the Human Capital Index, this indicates that the future earnings potential of children born today will be 70% of what they could have been with complete education and full health.\n\nThe index can directly be linked to scenarios for the future income of countries as well as individuals. If a country has a score of 0.50, then future GDP per worker could be twice as high if the country reached the benchmark of complete education and full health.\n\nThe index is presented as a country average and includes a breakdown by gender for countries where data is available. \n\nStatistical concept(s): Composite Health & Education Measure","theme":"education","source_group":"wb"},{"code":"HD.HCI.OVRL.MA","name":"Indice du capital humain (IHM), hommes (échelle 0-1)","description":"Le HCI calcule les contributions de la santé et de l’éducation à la productivité des travailleurs.","source_link":"https://donnees.banquemondiale.org/indicateur/HD.HCI.OVRL.MA?locations=CI","methodology":"Methodology: The index is a summary measure of the amount of human capital that a child born today can expect to acquire by age 18, given the risks of poor health and poor education that prevail in the country where she lives. A full accounting of the HCI methodology is available on the World Bank’s Open Knowledge Repository.\n\nA signi?cant innovation is that the index measures the contribution of health and education to the productivity of individuals and countries, anchored in rigorous micro-econometric studies.\n\nRanging between 0 and 1, the index takes the value 1 only if a child born today can expect to achieve full health (de?ned as no stunting and survival up to at least age 60) and achieve her formal education potential (de?ned as 14 years of high-quality school by age 18).\n\nA country’s score is its distance to the “frontier” of complete education and full health. If it scores 0.70 in the Human Capital Index, this indicates that the future earnings potential of children born today will be 70% of what they could have been with complete education and full health.\n\nThe index can directly be linked to scenarios for the future income of countries as well as individuals. If a country has a score of 0.50, then future GDP per worker could be twice as high if the country reached the benchmark of complete education and full health.\n\nThe index is presented as a country average and includes a breakdown by gender for countries where data is available. \n\nStatistical concept(s): Composite Health & Education Measure","theme":"education","source_group":"wb"},{"code":"HD.HCI.OVRL.LB.MA","name":"Indice du capital humain (IHM), masculin, borne inférieure (échelle 0-1)","description":"La limite inférieure du HCI reflète l’incertitude dans la mesure des composants et de l’indice global.","source_link":"https://donnees.banquemondiale.org/indicateur/HD.HCI.OVRL.LB.MA?locations=CI","methodology":"Methodology: The index is a summary measure of the amount of human capital that a child born today can expect to acquire by age 18, given the risks of poor health and poor education that prevail in the country where she lives. A full accounting of the HCI methodology is available on the World Bank’s Open Knowledge Repository.\n\nA signi?cant innovation is that the index measures the contribution of health and education to the productivity of individuals and countries, anchored in rigorous micro-econometric studies.\n\nRanging between 0 and 1, the index takes the value 1 only if a child born today can expect to achieve full health (de?ned as no stunting and survival up to at least age 60) and achieve her formal education potential (de?ned as 14 years of high-quality school by age 18).\n\nA country’s score is its distance to the “frontier” of complete education and full health. If it scores 0.70 in the Human Capital Index, this indicates that the future earnings potential of children born today will be 70% of what they could have been with complete education and full health.\n\nThe index can directly be linked to scenarios for the future income of countries as well as individuals. If a country has a score of 0.50, then future GDP per worker could be twice as high if the country reached the benchmark of complete education and full health.\n\nThe index is presented as a country average and includes a breakdown by gender for countries where data is available. \n\nStatistical concept(s): Composite Health & Education Measure","theme":"education","source_group":"wb"},{"code":"HD.HCI.OVRL.UB.MA","name":"Indice du capital humain (IHM), mâle, limite supérieure (échelle 0-1)","description":"La limite supérieure du HCI reflète l’incertitude dans la mesure des composants et de l’indice global.","source_link":"https://donnees.banquemondiale.org/indicateur/HD.HCI.OVRL.UB.MA?locations=CI","methodology":"Methodology: The index is a summary measure of the amount of human capital that a child born today can expect to acquire by age 18, given the risks of poor health and poor education that prevail in the country where she lives. A full accounting of the HCI methodology is available on the World Bank’s Open Knowledge Repository.\n\nA signi?cant innovation is that the index measures the contribution of health and education to the productivity of individuals and countries, anchored in rigorous micro-econometric studies.\n\nRanging between 0 and 1, the index takes the value 1 only if a child born today can expect to achieve full health (de?ned as no stunting and survival up to at least age 60) and achieve her formal education potential (de?ned as 14 years of high-quality school by age 18).\n\nA country’s score is its distance to the “frontier” of complete education and full health. If it scores 0.70 in the Human Capital Index, this indicates that the future earnings potential of children born today will be 70% of what they could have been with complete education and full health.\n\nThe index can directly be linked to scenarios for the future income of countries as well as individuals. If a country has a score of 0.50, then future GDP per worker could be twice as high if the country reached the benchmark of complete education and full health.\n\nThe index is presented as a country average and includes a breakdown by gender for countries where data is available. \n\nStatistical concept(s): Composite Health & Education Measure","theme":"education","source_group":"wb"},{"code":"HD.HCI.OVRL.UB","name":"Indice du capital humain (IHM), borne supérieure (échelle 0-1)","description":"La limite supérieure du HCI reflète l’incertitude dans la mesure des composants et de l’indice global.","source_link":"https://donnees.banquemondiale.org/indicateur/HD.HCI.OVRL.UB?locations=CI","methodology":"Methodology: The index is a summary measure of the amount of human capital that a child born today can expect to acquire by age 18, given the risks of poor health and poor education that prevail in the country where she lives. A full accounting of the HCI methodology is available on the World Bank’s Open Knowledge Repository.\nA signi?cant innovation is that the index measures the contribution of health and education to the productivity of individuals and countries, anchored in rigorous micro-econometric studies.\nRanging between 0 and 1, the index takes the value 1 only if a child born today can expect to achieve full health (de?ned as no stunting and survival up to at least age 60) and achieve her formal education potential (de?ned as 14 years of high-quality school by age 18).\nA country’s score is its distance to the “frontier” of complete education and full health. If it scores 0.70 in the Human Capital Index, this indicates that the future earnings potential of children born today will be 70% of what they could have been with complete education and full health.\nThe index can directly be linked to scenarios for the future income of countries as well as individuals. If a country has a score of 0.50, then future GDP per worker could be twice as high if the country reached the benchmark of complete education and full health.\nThe index is presented as a country average and includes a breakdown by gender for countries where data is available. \nStatistical concept(s): Composite Health & Education Measure","theme":"education","source_group":"wb"},{"code":"DT.DOD.MWBG.CD","name":"Prêts de la BIRD et crédits de l'IDA (DOD, dollars américains courants)","description":"Les prêts de la BIRD et les crédits de l'IDA sont des dettes publiques et garanties par l'État accordées par le Groupe de la Banque mondiale.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.MWBG.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"TX.VAL.ICTG.ZS.UN","name":"Exportations de biens TIC ( % des exportations totales de biens)","description":"Les exportations de biens des technologies de l’information et des communications comprennent les ordinateurs et équipements périphériques, les équ...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.ICTG.ZS.UN?locations=CI","methodology":"Methodology: Information and communication technology goods exports include computers and peripheral equipment, communication equipment, consumer electronic equipment, electronic components, and other information and technology goods (miscellaneous). Software is generally excluded, as there is a preference to record it under services (not an ICT good but an ICT product) to the extent possible. However it is hard to completely exclude embedded software from certain types of ICT goods, such as video game consoles (see for example the discussion on page 30 of the OECD guide cited below). ICT goods exports as a percentage of total goods exports is calculated for each country by dividing the value of its ICT goods exports by the total value of its goods exports. The result is then multiplied by 100 to be expressed as a percentage.\n\nICT goods are defined according to the OECD’s Guide on Measuring the Information Society 2011 for Harmonized System (HS) 2007 and adapted to HS12 by UNCTAD in collaboration with UNSD (United Nations Statistics Division). This new list consists of 93 goods defined at the 6 digit level of the 2012 version of the HS. The technical note is available online at: http://unctad.org/en/PublicationsLibrary/tn_unctad_ict4d02_en.pdf\nData were downloaded from COMTRADE according to the reported classification (HS92, 96, 02, 07, 12) and aggregated into ICT groups by UNCTAD.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.ICTG.ZS.UN","name":"Importations de biens TIC ( % des importations totales de biens)","description":"Les importations de biens liés aux technologies de l'information et de la communication comprennent les ordinateurs et les équipements périphérique...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.ICTG.ZS.UN?locations=CI","methodology":"Methodology: Information and communication technology goods imports include computers and peripheral equipment, communication equipment, consumer electronic equipment, electronic components, and other information and technology goods (miscellaneous). Software is generally excluded, as there is a preference to record it under services (not an ICT good but an ICT product) to the extent possible. However it is hard to completely exclude embedded software from certain types of ICT goods, such as video game consoles (see for example the discussion on page 30 of the OECD guide cited below). ICT goods imports as a percentage of total imports is calculated for each country by dividing the value of its ICT goods imports by the total value of its goods imports. The result is then multiplied by 100 to be expressed as a percentage.\n\nICT goods are defined according to the OECD’s Guide on Measuring the Information Society 2011 for Harmonized System (HS) 2007 and adapted to HS12 by UNCTAD in collaboration with UNSD (United Nations Statistics Division). This new list consists of 93 goods defined at the 6 digit level of the 2012 version of the HS. The technical note is available online at: http://unctad.org/en/PublicationsLibrary/tn_unctad_ict4d02_en.pdf\nData were downloaded from COMTRADE according to the reported classification (HS92, 96, 02, 07, 12) and aggregated into ICT groups by UNCTAD.","theme":"inter","source_group":"wb"},{"code":"BX.GSR.CCIS.ZS","name":"Exportations de services TIC ( % des exportations de services, BdP)","description":"Les exportations de services de technologies de l'information et des communications comprennent les services informatiques et de communication (tél...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GSR.CCIS.ZS?locations=CI","methodology":"Methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\n\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual.","theme":"inter","source_group":"wb"},{"code":"BX.GSR.CCIS.CD","name":"Exportations de services TIC (BdP, $ US courants)","description":"Les exportations de services de technologies de l'information et des communications comprennent les services informatiques et de communication (tél...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GSR.CCIS.CD?locations=CI","methodology":"Methodology: The balance of payments (BoP) is a double-entry accounting system that shows all flows of goods and services into and out of an economy; all transfers that are the counterpart of real resources or financial claims provided to or by the rest of the world without a quid pro quo, such as donations and grants; and all changes in residents' claims on and liabilities to nonresidents that arise from economic transactions. All transactions are recorded twice - once as a credit and once as a debit. In principle the net balance should be zero, but in practice the accounts often do not balance, requiring inclusion of a balancing item, net errors and omissions.\nThe concepts and definitions underlying the data are based on the sixth edition of the International Monetary Fund's (IMF) Balance of Payments Manual.","theme":"inter","source_group":"wb"},{"code":"IQ.CPA.IRAI.XQ","name":"Indice d'allocation des ressources IDA (1 = faible à 6 = élevé)","description":"La CPIA mesure dans quelle mesure le cadre politique et institutionnel d’un pays soutient la croissance durable et la réduction de la pauvreté, et ...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.CPA.IRAI.XQ?locations=CI","methodology":"Methodology: Each of the four clusters has a 25 percent weight in the overall rating. Within each cluster, all criteria receive equal weight, although components within a criterion may be weighted differently. The overall score is obtained by calculating the average score for each cluster, and then by averaging the scores of the four clusters. The CPIA can then be interpreted as representing an overall country score that considers each of the four clusters to be equally relevant even if some of the clusters contain more criteria than others.\n\nFor each of the criteria, the Bank has prepared guidance to help staff assess the country’s performance, by providing a definition of each criterion and a detailed description of each rating level. Bank staff assesses the country’s actual performance on each of the criteria and assign a rating. These scores are averaged—first to yield the cluster score, and then to determine a composite country rating as the average of the four clusters. The ratings reflect a variety of indicators, observations, and judgments based on country knowledge originated in the Bank or elsewhere, and on relevant publicly available indicators.\nStatistical concept(s): The CPIA consists of 16 criteria grouped in four equally weighted clusters: Economic Management, Structural Policies, Policies for Social Inclusion and Equity, and Public Sector Management and Institutions. For each of the 16 criteria, countries are rated on a scale of 1 to 6.  A rating of 1 corresponds to a very weak performance, and a rating of 6 to a very strong performance. Intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may also be given. \n\nThe scores depend on the level of performance each year assessed against the criteria, rather than on changes in performance compared to the previous year. The ratings depend on actual policies and performance, rather than on promises or intentions. In some cases, measures such as the passage of specific legislation can represent an important action that deserves consideration. However, the way such actions should be factored into the ratings is carefully assessed, because in the end, it is the implementation of legislation that determines the extent of its impact.","theme":"politique","source_group":"wb"},{"code":"DT.NFL.NIFC.CD","name":"IFC, privé non garanti (NFL, $ US courants)","description":"Dette à long terme non garantie placée en privé auprès de la Société Financière Internationale (IFC).","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.NIFC.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.TDS.DIMF.CD","name":"Rachats et frais du FMI (ATD, $ US courants)","description":"Les rachats du FMI correspondent au remboursement total des tirages en cours sur le Compte des ressources générales au cours de l'année spécifiée, ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.TDS.DIMF.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"SH.IMM.IDPT","name":"Vaccination, DTC ( % des enfants âgés de 12 à 23 mois)","description":"La vaccination des enfants, DTC, mesure le pourcentage d'enfants âgés de 12 à 23 mois qui ont reçu le vaccin DTC avant 12 mois ou à tout moment ava...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.IMM.IDPT?locations=CI","methodology":"Methodology: The data shown here are based on an assessment of national immunization coverage rates by the WHO and UNICEF. The assessment considered both administrative data from service providers and household survey data on children's immunization histories. Based on the data available, consideration of potential biases, and contributions of local experts, the most likely true level of immunization coverage was determined for each year. Notes on regional and global aggregates: When the vaccine is not introduced in a national immunization schedule, the missing value is assumed zero (or close to zero) in the relevant groups' averages.\nStatistical concept(s): Governments in developing countries usually finance immunization against measles and diphtheria, pertussis (whooping cough), and tetanus (DTP) as part of the basic public health package.","theme":"sante","source_group":"wb"},{"code":"SH.IMM.HEPB","name":"Vaccination, hépatite B3 ( % des enfants d'un an)","description":"Le taux de vaccination des enfants contre l'hépatite B est le pourcentage d'enfants âgés de 12 à 23 mois qui ont reçu des vaccins contre l'hépatite...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.IMM.HEPB?locations=CI","methodology":"Methodology: The data shown here are based on an assessment of national immunization coverage rates by the WHO and UNICEF. The assessment considered both administrative data from service providers and household survey data on children's immunization histories. Based on the data available, consideration of potential biases, and contributions of local experts, the most likely true level of immunization coverage was determined for each year. Notes on regional and global aggregates: When the vaccine is not introduced in a national immunization schedule, the missing value is assumed zero (or close to zero) in the relevant groups' averages.\nStatistical concept(s): Governments in developing countries usually finance immunization against measles and diphtheria, pertussis (whooping cough), and tetanus (DTP) as part of the basic public health package.","theme":"sante","source_group":"wb"},{"code":"SH.IMM.MEAS","name":"Vaccination, rougeole ( % des enfants âgés de 12 à 23 mois)","description":"La vaccination des enfants contre la rougeole mesure le pourcentage d'enfants âgés de 12 à 23 mois qui ont reçu le vaccin contre la rougeole avant ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.IMM.MEAS?locations=CI","methodology":"Methodology: The data shown here are based on an assessment of national immunization coverage rates by the WHO and UNICEF. The assessment considered both administrative data from service providers and household survey data on children's immunization histories. Based on the data available, consideration of potential biases, and contributions of local experts, the most likely true level of immunization coverage was determined for each year. Notes on regional and global aggregates: When the vaccine is not introduced in a national immunization schedule, the missing value is assumed zero (or close to zero) in the relevant groups' averages.\nStatistical concept(s): Governments in developing countries usually finance immunization against measles and diphtheria, pertussis (whooping cough), and tetanus (DTP) as part of the basic public health package.","theme":"sante","source_group":"wb"},{"code":"TM.UVI.MRCH.XD.WD","name":"Indice de la valeur unitaire des importations (2015 = 100)","description":"Les indices de valeur unitaire des importations proviennent de la base de données sur le commerce de la CNUCED.","source_link":"https://donnees.banquemondiale.org/indicateur/TM.UVI.MRCH.XD.WD?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.XD.WD","name":"Indice de la valeur des importations (2015 = 100)","description":"Les indices de valeur des importations correspondent à la valeur actuelle des importations (c.a.f.) convertie en dollars américains et exprimée en ...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.XD.WD?locations=CI","methodology":"Methodology: The Import Value Index (base year 2015 = 100) captures the movement in the total value of merchandise imports over time, using 2015 as the reference period. This index reflects changes in both the price and quantity of imported goods. An index value above 100 indicates that the total value of imports has increased compared to the base year, while a value below 100 suggests a decline. The indicator is constructed using current-dollar import values, typically sourced from customs data or trade statistics reports. \n\nImport values are aggregated across all products and trading partners. Because the index combines both price and volume effects, it does not isolate whether changes are due to rising prices, increased quantities, or both. For this reason, it is often interpreted alongside other indicators such as unit value or volume indexes.\n\nIndex values are calculated by comparing the nominal value of imports in each year to that of the base year, then scaling the result so that the base year equals 100. This normalization allows for straightforward interpretation and cross-country comparisons. The index is useful for identifying structural shifts in import demand, the impact of currency fluctuations, and the effects of trade policy. It can also be used in macroeconomic modeling to estimate import deflators or as an input for terms-of-trade calculations.","theme":"inter","source_group":"wb"},{"code":"TM.QTY.MRCH.XD.WD","name":"Indice du volume des importations (2015 = 100)","description":"Les indices de volume des importations sont dérivés des séries d'indices de volume de la CNUCED et correspondent au rapport entre les indices de va...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.QTY.MRCH.XD.WD?locations=CI","methodology":"Methodology: This indicator is constructed as the ratio of the import value index to the corresponding unit value index, both compiled by the United Nations Conference on Trade and Development (UNCTAD). The import value index reflects the nominal value of imports over time, while the unit value index serves as a proxy for import prices by capturing changes in average prices per unit. Unit value indexes are based primarily on data reported by national statistical authorities. To ensure data reliability, only values from countries that demonstrate internal consistency and meet quality thresholds defined by UNCTAD are used. Where data are incomplete or fail to meet these standards, UNCTAD supplements them with its own estimates.\n\nThe estimation procedure for unit value indexes involves applying trade values from the previous year as weights, using the Standard International Trade Classification (SITC) at the three-digit level of aggregation. This method helps to reduce distortions from shifts in trade structure or classification inconsistencies. The resulting indexes are chain-linked to ensure temporal comparability and are rebased to the year 2015 (2015 = 100). The final import volume index allows for the analysis of changes in the physical volume of imports over time, net of price effects, and is particularly useful for assessing trends in trade flows in real terms.","theme":"inter","source_group":"wb"},{"code":"NE.IMP.GNFS.ZS","name":"Importations de biens et de services (en % du PIB)","description":"Les importations de biens incluent le changement de propriété économique des biens des non-résidents aux\n\n\nrésidents de l’économie déclarante, indé...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.IMP.GNFS.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"NE.IMP.GNFS.KD.ZG","name":"Importations de biens et de services (croissance annuelle en %)","description":"Les importations de biens incluent le changement de propriété économique des biens des non-résidents aux\n\n\nrésidents de l’économie déclarante, indé...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.IMP.GNFS.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"BM.GSR.GNFS.CD","name":"Importations de biens et de services ($ US courants, BdP)","description":"Les importations de biens incluent le changement de propriété économique des biens des non-résidents aux\n\n\nrésidents de l’économie déclarante, indé...","source_link":"https://donnees.banquemondiale.org/indicateur/BM.GSR.GNFS.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"NE.IMP.GNFS.KD","name":"Importations de biens et de services (en dollars constants de 2015)","description":"Les importations de biens incluent le changement de propriété économique des biens des non-résidents aux\n\n\nrésidents de l’économie déclarante, indé...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.IMP.GNFS.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"NE.IMP.GNFS.KN","name":"Importations de biens et de services (UCT constantes)","description":"Les importations de biens incluent le changement de propriété économique des biens des non-résidents aux\n\n\nrésidents de l’économie déclarante, indé...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.IMP.GNFS.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"NE.IMP.GNFS.CN","name":"Importations de biens et de services (UCL courantes)","description":"Les importations de biens incluent le changement de propriété économique des biens des non-résidents aux\n\n\nrésidents de l’économie déclarante, indé...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.IMP.GNFS.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"NE.IMP.GNFS.CD","name":"Importations de biens et de services (en dollars américains courants)","description":"Les importations de biens incluent le changement de propriété économique des biens des non-résidents aux\n\n\nrésidents de l’économie déclarante, indé...","source_link":"https://donnees.banquemondiale.org/indicateur/NE.IMP.GNFS.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"BM.GSR.TOTL.CD","name":"Importations de biens, de services et de revenus primaires ($ US courants, BdP)","description":"Les importations de biens incluent le changement de propriété économique des biens des non-résidents aux\n\n\nrésidents de l’économie déclarante, indé...","source_link":"https://donnees.banquemondiale.org/indicateur/BM.GSR.TOTL.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"SH.HIV.INCD.YG.P3","name":"Incidence du VIH, 15-24 ans (pour 1 000 personnes non infectées âgées de 15 à 24 ans)","description":"Nombre de nouvelles infections par le VIH parmi les populations non infectées âgées de 15 à 24 ans, exprimé pour 1 000 personnes non infectées âgée...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.HIV.INCD.YG.P3?locations=CI","methodology":"Methodology: Data on incidence of HIV are from the Joint United Nations Programme on HIV/AIDS. Because of challenges in collecting direct measures of HIV incidence, modelled estimates are used (the Spectrum software). The models incorporate data on HIV prevalence from surveys of the general population, antenatal clinic attendees, and populations at increased risk of contracting HIV (such as sex workers, men who have sex with men, and people who inject drugs) and on the number of people receiving antiretroviral therapy, which will increase the prevalence of HIV because people living with HIV now survive longer. In countries with high-quality health information systems the models are also informed by case reporting and vital registration data.","theme":"sante","source_group":"wb"},{"code":"SH.HIV.INCD.ZS","name":"Incidence du VIH, 15-49 ans (pour 1 000 personnes non infectées âgées de 15 à 49 ans)","description":"Nombre de nouvelles infections par le VIH parmi les populations non infectées âgées de 15 à 49 ans, exprimé pour 1 000 habitants non infectés au co...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.HIV.INCD.ZS?locations=CI","methodology":"Methodology: Data on incidence of HIV are from the Joint United Nations Programme on HIV/AIDS. Because of challenges in collecting direct measures of HIV incidence, modelled estimates are used (the Spectrum software). The models incorporate data on HIV prevalence from surveys of the general population, antenatal clinic attendees, and populations at increased risk of contracting HIV (such as sex workers, men who have sex with men, and people who inject drugs) and on the number of people receiving antiretroviral therapy, which will increase the prevalence of HIV because people living with HIV now survive longer. In countries with high-quality health information systems the models are also informed by case reporting and vital registration data.","theme":"sante","source_group":"wb"},{"code":"SH.HIV.INCD.TL.P3","name":"Incidence du VIH, tous facteurs confondus (pour 1 000 personnes non infectées)","description":"Nombre de nouvelles infections par le VIH parmi les populations non infectées, exprimé pour 1 000 habitants non infectés au cours de l'année précéd...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.HIV.INCD.TL.P3?locations=CI","methodology":"Methodology: Data on incidence of HIV are from the Joint United Nations Programme on HIV/AIDS. Because of challenges in collecting direct measures of HIV incidence, modelled estimates are used (the Spectrum software). The models incorporate data on HIV prevalence from surveys of the general population, antenatal clinic attendees, and populations at increased risk of contracting HIV (such as sex workers, men who have sex with men, and people who inject drugs) and on the number of people receiving antiretroviral therapy, which will increase the prevalence of HIV because people living with HIV now survive longer. In countries with high-quality health information systems the models are also informed by case reporting and vital registration data.","theme":"sante","source_group":"wb"},{"code":"SH.MLR.INCD.P3","name":"Incidence du paludisme (pour 1 000 personnes à risque)","description":"L'incidence du paludisme correspond au nombre de nouveaux cas de paludisme sur une année pour 1 000 personnes à risque.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.MLR.INCD.P3?locations=CI","methodology":"Methodology: Confirmed malaria cases for countries and areas outside Africa, and for low-transmission countries and areas in Africa are adjusted for extent of health service use (treatment seeking), underreporting and lack of case confirmation (the likelihood that cases are parasite positive). In high transmission areas in which the quality of surveillance data does not permit a robust estimate from the number of reported cases, but good data on parasite prevalence is available, the number of cases can be estimated from parasite prevalence. The denominator is estimated, using official UN population and population at risk estimates for countries with sub-national endemicity.\nStatistical concept(s): Complete data on malaria cases reported through surveillance systems are the best source of data but are rarely available for large populations at high quality and accuracy. Reported data on malaria cases generally need to be adjusted for extent of health service use (treatment seeking), underreporting and lack of case confirmation (the likelihood that cases are parasite positive). WHO compiles data on reported confirmed cases of malaria and suspected cases tested with microscopy or RDT, submitted by national malaria control programmes. Underreporting is reported or estimated by countries. The extent of health service use (treatment seeking) data were obtained from nationally representative household surveys on health service use.","theme":"sante","source_group":"wb"},{"code":"SH.TBS.INCD","name":"Incidence de la tuberculose (pour 100 000 personnes)","description":"L'incidence de la tuberculose est le nombre estimé de nouveaux cas de tuberculose et de rechutes survenant au cours d'une année donnée, exprimé en ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.TBS.INCD?locations=CI","methodology":"Methodology: Estimates of TB incidence are produced through a consultative and analytical process led by WHO and are published annually. These estimates are based on annual case notifications, assessments of the quality and coverage of TB notification data, national surveys of the prevalence of TB disease and on information from death (vital) registration systems.\nStatistical concept(s): Tuberculosis is one of the main causes of adult deaths from a single infectious agent in developing countries. In developed countries tuberculosis has reemerged largely as a result of cases among immigrants. Since tuberculosis incidence cannot be directly measured, estimates are obtained by eliciting expert opinion or are derived from measurements of prevalence or mortality.","theme":"sante","source_group":"wb"},{"code":"SI.DST.04TH.20","name":"Part des revenus détenue par le quatrième 20 %","description":"La part en pourcentage du revenu ou de la consommation est la part qui revient aux sous-groupes de population indiqués par déciles ou quintiles.","source_link":"https://donnees.banquemondiale.org/indicateur/SI.DST.04TH.20?locations=CI","methodology":"Methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption. \nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\nPercentage shares by quintile may not sum to 100 because of rounding.\nStatistical concept(s): The percentage of total income in a population that is held by the fourth quintile, meaning the fourth 20% of people when ranked from lowest to highest income.","theme":"social","source_group":"wb"},{"code":"SI.DST.10TH.10","name":"Part des revenus détenue par les 10 % les plus riches","description":"La part en pourcentage du revenu ou de la consommation est la part qui revient aux sous-groupes de population indiqués par déciles ou quintiles.","source_link":"https://donnees.banquemondiale.org/indicateur/SI.DST.10TH.10?locations=CI","methodology":"Methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption. \nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\nStatistical concept(s): The percentage of total income in a population that is held by the tenth or top decile, meaning the top 10% of people when ranked from lowest to highest income.","theme":"social","source_group":"wb"},{"code":"SI.DST.05TH.20","name":"Part des revenus détenue par les 20 % les plus riches","description":"La part en pourcentage du revenu ou de la consommation est la part qui revient aux sous-groupes de population indiqués par déciles ou quintiles.","source_link":"https://donnees.banquemondiale.org/indicateur/SI.DST.05TH.20?locations=CI","methodology":"Methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption. \nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\nPercentage shares by quintile may not sum to 100 because of rounding.\nStatistical concept(s): The percentage of total income in a population that is held by the fifth or top quintile, meaning the top 20% of people when ranked from lowest to highest income.","theme":"social","source_group":"wb"},{"code":"SI.DST.FRST.10","name":"Part des revenus détenue par les 10 % les plus pauvres","description":"La part en pourcentage du revenu ou de la consommation est la part qui revient aux sous-groupes de population indiqués par déciles ou quintiles.","source_link":"https://donnees.banquemondiale.org/indicateur/SI.DST.FRST.10?locations=CI","methodology":"Methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption. No adjustment has been made for spatial differences in cost of living within countries, because the data needed for such calculations are generally unavailable. For further details on the estimation method for low- and middle-income economies, see Ravallion and Chen (1996).\nSurvey year is the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which most of the data were collected.\nStatistical concept(s): The percentage of a population whose income or consumption falls below half of the median in their country, essentially indicating the level of \"relative poverty\" within a society. It reflects the share of the population whose income or consumption is less than half of the typical standard in their society, highlighting income inequality at the lower end of the distribution.","theme":"social","source_group":"wb"},{"code":"SI.DST.FRST.20","name":"Part des revenus détenue par les 20 % les plus pauvres","description":"La part en pourcentage du revenu ou de la consommation est la part qui revient aux sous-groupes de population indiqués par déciles ou quintiles.","source_link":"https://donnees.banquemondiale.org/indicateur/SI.DST.FRST.20?locations=CI","methodology":"Methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption. \nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\nPercentage shares by quintile may not sum to 100 because of rounding.\nStatistical concept(s): The percentage of total income in a population that is held by the bottom quintile, meaning the bottom 20% of people when ranked from lowest to highest income.","theme":"social","source_group":"wb"},{"code":"SI.DST.02ND.20","name":"Part des revenus détenue par les 20 % suivants","description":"La part en pourcentage du revenu ou de la consommation est la part qui revient aux sous-groupes de population indiqués par déciles ou quintiles.","source_link":"https://donnees.banquemondiale.org/indicateur/SI.DST.02ND.20?locations=CI","methodology":"Methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption. \nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\nPercentage shares by quintile may not sum to 100 because of rounding.\nStatistical concept(s): The percentage of total income in a population that is held by the second quintile, meaning the second 20% of people when ranked from lowest to highest income.","theme":"social","source_group":"wb"},{"code":"SI.DST.03RD.20","name":"Part des revenus détenue par le tiers 20 %","description":"La part en pourcentage du revenu ou de la consommation est la part qui revient aux sous-groupes de population indiqués par déciles ou quintiles.","source_link":"https://donnees.banquemondiale.org/indicateur/SI.DST.03RD.20?locations=CI","methodology":"Methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption. \nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\nPercentage shares by quintile may not sum to 100 because of rounding.\nStatistical concept(s): The percentage of total income in a population that is held by the third quintile, meaning the third 20% of people when ranked from lowest to highest income.","theme":"social","source_group":"wb"},{"code":"IT.NET.USER.ZS","name":"Utilisateurs d'Internet ( % de la population)","description":"Les internautes sont des personnes qui ont utilisé Internet (depuis n'importe quel endroit) au cours des 3 derniers mois.","source_link":"https://donnees.banquemondiale.org/indicateur/IT.NET.USER.ZS?locations=CI","methodology":"Methodology: The Internet is a world-wide public computer network. It provides access to a number of communication services including the World Wide Web and carries email, news, entertainment and data files, irrespective of the device used (not assumed to be only via a computer - it may also be by mobile phone, PDA, games machine, digital TV etc.). Access can be via a fixed or mobile network. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx\nStatistical concept(s): The number of in-scope individuals using the Internet is calculated by aggregating the weighted responses. The proportion of individuals using the Internet is expressed as a percentage and is calculated by dividing the total number of in-scope individuals using the Internet by the total number of in-scope individuals, and then multiplying the result by 100.","theme":"tertiary","source_group":"wb"},{"code":"IT.NET.USER.FE.ZS","name":"Utilisateurs d'Internet, femmes ( % de la population féminine)","description":"Cet indicateur fait référence aux femmes qui ont utilisé Internet (de n'importe quel endroit) au cours des 3 derniers mois.","source_link":"https://donnees.banquemondiale.org/indicateur/IT.NET.USER.FE.ZS?locations=CI","methodology":"Methodology: The Internet is a world-wide public computer network. It provides access to a number of communication services including the World Wide Web and carries email, news, entertainment and data files, irrespective of the device used (not assumed to be only via a computer - it may also be by mobile phone, PDA, games machine, digital TV etc.). Access can be via a fixed or mobile network. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx","theme":"tertiary","source_group":"wb"},{"code":"IT.NET.USER.MA.ZS","name":"Utilisateurs d'Internet, hommes ( % de la population masculine)","description":"Cet indicateur fait référence aux individus de sexe masculin qui ont utilisé Internet (de n'importe quel endroit) au cours des 3 derniers mois.","source_link":"https://donnees.banquemondiale.org/indicateur/IT.NET.USER.MA.ZS?locations=CI","methodology":"Methodology: The Internet is a world-wide public computer network. It provides access to a number of communication services including the World Wide Web and carries email, news, entertainment and data files, irrespective of the device used (not assumed to be only via a computer - it may also be by mobile phone, PDA, games machine, digital TV etc.). Access can be via a fixed or mobile network. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx","theme":"tertiary","source_group":"wb"},{"code":"IP.IDS.NRCT","name":"Demandes d'enregistrement ou de dessin industriel, non-résidents, en nombre","description":"Les demandes de dessin industriel sont des demandes d'enregistrement d'un dessin industriel auprès d'un office national ou régional de la propriété...","source_link":"https://donnees.banquemondiale.org/indicateur/IP.IDS.NRCT?locations=CI","methodology":"Methodology: Information about the World Intellectual Property Organization (WIPO) data collection can be accessed on the WIPO website: https://www.wipo.int/en/web/ip-statistics/about\n\nStatistical concept(s): Industrial designs are applied to a wide variety of industrial products and handicrafts. They refer to the ornamental or aesthetic aspects of a useful article, including compositions of lines or colors or any three-dimensional forms that give a special appearance to a product or handicraft. The holder of a registered industrial design has exclusive rights against unauthorized copying or imitation of the design by third parties. Industrial design registrations are valid for a limited period. The term of protection is usually 15 years in most jurisdictions. However, differences in legislation exist, notably in China (which provides for a 10-year term from the application date).\n\nNon-resident application refers to an application filed with the IP office of or acting on behalf of a state or jurisdiction in which the first-named applicant in the application is not domiciled. \n\nDesign count: The number of designs contained in an industrial design application or registration. Under the Hague System for the International Registration of Industrial Designs, it is possible for an applicant to obtain protection for up to 100 industrial designs for products belonging to one and the same class by filing a single application. Some national or regional IP offices allow applications to contain more than one design for the same product or within the same class, while others allow only one design per application. In order to capture the differences in application and registration numbers across offices, it is useful to compare their respective application and registration design counts.","theme":"business","source_group":"wb"},{"code":"IP.IDS.RSCT","name":"Demandes de dessins et modèles industriels, résidents, en nombre","description":"Les demandes de dessin industriel sont des demandes d'enregistrement d'un dessin industriel auprès d'un office national ou régional de la propriété...","source_link":"https://donnees.banquemondiale.org/indicateur/IP.IDS.RSCT?locations=CI","methodology":"Methodology: Information about the World Intellectual Property Organization (WIPO) data collection can be accessed on the WIPO website: https://www.wipo.int/en/web/ip-statistics/about\nStatistical concept(s): Industrial designs are applied to a wide variety of industrial products and handicrafts. They refer to the ornamental or aesthetic aspects of a useful article, including compositions of lines or colors or any three-dimensional forms that give a special appearance to a product or handicraft. The holder of a registered industrial design has exclusive rights against unauthorized copying or imitation of the design by third parties. Industrial design registrations are valid for a limited period. The term of protection is usually 15 years in most jurisdictions. However, differences in legislation exist, notably in China (which provides for a 10-year term from the application date).\n\nFor statistical purposes, a resident application refers to an application filed with the IP office of, or acting for, the state or jurisdiction in which the first named applicant in the application is resident. For example, an application filed with the Japan Patent Office (JPO) by a resident of Japan is considered a resident application from the perspective of the JPO. Resident applications are sometimes referred to as “domestic applications.” A resident grant/registration is an IP right issued on the basis of a resident application.\n\nDesign count: The number of designs contained in an industrial design application or registration. Under the Hague System for the International Registration of Industrial Designs, it is possible for an applicant to obtain protection for up to 100 industrial designs for products belonging to one and the same class by filing a single application. Some national or regional IP offices allow applications to contain more than one design for the same product or within the same class, while others allow only one design per application. In order to capture the differences in application and registration numbers across offices, it is useful to compare their respective application and registration design counts.","theme":"business","source_group":"wb"},{"code":"NV.IND.TOTL.ZS","name":"Industrie, y compris la construction, valeur ajoutée ( % du PIB)","description":"L'industrie (y compris la construction) correspond aux divisions 05-43 de la CITI (Rév.4).","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.TOTL.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"NV.IND.TOTL.KD.ZG","name":"Industrie, y compris la construction, valeur ajoutée (croissance annuelle en %)","description":"L'industrie (y compris la construction) correspond aux divisions 05-43 de la CITI (Rév.4).","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.TOTL.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"NV.IND.TOTL.KD","name":"Industrie, y compris la construction, valeur ajoutée (en dollars constants de 2015)","description":"L'industrie (y compris la construction) correspond aux divisions 05-43 de la CITI (Rév.4).","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.TOTL.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"NV.IND.TOTL.KN","name":"Industrie, y compris la construction, valeur ajoutée (UCT constantes)","description":"L'industrie (y compris la construction) correspond aux divisions 05-43 de la CITI (Rév.4).","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.TOTL.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"NV.IND.TOTL.CN","name":"Industrie, y compris la construction, valeur ajoutée (LCU actuelle)","description":"L'industrie (y compris la construction) correspond aux divisions 05-43 de la CITI (Rév.4).","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.TOTL.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"NV.IND.TOTL.CD","name":"Industrie, y compris la construction, valeur ajoutée (en dollars américains courants)","description":"L'industrie (y compris la construction) correspond aux divisions 05-43 de la CITI (Rév.4).","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.TOTL.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"NV.IND.EMPL.KD","name":"Industrie, y compris la construction, valeur ajoutée par travailleur (en dollars américains constants de 2015)","description":"L'industrie (y compris la construction) correspond aux divisions 05-43 de la CITI (Rév.4).","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.EMPL.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Value added per worker is calculated by dividing value added of a sector by the number employed in the sector.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"FP.CPI.TOTL.ZG","name":"Inflation, prix à la consommation (croissance annuelle en %)","description":"L'inflation telle que mesurée par l'indice des prix à la consommation reflète la variation annuelle en pourcentage du coût pour le consommateur moy...","source_link":"https://donnees.banquemondiale.org/indicateur/FP.CPI.TOTL.ZG?locations=CI","methodology":"Methodology: Consumer Prices Indices are compiled in accordance with international standards: Consumer Price Index Manual, 2020 or 2004 version. Specific information on how countries compile their CPI statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of a consumer price index series is to measure the rate at which prices of consumption goods and services are changing from one period to another.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.DEFL.KD.ZG","name":"Inflation, déflateur du PIB (croissance annuelle en %)","description":"L'inflation, mesurée par le taux de croissance annuel du déflateur implicite du PIB, montre le taux de variation des prix dans l'économie dans son ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.DEFL.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.DEFL.KD.ZG.AD","name":"Inflation, déflateur du PIB, séries liées (croissance annuelle en %)","description":"L'inflation, mesurée par le taux de croissance annuel du déflateur implicite du PIB, montre le taux de variation des prix dans l'économie dans son ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.DEFL.KD.ZG.AD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/  Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"IC.FRM.CORR.ZS","name":"Paiements informels aux agents publics ( % des entreprises)","description":"Pourcentage d'établissements qui considèrent que des entreprises présentant des caractéristiques similaires aux leurs effectuent des paiements info...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.CORR.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"TX.VAL.INSF.ZS.WT","name":"Assurance et services financiers ( % des exportations de services commerciaux)","description":"Les services financiers recouvrent les services liés à l'intermédiation financière, à la gestion des risques financiers, à la transformation des li...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.INSF.ZS.WT?locations=CI","methodology":"Methodology: International trade in services statistics are compiled in accordance with international standards: Manual on Statistics of International Trade in Services 2010. Specific information on how countries compile their trade in service statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of international trade in services covers trade in services in the conventional sense of transactions (exports and imports) between residents and non-residents. In addition, it covers services delivered through enterprises that are locally established but foreign-controlled and cases where individuals are temporarily present abroad for the purpose of supplying a service.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.INSF.ZS.WT","name":"Assurance et services financiers ( % des importations de services commerciaux)","description":"Les services financiers recouvrent les services liés à l'intermédiation financière, à la gestion des risques financiers, à la transformation des li...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.INSF.ZS.WT?locations=CI","methodology":"Methodology: International trade in services statistics are compiled in accordance with international standards: Manual on Statistics of International Trade in Services 2010. Specific information on how countries compile their trade in service statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of international trade in services covers trade in services in the conventional sense of transactions (exports and imports) between residents and non-residents. In addition, it covers services delivered through enterprises that are locally established but foreign-controlled and cases where individuals are temporarily present abroad for the purpose of supplying a service.","theme":"inter","source_group":"wb"},{"code":"BX.GSR.INSF.ZS","name":"Assurance et services financiers (en % des exportations de services, BdP)","description":"Les services d'assurance et financiers couvrent divers types d'assurance fournis aux non-résidents par des entreprises d'assurance résidentes et vi...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GSR.INSF.ZS?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BM.GSR.INSF.ZS","name":"Assurance et services financiers ( % des importations de services, balance des charges)","description":"Les services d'assurance et financiers couvrent divers types d'assurance fournis aux non-résidents par des entreprises d'assurance résidentes et vi...","source_link":"https://donnees.banquemondiale.org/indicateur/BM.GSR.INSF.ZS?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"VC.IHR.PSRC.P5","name":"Homicides intentionnels (pour 100 000 personnes)","description":"Les homicides intentionnels sont des estimations des homicides illégaux délibérément infligés à la suite de conflits domestiques, de violences inte...","source_link":"https://donnees.banquemondiale.org/indicateur/VC.IHR.PSRC.P5?locations=CI","methodology":"Methodology: The definitions used to produce data are in line with the homicide definition used in the UNODC Homicide Statistics dataset. On the basis of these selection criteria and subject to data availability, a long and continuous time series including recent data on homicide counts and rates has been identified or created at country level. Data included in the dataset correspond to the original value provided by the source of origin, since no statistical procedure or modeling was used to change collected values or to create new or revised figures.\n\nThe intentional killing of a human being by another is the ultimate crime. Its indisputable physical consequences manifested in the form of a dead body also make it the most categorical and calculable. All existing data sources on intentional homicides, both at national and international level, stem from either criminal justice or public health systems. In the former case, data are generated by law enforcement or criminal justice authorities in the process of recording and investigating a crime event. In the latter, data are produced by health authorities certifying the cause of death of an individual.\n \nCriminal justice data were collected through UNODC regular collections of crime data from Member States, through publicly available data produced by national government sources and from data compiled by other international and regional agencies, including from Interpol, Eurostat, the Organization of American States and UNICEF. Public health data on homicides were mainly derived from databases on deaths by cause disseminated by the World Health Organization (WHO).\n\nThe inclusion of recent data was given a higher priority in the selection process than the length of the time series (number of years covered). An analysis of official reports and research literature is regularly carried out to verify homicide data used by government agencies and the scientific community.\n\nAs a result of the data collection and validation process, in many countries several homicide datasets have become available from different or multiple sources. Therefore, data series have been selected to provide the most appropriate reference counts.","theme":"politique","source_group":"wb"},{"code":"VC.IHR.PSRC.FE.P5","name":"Homicides intentionnels, femmes (pour 100 000 femmes)","description":"Les homicides intentionnels chez les femmes sont des estimations des homicides illégaux de femmes intentionnellement infligés à la suite de conflit...","source_link":"https://donnees.banquemondiale.org/indicateur/VC.IHR.PSRC.FE.P5?locations=CI","methodology":"Methodology: The definitions used to produce data are in line with the homicide definition used in the UNODC Homicide Statistics dataset. On the basis of these selection criteria and subject to data availability, a long and continuous time series including recent data on homicide counts and rates has been identified or created at country level. Data are adjusted to conform to the total number of victims of intentional homicide. The adjustment is carried out by applying the sex ratio of reported victims to the total number of victims of intentional homicide.\n\nThe intentional killing of a human being by another is the ultimate crime. Its indisputable physical consequences manifested in the form of a dead body also make it the most categorical and calculable. All existing data sources on intentional homicides, both at national and international level, stem from either criminal justice or public health systems. In the former case, data are generated by law enforcement or criminal justice authorities in the process of recording and investigating a crime event. In the latter, data are produced by health authorities certifying the cause of death of an individual.\n \nCriminal justice data were collected through UNODC regular collections of crime data from Member States, through publicly available data produced by national government sources and from data compiled by other international and regional agencies, including from Interpol, Eurostat, the Organization of American States and UNICEF. Public health data on homicides were mainly derived from databases on deaths by cause disseminated by the World Health Organization (WHO).\n\nThe inclusion of recent data was given a higher priority in the selection process than the length of the time series (number of years covered). An analysis of official reports and research literature is regularly carried out to verify homicide data used by government agencies and the scientific community.\n\nAs a result of the data collection and validation process, in many countries several homicide datasets have become available from different or multiple sources. Therefore, data series have been selected to provide the most appropriate reference counts.","theme":"politique","source_group":"wb"},{"code":"VC.IHR.PSRC.MA.P5","name":"Homicides intentionnels, hommes (pour 100 000 hommes)","description":"Les homicides intentionnels chez les hommes sont des estimations des homicides illégaux d'hommes délibérément infligés à la suite de conflits domes...","source_link":"https://donnees.banquemondiale.org/indicateur/VC.IHR.PSRC.MA.P5?locations=CI","methodology":"Methodology: The definitions used to produce data are in line with the homicide definition used in the UNODC Homicide Statistics dataset. On the basis of these selection criteria and subject to data availability, a long and continuous time series including recent data on homicide counts and rates has been identified or created at country level. Data are adjusted to conform to the total number of victims of intentional homicide. The adjustment is carried out by applying the sex ratio of reported victims to the total number of victims of intentional homicide.\n\nThe intentional killing of a human being by another is the ultimate crime. Its indisputable physical consequences manifested in the form of a dead body also make it the most categorical and calculable. All existing data sources on intentional homicides, both at national and international level, stem from either criminal justice or public health systems. In the former case, data are generated by law enforcement or criminal justice authorities in the process of recording and investigating a crime event. In the latter, data are produced by health authorities certifying the cause of death of an individual.\n \nCriminal justice data were collected through UNODC regular collections of crime data from Member States, through publicly available data produced by national government sources and from data compiled by other international and regional agencies, including from Interpol, Eurostat, the Organization of American States and UNICEF. Public health data on homicides were mainly derived from databases on deaths by cause disseminated by the World Health Organization (WHO).\n\nThe inclusion of recent data was given a higher priority in the selection process than the length of the time series (number of years covered). An analysis of official reports and research literature is regularly carried out to verify homicide data used by government agencies and the scientific community.\n\nAs a result of the data collection and validation process, in many countries several homicide datasets have become available from different or multiple sources. Therefore, data series have been selected to provide the most appropriate reference counts.","theme":"politique","source_group":"wb"},{"code":"GC.XPN.INTP.ZS","name":"Paiements d'intérêts ( % de la dépense)","description":"Les paiements d'intérêts comprennent les paiements d'intérêts sur la dette publique (y compris les obligations à long terme, les prêts à long terme...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.INTP.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.XPN.INTP.RV.ZS","name":"Paiements d'intérêts ( % du chiffre d'affaires)","description":"Les paiements d'intérêts comprennent les paiements d'intérêts sur la dette publique (y compris les obligations à long terme, les prêts à long terme...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.INTP.RV.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.XPN.INTP.CN","name":"Paiements d'intérêts (LCU actuels)","description":"Les paiements d'intérêts comprennent les paiements d'intérêts sur la dette publique (y compris les obligations à long terme, les prêts à long terme...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.INTP.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"FR.INR.LNDP","name":"Écart de taux d'intérêt (taux débiteur moins taux de dépôt, %)","description":"L'écart de taux d'intérêt est le taux d'intérêt appliqué par les banques sur les prêts aux clients du secteur privé moins le taux d'intérêt payé pa...","source_link":"https://donnees.banquemondiale.org/indicateur/FR.INR.LNDP?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"SM.POP.IDPC","name":"Personnes déplacées à l'intérieur de leur propre pays (PDI) par pays ou territoire d'asile / d'origine","description":"Les personnes déplacées internes (PDI) sont des personnes ou des groupes de personnes qui ont été forcées ou obligées de fuir ou de quitter leur do...","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.IDPC?locations=CI","methodology":"Methodology: Data collection on internally displaced people (IDPs) is based on a combination of population censuses, household surveys, administrative records, and operational data from humanitarian organizations. Population censuses provide a baseline count of IDPs, while household surveys are often used to collect more detailed and current data, particularly in situations where displacement is ongoing or rapidly changing.\n\n\n\nAdministrative records from local governments and humanitarian agencies provide additional data on the movements, living conditions, and access to services for IDP populations. \n\n\n\nThe Internal Displacement Monitoring Centre (IDMC) compiles and publishes IDP statistics from multiple sources. These include operational data produced by the Joint IDP Profiling Service (JIPS) and the International Organization for Migration (IOM), particularly in conflict-affected regions where official statistics may be less reliable or incomplete.\n\n\n\nThe methodology for collecting and reporting IDP data adheres to the International Recommendations on IDP Statistics (IRIS), developed by the Expert Group on Refugee, IDP and Statelessness Statistics (EGRISS). The IRIS framework provides a detailed structure for defining and measuring IDP populations, ensuring that data on IDPs is consistent, reliable, and comparable across different contexts and countries. The framework includes recommendations for both stock data (the number of IDPs at a given time) and flow data (movements into and out of the IDP population), providing a comprehensive understanding of internal displacement dynamics. This methodology has been applied in various contexts, such as in the Democratic Republic of the Congo and Colombia, where detailed IDP profiling has been essential for understanding the needs and vulnerabilities of displaced populations.","theme":"demo","source_group":"wb"},{"code":"VC.IDP.NWCV","name":"Personnes déplacées à l'intérieur de leur propre pays, nouveaux déplacements liés aux conflits et à la violence (nombre de cas)","description":"Les personnes déplacées internes sont définies selon les Principes directeurs de 1998 (http://www.internal-displacement.org/publications/1998/ocha-...","source_link":"https://donnees.banquemondiale.org/indicateur/VC.IDP.NWCV?locations=CI","methodology":"Methodology: Internally displaced persons are \"persons or groups of persons who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of or in order to avoid the effects of armed conflict, situations of generalized violence, violations of human rights or natural or human-made disasters, and who have not crossed an internationally recognized state border.\" Internally displaced people are often confused with refugees. Unlike refugees, internally displaced people remain under the protection of their own government, even if their reason for fleeing was similar to that of refugees. Refugees are people who have crossed an international border to find sanctuary and have been granted refugee or refugee-like status or temporary protection. For more information on methodology, please refer to the information published by IDMC: http://www.internal-displacement.org/database/","theme":"politique","source_group":"wb"},{"code":"VC.IDP.NWDS","name":"Personnes déplacées à l'intérieur de leur propre pays, nouveaux déplacements associés aux catastrophes (nombre de cas)","description":"Les personnes déplacées internes sont définies selon les Principes directeurs de 1998 (http://www.internal-displacement.org/publications/1998/ocha-...","source_link":"https://donnees.banquemondiale.org/indicateur/VC.IDP.NWDS?locations=CI","methodology":"Methodology: Internally displaced persons are \"persons or groups of persons who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of or in order to avoid the effects of armed conflict, situations of generalized violence, violations of human rights or natural or human-made disasters, and who have not crossed an internationally recognized state border.\" Internally displaced people are often confused with refugees. Unlike refugees, internally displaced people remain under the protection of their own government, even if their reason for fleeing was similar to that of refugees. Refugees are people who have crossed an international border to find sanctuary and have been granted refugee or refugee-like status or temporary protection.","theme":"politique","source_group":"wb"},{"code":"SM.POP.TOTL.ZS","name":"Stock de migrants internationaux ( % de la population)","description":"Le stock de migrants internationaux correspond au nombre de personnes nées dans un pays autre que celui dans lequel elles vivent.","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.TOTL.ZS?locations=CI","methodology":"Methodology: The basic data to estimate the international migrant stock were obtained mostly from population censuses held during the decennial rounds of censuses. Some of the data used were obtained from population registers and nationally representative surveys.\n\nIn the majority of cases, the sources available had gathered information on the place of birth of the enumerated population, thus allowing for the identification of the foreign-born population. In estimating the international migrant stock, international migrants have been equated with the foreign-born whenever possible. In most countries lacking data on place of birth, information on the country of citizenship of those enumerated was available and was used as the basis for the identification of international migrants, thus effectively equating international migrants with foreign citizens.\n\nAmong the 230 countries or areas that constituted the world in 2008, 91 percent had at least one data source on the international migrant stock, and of those 78 percent used the number of foreign-born persons as the basis for estimation. For about 18 percent of the countries, the number of international migrants was based on data regarding foreign citizens. There were nine countries with no information including China, the Democratic People's Republic of Korea, Eritrea and Somalia.\n\nFor countries having information on the international migrant stock for at least two points in time, interpolation or extrapolation using an exponential growth rate was used to estimate the international migrant stock on 1 July of the reference years. In some instances, the estimates were adjusted on the basis of other relevant information, including the size of the total population in the country, to ensure that the proportion of migrants in small populations did not increase to unacceptable levels.\n\nFor all other countries with only one data source, estimates for the reference years were derived by assuming growth rates of the migrant stock in the years preceding or following the only data source available. For the nine countries or areas for which no information was available on the international migrant stock, a model, based on the general observation that the proportion of international migrants tends to be inversely related to the size of the total population, was used.\n\nAfter the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union.","theme":"demo","source_group":"wb"},{"code":"SM.POP.TOTL","name":"Stock de migrants internationaux, total","description":"Le stock de migrants internationaux correspond au nombre de personnes nées dans un pays autre que celui dans lequel elles vivent.","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.TOTL?locations=CI","methodology":"Methodology: The basic data to estimate the international migrant stock were obtained mostly from population censuses held during the decennial rounds of censuses. Some of the data used were obtained from population registers and nationally representative surveys.\n\nIn the majority of cases, the sources available had gathered information on the place of birth of the enumerated population, thus allowing for the identification of the foreign-born population. In estimating the international migrant stock, international migrants have been equated with the foreign-born whenever possible. In most countries lacking data on place of birth, information on the country of citizenship of those enumerated was available and was used as the basis for the identification of international migrants, thus effectively equating international migrants with foreign citizens.\n\nAmong the 230 countries or areas that constituted the world in 2008, 91 percent had at least one data source on the international migrant stock, and of those 78 percent used the number of foreign-born persons as the basis for estimation. For about 18 percent of the countries, the number of international migrants was based on data regarding foreign citizens. There were nine countries with no information including China, the Democratic People's Republic of Korea, Eritrea and Somalia.\n\nFor countries having information on the international migrant stock for at least two points in time, interpolation or extrapolation using an exponential growth rate was used to estimate the international migrant stock on 1 July of the reference years. In some instances, the estimates were adjusted on the basis of other relevant information, including the size of the total population in the country, to ensure that the proportion of migrants in small populations did not increase to unacceptable levels.\n\nFor all other countries with only one data source, estimates for the reference years were derived by assuming growth rates of the migrant stock in the years preceding or following the only data source available. For the nine countries or areas for which no information was available on the international migrant stock, a model, based on the general observation that the proportion of international migrants tends to be inversely related to the size of the total population, was used.\n\nAfter the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union.","theme":"demo","source_group":"wb"},{"code":"ST.INT.XPND.MP.ZS","name":"Tourisme international, dépenses ( % des importations totales)","description":"Les dépenses du tourisme international sont les dépenses des visiteurs internationaux sortant dans d'autres pays, y compris les paiements aux trans...","source_link":"https://donnees.banquemondiale.org/indicateur/ST.INT.XPND.MP.ZS?locations=CI","methodology":"Methodology: Outbound tourism expenditures may include those by residents traveling abroad as same-day visitors, except when these are important enough to justify separate classification. For some countries they do not include expenditures for passenger transport items. Their share in imports is calculated as a ratio to imports of goods and services (all transactions between residents of a country and the rest of the world involving a change of ownership from nonresidents to residents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services).\n\nInternational tourism expenditures' share in imports is calculated as a ratio to imports of goods and services, which comprise all transactions between residents of a country and the rest of the world involving a change of ownership from nonresidents to residents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services.\n\nStatistical information on tourism is based mainly on data on arrivals and overnight stays along with balance of payments information. These data do not completely capture the economic phenomenon of tourism or provide the information needed for effective public policies and efficient business operations. Data are needed on the scale and significance of tourism. Information on the role of tourism in national economies is particularly deficient. Although the World Tourism Organization reports progress in harmonizing definitions and measurement, differences in national practices still prevent full comparability.\n\nThe World Tourism Organization is improving its coverage of tourism expenditure data, using balance of payments data from the International Monetary Fund (IMF) supplemented by data from individual countries. These data include travel and passenger transport items as defined in the IMF's Balance of Payments. When the IMF does not report data on passenger transport items, expenditure data for travel items are shown.\n\nThe aggregates are calculated using the World Bank's weighted aggregation methodology and differ from the World Tourism Organization's aggregates.","theme":"tertiary","source_group":"wb"},{"code":"ST.INT.XPND.CD","name":"Tourisme international, dépenses (en dollars américains courants)","description":"Les dépenses du tourisme international sont les dépenses des visiteurs internationaux sortant dans d'autres pays, y compris les paiements aux trans...","source_link":"https://donnees.banquemondiale.org/indicateur/ST.INT.XPND.CD?locations=CI","methodology":"Methodology: Outbound tourism expenditures may include those by residents traveling abroad as same-day visitors, except when these are important enough to justify separate classification. For some countries they do not include expenditures for passenger transport items. Their share in imports is calculated as a ratio to imports of goods and services (all transactions between residents of a country and the rest of the world involving a change of ownership from nonresidents to residents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services).\n\nStatistical information on tourism is based mainly on data on arrivals and overnight stays along with balance of payments information. These data do not completely capture the economic phenomenon of tourism or provide the information needed for effective public policies and efficient business operations. Data are needed on the scale and significance of tourism. Information on the role of tourism in national economies is particularly deficient. Although the World Tourism Organization reports progress in harmonizing definitions and measurement, differences in national practices still prevent full comparability.\n\nThe World Tourism Organization is improving its coverage of tourism expenditure data, using balance of payments data from the International Monetary Fund (IMF) supplemented by data from individual countries. These data include travel and passenger transport items as defined in the IMF's Balance of Payments. When the IMF does not report data on passenger transport items, expenditure data for travel items are shown.\n\nThe aggregates are calculated using the World Bank's weighted aggregation methodology and differ from the World Tourism Organization's aggregates.","theme":"tertiary","source_group":"wb"},{"code":"ST.INT.TRNX.CD","name":"Tourisme international, dépenses pour le transport de passagers (en dollars américains courants)","description":"Les dépenses du tourisme international pour les postes de transport de passagers sont les dépenses des visiteurs internationaux sortants dans d'aut...","source_link":"https://donnees.banquemondiale.org/indicateur/ST.INT.TRNX.CD?locations=CI","methodology":"Methodology: Tourism data is compiled based on the International Recommendations for Tourism Statistics (IRTS 2008). The World Tourism Organization enhances its coverage of tourism expenditure data by using balance of payments data from the International Monetary Fund (IMF) supplemented by data from individual countries. When data on passenger transport items is unavailable, expenditure data for travel items are shown.","theme":"tertiary","source_group":"wb"},{"code":"ST.INT.TVLX.CD","name":"Tourisme international, dépenses pour les articles de voyage (en dollars américains courants)","description":"Les dépenses du tourisme international sont les dépenses des visiteurs internationaux sortant dans d’autres pays.","source_link":"https://donnees.banquemondiale.org/indicateur/ST.INT.TVLX.CD?locations=CI","methodology":"Methodology: Tourism data is compiled based on the International Recommendations for Tourism Statistics (IRTS 2008). The World Tourism Organization enhances its coverage of tourism expenditure data by using balance of payments data from the International Monetary Fund (IMF) supplemented by data from individual countries. When data on passenger transport items is unavailable, expenditure data for travel items are shown.","theme":"tertiary","source_group":"wb"},{"code":"ST.INT.ARVL","name":"Tourisme international, nombre d'arrivées","description":"Les touristes internationaux entrants (visiteurs d'une nuit) sont le nombre de touristes qui voyagent dans un pays autre que celui dans lequel ils ...","source_link":"https://donnees.banquemondiale.org/indicateur/ST.INT.ARVL?locations=CI","methodology":"Methodology: Statistical information on tourism is based mainly on data on arrivals and overnight stays along with balance of payments information. These data do not completely capture the economic phenomenon of tourism or provide the information needed for effective public policies and efficient business operations. Data are needed on the scale and significance of tourism. Information on the role of tourism in national economies is particularly deficient. Although the World Tourism Organization reports progress in harmonizing definitions and measurement, differences in national practices still prevent full comparability.\n\nArrivals data measure the flows of international visitors to the country of reference: each arrival corresponds to one in inbound tourism trip. If a person visits several countries during the course of a single trip, his/her arrival in each country is recorded separately. In an accounting period, arrivals are not necessarily equal to the number of persons travelling (when a person visits the same country several times a year, each trip by the same person is counted as a separate arrival).\n\nArrivals data should correspond to inbound visitors by including both tourists and same-day non-resident visitors. All other types of travelers (such as border, seasonal and other short-term workers, long-term students and others) should be excluded as they do not qualify as visitors.\n\nData are obtained from different sources: administrative records (immigration, traffic counts, and other possible types of controls), border surveys or a mix of them. If data are obtained from accommodation surveys, the number of guests is used as estimate of arrival figures; consequently, in this case, breakdowns by regions, main purpose of the trip, modes of transport used or forms of organization of the trip are based on complementary visitor surveys.","theme":"tertiary","source_group":"wb"},{"code":"ST.INT.DPRT","name":"Tourisme international, nombre de départs","description":"Les touristes internationaux à l'étranger correspondent au nombre de départs que des personnes effectuent de leur pays de résidence habituelle vers...","source_link":"https://donnees.banquemondiale.org/indicateur/ST.INT.DPRT?locations=CI","methodology":"Methodology: Statistical information on tourism is based mainly on data on arrivals and overnight stays along with balance of payments information. These data do not completely capture the economic phenomenon of tourism or provide the information needed for effective public policies and efficient business operations. Data are needed on the scale and significance of tourism. Information on the role of tourism in national economies is particularly deficient. Although the World Tourism Organization reports progress in harmonizing definitions and measurement, differences in national practices still prevent full comparability.\n\nDepartures data measure the flows of resident visitors leaving the country of reference. Departures are not necessarily equal to the number of arrivals reported by international destinations for the country of reference.\n\nIn many countries, the characteristics of trips and visitors are established through questions on the entry/departure cards, in surveys at the borders, at destination (accommodation surveys) or as part of household surveys (for domestic and outbound tourism). The entry/departure cards, or records of entry and departure, captured and reconciled by the immigration authorities are often the basic source for establishing the flows of inbound and outbound visitors. These cards usually collect information on a census basis on name, sex, age, nationality, current address, date of arrival (or departure in the departure card), purpose of trip, main destination visited and length of stay (expected on arrival and actual on departure for inbound visitors; expected on departure and actual on arrival for outbound visitors).\n\nData is collected using one of three methods, or a combination of these to determine the flows of outbound visitors: using an entry/departure card; a specific survey at the border, or observing them from household surveys because they belong to resident households. In the latter case, the information on outbound trips is usually collected at the same time as that on domestic trips.","theme":"tertiary","source_group":"wb"},{"code":"ST.INT.RCPT.XP.ZS","name":"Tourisme international, recettes ( % des exportations totales)","description":"Les recettes du tourisme international sont les dépenses des visiteurs internationaux entrants, y compris les paiements aux transporteurs nationaux...","source_link":"https://donnees.banquemondiale.org/indicateur/ST.INT.RCPT.XP.ZS?locations=CI","methodology":"Methodology: Inbound tourism expenditures may include receipts from same-day visitors, except when these are important enough to justify separate classification. For some countries they do not include receipts for passenger transport items. Their share in exports is calculated as a ratio to exports of goods and services (all transactions between residents of a country and the rest of the world involving a change of ownership from residents to nonresidents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services).\n\nInternational tourism expenditures' share in exports is calculated as a ratio to exports of goods and services, which comprise all transactions between residents of a country and the rest of the world involving a change of ownership from residents to nonresidents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services.\n\nStatistical information on tourism is based mainly on data on arrivals and overnight stays along with balance of payments information. These data do not completely capture the economic phenomenon of tourism or provide the information needed for effective public policies and efficient business operations. Data are needed on the scale and significance of tourism. Information on the role of tourism in national economies is particularly deficient. Although the World Tourism Organization (WTO) reports progress in harmonizing definitions and measurement, differences in national practices still prevent full comparability.\n\nThe World Tourism Organization is improving its coverage of tourism expenditure data, using balance of payments data from the International Monetary Fund (IMF) supplemented by data from individual countries. These data include travel and passenger transport items as defined in the IMF's Balance of Payments. When the IMF does not report data on passenger transport items, expenditure data for travel items are shown.\n\nThe aggregates are calculated using the World Bank's weighted aggregation methodology and differ from the World Tourism Organization's aggregates.","theme":"tertiary","source_group":"wb"},{"code":"ST.INT.RCPT.CD","name":"Tourisme international, recettes (en dollars américains courants)","description":"Les recettes du tourisme international sont les dépenses des visiteurs internationaux entrants, y compris les paiements aux transporteurs nationaux...","source_link":"https://donnees.banquemondiale.org/indicateur/ST.INT.RCPT.CD?locations=CI","methodology":"Methodology: Inbound tourism expenditures may include receipts from same-day visitors, except when these are important enough to justify separate classification. For some countries they do not include receipts for passenger transport items. Their share in exports is calculated as a ratio to exports of goods and services (all transactions between residents of a country and the rest of the world involving a change of ownership from residents to nonresidents of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services).\n\nStatistical information on tourism is based mainly on data on arrivals and overnight stays along with balance of payments information. These data do not completely capture the economic phenomenon of tourism or provide the information needed for effective public policies and efficient business operations. Data are needed on the scale and significance of tourism. Information on the role of tourism in national economies is particularly deficient. Although the World Tourism Organization (WTO) reports progress in harmonizing definitions and measurement, differences in national practices still prevent full comparability.\n\nThe World Tourism Organization is improving its coverage of tourism expenditure data, using balance of payments data from the International Monetary Fund (IMF) supplemented by data from individual countries. These data include travel and passenger transport items as defined in the IMF's Balance of Payments. When the IMF does not report data on passenger transport items, expenditure data for travel items are shown.\n\nThe aggregates are calculated using the World Bank's weighted aggregation methodology and differ from the World Tourism Organization's aggregates.","theme":"tertiary","source_group":"wb"},{"code":"ST.INT.TRNR.CD","name":"Tourisme international, recettes pour le transport de passagers (en dollars courants des États-Unis)","description":"Les recettes du tourisme international pour les éléments de transport de passagers sont les dépenses des visiteurs internationaux entrants pour tou...","source_link":"https://donnees.banquemondiale.org/indicateur/ST.INT.TRNR.CD?locations=CI","methodology":"Methodology: Tourism data is compiled based on the International Recommendations for Tourism Statistics (IRTS 2008). The World Tourism Organization enhances its coverage of tourism expenditure data by using balance of payments data from the International Monetary Fund (IMF) supplemented by data from individual countries. When data on passenger transport items is unavailable, expenditure data for travel items are shown.","theme":"tertiary","source_group":"wb"},{"code":"ST.INT.TVLR.CD","name":"Tourisme international, recettes pour les articles de voyage (en dollars américains courants)","description":"Les recettes du tourisme international pour les articles de voyage sont les dépenses des visiteurs internationaux entrants dans l’économie déclarante.","source_link":"https://donnees.banquemondiale.org/indicateur/ST.INT.TVLR.CD?locations=CI","methodology":"Methodology: Tourism data is compiled based on the International Recommendations for Tourism Statistics (IRTS 2008). The World Tourism Organization enhances its coverage of tourism expenditure data by using balance of payments data from the International Monetary Fund (IMF) supplemented by data from individual countries. When data on passenger transport items is unavailable, expenditure data for travel items are shown.","theme":"tertiary","source_group":"wb"},{"code":"IE.PPI.ENGY.CD","name":"Investissement dans l'énergie avec participation privée (en dollars courants des États-Unis)","description":"La base de données sur la participation privée aux infrastructures (PPI) enregistre les accords contractuels pour les projets d'infrastructures pub...","source_link":"https://donnees.banquemondiale.org/indicateur/IE.PPI.ENGY.CD?locations=CI","methodology":"Methodology: A team of researchers gather data for each of the regions using public sources (from government and MDBs websites); commercial news databases (such as Factiva, Business News America, ISI Emerging markets, and the Economist Intelligence Unit’s databases) as well as from commercial specialized and industry publications/subscriptions (Thomson Financial’s Project Finance International, Euromoney’s Project Finance, Media Analytics’ Global Water Intelligence, Pisent Masons’ Water Yearbooks, and Platt’s Power in Asia, etc.), specialist portal (such as Privatization, IPAnet, and Privatization Barometer), Internet resources (such as web sites of project companies, privatization or Public-Private Partnership (PPP) agencies, and regulatory agencies) sponsor information (primarily through their websites, annual reports, press releases, and financial reports such as 10K and 20F forms submitted to the NYSE) and multilateral development agencies primarily through information on their websites, annual reports, and other studies.\n\nData is uploaded to an administrative website through a template ensure that the data is standardized. Data is validated by a group of experts in Singapore first (PPI team), then by the World Bank focal points colleagues.\n\nData is later uploaded to the public website (www.ppi.worldbank.org) and made available free of charge. The website has a mechanism for challenges to the data and welcomes all PPP units to give feedback about any project.\n\n\nStatistical concept(s): PPPs is defined as “any contractual arrangement between a public entity or authority and a private entity, for providing a public asset or service, in which the private party bears significant risk and management responsibility.”\nThe term infrastructure refers to:\n• Energy: electricity generation, transmission, and distribution, and natural gas transmission and\ndistribution pipelines\n• Information and communications technology (ICT): ICT backbone infrastructure\n• Transport: Airports, railways, ports, and roads.\n• Water: potable water treatment and distribution, and sewerage collection and treatment.","theme":"secondary","source_group":"wb"},{"code":"IE.PPI.ICTI.CD","name":"Investissement dans les TIC avec participation privée (en dollars américains courants)","description":"La base de données sur la participation privée aux infrastructures (PPI) enregistre les accords contractuels pour les projets d'infrastructures pub...","source_link":"https://donnees.banquemondiale.org/indicateur/IE.PPI.ICTI.CD?locations=CI","methodology":"Methodology: A team of researchers gather data for each of the regions using public sources (from government and MDBs websites); commercial news databases (such as Factiva, Business News America, ISI Emerging markets, and the Economist Intelligence Unit’s databases) as well as from commercial specialized and industry publications/subscriptions (Thomson Financial’s Project Finance International, Euromoney’s Project Finance, Media Analytics’ Global Water Intelligence, Pisent Masons’ Water Yearbooks, and Platt’s Power in Asia, etc.), specialist portal (such as Privatization, IPAnet, and Privatization Barometer), Internet resources (such as web sites of project companies, privatization or Public-Private Partnership (PPP) agencies, and regulatory agencies) sponsor information (primarily through their websites, annual reports, press releases, and financial reports such as 10K and 20F forms submitted to the NYSE) and multilateral development agencies primarily through information on their websites, annual reports, and other studies.\n\nData is uploaded to an administrative website through a template ensure that the data is standardized. Data is validated by a group of experts in Singapore first (PPI team), then by the World Bank focal points colleagues.\n\nData is later uploaded to the public website (www.ppi.worldbank.org) and made available free of charge. The website has a mechanism for challenges to the data and welcomes all PPP units to give feedback about any project.\n\n\nStatistical concept(s): PPPs is defined as “any contractual arrangement between a public entity or authority and a private entity, for providing a public asset or service, in which the private party bears significant risk and management responsibility.”\nThe term infrastructure refers to:\n• Energy: electricity generation, transmission, and distribution, and natural gas transmission and\ndistribution pipelines\n• Information and communications technology (ICT): ICT backbone infrastructure\n• Transport: Airports, railways, ports, and roads.\n• Water: potable water treatment and distribution, and sewerage collection and treatment.","theme":"secondary","source_group":"wb"},{"code":"IE.PPI.TRAN.CD","name":"Investissement dans les transports avec participation privée (en dollars courants des États-Unis)","description":"La base de données sur la participation privée aux infrastructures (PPI) enregistre les accords contractuels pour les projets d'infrastructures pub...","source_link":"https://donnees.banquemondiale.org/indicateur/IE.PPI.TRAN.CD?locations=CI","methodology":"Methodology: A team of researchers gather data for each of the regions using public sources (from government and MDBs websites); commercial news databases (such as Factiva, Business News America, ISI Emerging markets, and the Economist Intelligence Unit’s databases) as well as from commercial specialized and industry publications/subscriptions (Thomson Financial’s Project Finance International, Euromoney’s Project Finance, Media Analytics’ Global Water Intelligence, Pisent Masons’ Water Yearbooks, and Platt’s Power in Asia, etc.), specialist portal (such as Privatization, IPAnet, and Privatization Barometer), Internet resources (such as web sites of project companies, privatization or Public-Private Partnership (PPP) agencies, and regulatory agencies) sponsor information (primarily through their Web sites, annual reports, press releases, and financial reports such as 10K and 20F forms submitted to the NYSE) and multilateral development agencies primarily through information on their websites, annual reports, and other studies.\n\nData is uploaded to an administrative website through a template ensure that the data is standardized. Data is validated by a group of experts in Singapore first (PPI team), then by the World Bank focal points colleagues.\n\nData is later uploaded to the public website (www.ppi.worldbank.org) and made available free of charge. The website has a mechanism for challenges to the data and welcomes all PPP units to give feedback about any project.\n\n\nStatistical concept(s): PPPs is defined as “any contractual arrangement between a public entity or authority and a private entity, for providing a public asset or service, in which the private party bears significant risk and management responsibility.”\nThe term infrastructure refers to:\n• Energy: electricity generation, transmission, and distribution, and natural gas transmission and\ndistribution pipelines\n• Information and communications technology (ICT): ICT backbone infrastructure\n• Transport: Airports, railways, ports, and roads.\n• Water: potable water treatment and distribution, and sewerage collection and treatment.","theme":"secondary","source_group":"wb"},{"code":"IE.PPI.WATR.CD","name":"Investissements dans l'eau et l'assainissement avec participation privée (en dollars américains courants)","description":"La base de données sur la participation privée aux infrastructures (PPI) enregistre les accords contractuels pour les projets d'infrastructures pub...","source_link":"https://donnees.banquemondiale.org/indicateur/IE.PPI.WATR.CD?locations=CI","methodology":"Methodology: A team of researchers gather data for each of the regions using public sources (from government and MDBs websites); commercial news databases (such as Factiva, Business News America, ISI Emerging markets, and the Economist Intelligence Unit’s databases) as well as from commercial specialized and industry publications/subscriptions (Thomson Financial’s Project Finance International, Euromoney’s Project Finance, Media Analytics’ Global Water Intelligence, Pisent Masons’ Water Yearbooks, and Platt’s Power in Asia, etc.), specialist portal (such as Privatization, IPAnet, and Privatization Barometer), Internet resources (such as web sites of project companies, privatization or Public-Private Partnership (PPP) agencies, and regulatory agencies) sponsor information (primarily through their websites, annual reports, press releases, and financial reports such as 10K and 20F forms submitted to the NYSE) and multilateral development agencies primarily through information on their Websites, annual reports, and other studies.\n\nData is uploaded to an administrative website through a template to make sure data is standardized. Data is validated by a group of experts in Singapore first (PPI team), then for the World Bank focal points colleagues.\n\nData is later uploaded to the public website (www.ppi.worldbank.org) and made available free of charge. The website has a mechanism for challenges to the data and welcomes all PPP units to give feedback about any project.\n\nStatistical concept(s): PPPs is defined as “any contractual arrangement between a public entity or authority and a private entity, for providing a public asset or service, in which the private party bears significant risk and management responsibility.”\nThe term infrastructure refers to:\n• Energy: electricity generation, transmission, and distribution, and natural gas transmission and\ndistribution pipelines\n• Information and communications technology (ICT): ICT backbone infrastructure\n• Transport: Airports, railways, ports, and roads.\n• Water: potable water treatment and distribution, and sewerage collection and treatment.","theme":"secondary","source_group":"wb"},{"code":"SL.TLF.ACTI.1524.FE.ZS","name":"Taux d'activité des 15-24 ans, femmes ( %) (estimation modélisée de l'OIT)","description":"Le taux de participation au marché du travail pour les 15-24 ans est la proportion de la population âgée de 15-24 ans qui est économiquement active...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.ACTI.1524.FE.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.ACTI.1524.FE.NE.ZS","name":"Taux d'activité des 15-24 ans, femmes ( %) (estimation nationale)","description":"Le taux de participation au marché du travail pour les 15-24 ans est la proportion de la population âgée de 15-24 ans qui est économiquement active...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.ACTI.1524.FE.NE.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.ACTI.1524.MA.ZS","name":"Taux d'activité des 15-24 ans, hommes ( %) (estimation modélisée de l'OIT)","description":"Le taux de participation au marché du travail pour les 15-24 ans est la proportion de la population âgée de 15-24 ans qui est économiquement active...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.ACTI.1524.MA.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.ACTI.1524.MA.NE.ZS","name":"Taux d'activité des 15-24 ans, hommes ( %) (estimation nationale)","description":"Le taux de participation au marché du travail pour les 15-24 ans est la proportion de la population âgée de 15-24 ans qui est économiquement active...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.ACTI.1524.MA.NE.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.ACTI.1524.ZS","name":"Taux d'activité des 15-24 ans, total ( %) (estimation modélisée de l'OIT)","description":"Le taux de participation au marché du travail pour les 15-24 ans est la proportion de la population âgée de 15-24 ans qui est économiquement active...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.ACTI.1524.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.ACTI.1524.NE.ZS","name":"Taux d'activité des 15-24 ans, total ( %) (estimation nationale)","description":"Le taux de participation au marché du travail pour les 15-24 ans est la proportion de la population âgée de 15-24 ans qui est économiquement active...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.ACTI.1524.NE.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.CACT.FE.ZS","name":"Taux d'activité féminin ( % de la population féminine âgée de 15 ans et +) (estimation modélisée de l'OIT)","description":"Le taux de participation à la population active correspond à la population active exprimée en pourcentage de la population âgée de 15 ans et plus.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.CACT.FE.ZS?locations=CI","methodology":"Methodology: The labor force participation rate (LFPR) is calculated as follows: \n\n\nLFPR (%) = 100 x Labor force / population of a given age group, where the labor force is equal to employment plus unemployment.\n\n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Population censuses are another major source of data on the labor force and its components.\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.CACT.FE.NE.ZS","name":"Taux d'activité féminin ( % de la population féminine âgée de 15 ans et +) (estimation nationale)","description":"Le taux de participation à la population active est la proportion de la population âgée de 15 ans et plus qui est économiquement active : toutes le...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.CACT.FE.NE.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\n\n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.ACTI.FE.ZS","name":"Taux d'activité des femmes ( % de la population féminine âgée de 15 à 64 ans) (estimation modélisée de l'OIT)","description":"Le taux de participation à la population active est la proportion de la population âgée de 15 à 64 ans qui est économiquement active : toutes les p...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.ACTI.FE.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.CACT.MA.ZS","name":"Taux d'activité masculin ( % de la population masculine âgée de 15 ans et +) (estimation modélisée de l'OIT)","description":"Le taux de participation à la population active est la proportion de la population âgée de 15 ans et plus qui est économiquement active : toutes le...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.CACT.MA.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.CACT.MA.NE.ZS","name":"Taux d'activité masculin (en % de la population masculine âgée de 15 ans et +) (estimation nationale)","description":"Le taux de participation à la population active est la proportion de la population âgée de 15 ans et plus qui est économiquement active : toutes le...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.CACT.MA.NE.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.ACTI.MA.ZS","name":"Taux d'activité masculin ( % de la population masculine âgée de 15 à 64 ans) (estimation modélisée de l'OIT)","description":"Le taux de participation à la population active est la proportion de la population âgée de 15 à 64 ans qui est économiquement active : toutes les p...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.ACTI.MA.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.CACT.ZS","name":"Taux d'activité total ( % de la population totale âgée de 15 ans et +) (estimation modélisée de l'OIT)","description":"Le taux de participation à la population active est la proportion de la population âgée de 15 ans et plus qui est économiquement active : toutes le...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.CACT.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.CACT.NE.ZS","name":"Taux d'activité total (en % de la population totale âgée de 15 ans et +) (estimation nationale)","description":"Le taux de participation à la population active est la proportion de la population âgée de 15 ans et plus qui est économiquement active : toutes le...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.CACT.NE.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.ACTI.ZS","name":"Taux d'activité total ( % de la population totale âgée de 15 à 64 ans) (estimation modélisée de l'OIT)","description":"Le taux de participation à la population active est la proportion de la population âgée de 15 à 64 ans qui est économiquement active : toutes les p...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.ACTI.ZS?locations=CI","methodology":"Methodology: The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.ADVN.ZS","name":"Main-d'œuvre ayant fait des études supérieures (en % de la population totale en âge de travailler ayant fait des études supérieures)","description":"Le rapport entre la population active ayant fait des études supérieures et la population en âge de travailler ayant fait des études supérieures.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.ADVN.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force participation rate is the labor force as a percent of the working-age population. The labor force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.ADVN.FE.ZS","name":"Main-d'œuvre ayant fait des études supérieures, femmes ( % de la population féminine en âge de travailler ayant fait des études supérieures)","description":"Le rapport entre la population active ayant fait des études supérieures et la population en âge de travailler ayant fait des études supérieures.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.ADVN.FE.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force participation rate is the labor force as a percent of the working-age population. The labor force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.ADVN.MA.ZS","name":"Population active ayant fait des études supérieures, hommes ( % de la population masculine en âge de travailler ayant fait des études supérieures)","description":"Le rapport entre la population active ayant fait des études supérieures et la population en âge de travailler ayant fait des études supérieures.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.ADVN.MA.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force participation rate is the labor force as a percent of the working-age population. The labor force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.BASC.ZS","name":"Main-d'œuvre ayant un niveau d'éducation de base (en % de la population totale en âge de travailler ayant reçu un niveau d'éducation de base)","description":"Le rapport entre la population active ayant reçu une éducation de base et la population en âge de travailler ayant reçu une éducation de base.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.BASC.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force participation rate is the labor force as a percent of the working-age population. The labor force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.BASC.FE.ZS","name":"Main-d'œuvre ayant un niveau d'éducation de base, femmes ( % de la population féminine en âge de travailler ayant reçu un niveau d'éducation de base)","description":"Le rapport entre la population active ayant reçu une éducation de base et la population en âge de travailler ayant reçu une éducation de base.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.BASC.FE.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force participation rate is the labor force as a percent of the working-age population. The labor force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.BASC.MA.ZS","name":"Main-d'œuvre ayant un niveau d'éducation de base, hommes ( % de la population masculine en âge de travailler ayant reçu un niveau d'éducation de base)","description":"Le rapport entre la population active ayant reçu une éducation de base et la population en âge de travailler ayant reçu une éducation de base.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.BASC.MA.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force participation rate is the labor force as a percent of the working-age population. The labor force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.INTM.ZS","name":"Main-d'œuvre ayant un niveau d'éducation intermédiaire ( % de la population totale en âge de travailler ayant un niveau d'éducation intermédiaire)","description":"Le rapport entre la population active ayant une éducation intermédiaire et la population en âge de travailler ayant une éducation intermédiaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.INTM.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force participation rate is the labor force as a percent of the working-age population. The labor force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.INTM.FE.ZS","name":"Main-d'œuvre ayant un niveau d'éducation intermédiaire, femmes ( % de la population féminine en âge de travailler ayant un niveau d'éducation intermédiaire)","description":"Le rapport entre la population active ayant une éducation intermédiaire et la population en âge de travailler ayant une éducation intermédiaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.INTM.FE.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force participation rate is the labor force as a percent of the working-age population. The labor force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.INTM.MA.ZS","name":"Population active ayant un niveau d'éducation intermédiaire, hommes ( % de la population masculine en âge de travailler ayant un niveau d'éducation intermédiaire)","description":"Le rapport entre la population active ayant une éducation intermédiaire et la population en âge de travailler ayant une éducation intermédiaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.INTM.MA.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force participation rate is the labor force as a percent of the working-age population. The labor force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.TOTL.FE.ZS","name":"Main-d'œuvre féminine ( % de la population active totale)","description":"La population active féminine en pourcentage du total montre dans quelle mesure les femmes sont actives dans la population active.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.TOTL.FE.ZS?locations=CI","methodology":"Methodology: Estimates are based on labor force participation rates and population data from International Labour Organization and United Nations Population Division. The labor force participation rates are part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or voluntarily left work. In addition, persons who did not look for work but have an arrangement for a future job are also counted as unemployed. Still, some unemployment is unavoidable—at any time, some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. The labor force or the economically active portion of the population serves as the base for this indicator, not the total population.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.TOTL.IN","name":"Population active, total","description":"La population active comprend les personnes âgées de 15 ans et plus qui fournissent de la main-d'œuvre pour la production de biens et de services p...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.TOTL.IN?locations=CI","methodology":"Methodology: Estimates are based on labor force participation rates and population data from International Labour Organization and United Nations Population Division. The labor force participation rates are part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or voluntarily left work. In addition, persons who did not look for work but have an arrangement for a future job are also counted as unemployed. Still, some unemployment is unavoidable—at any time, some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. The labor force or the economically active portion of the population serves as the base for this indicator, not the total population.","theme":"emploi","source_group":"wb"},{"code":"AG.LND.TOTL.K2","name":"Superficie du terrain (km²)","description":"La superficie terrestre est la superficie totale d'un pays, à l'exclusion de la superficie située sous les masses d'eau intérieures, des revendicat...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.TOTL.K2?locations=CI","methodology":"Methodology: Total land area does not include inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area. Including areas of former states; for example, the areas of the Union of Soviet Socialist Republics (USSR) are counted in Russian Federation and other successor states.","theme":"primary","source_group":"wb"},{"code":"AG.LND.EL5M.ZS","name":"Superficie du terrain dont l'altitude est inférieure à 5 mètres ( % de la superficie totale du terrain)","description":"La superficie inférieure à 5 m correspond au pourcentage de la superficie totale du terrain dont l'élévation est de 5 mètres ou moins.","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.EL5M.ZS?locations=CI","methodology":"Methodology: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).","theme":"primary","source_group":"wb"},{"code":"AG.LND.CREL.HA","name":"Terres consacrées à la production céréalière (hectares)","description":"Les terres consacrées à la production céréalière font référence à la superficie récoltée, bien que certains pays ne déclarent que la superficie ens...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.CREL.HA?locations=CI","methodology":"Methodology: Cereals production includes wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded.\nA cereal is a grass cultivated for the edible components of their grain, composed of the endosperm, germ, and bran. Cereal grains are grown in greater quantities and provide more food energy worldwide than any other type of crop; cereal crops therefore can also be called staple crops.","theme":"primary","source_group":"wb"},{"code":"LP.EXP.DURS.MD","name":"Délai d'exportation, cas médian (jours)","description":"Le délai d’exportation est le temps médian (la valeur pour 50 pour cent des expéditions) entre le point d’expédition et le port de chargement.","source_link":"https://donnees.banquemondiale.org/indicateur/LP.EXP.DURS.MD?locations=CI","methodology":"Methodology: Data on lead time to export are from the Logistics Performance Index (LPI) survey. Respondents provided separate values for the best case (10 percent of shipments) and the median case (50 percent of shipments) of shipments from the point of origin (the seller's factory, typically located either in the capital city or in the largest commercial center) to the port of loading or equivalent (port/airport), and excluding international shipping.\n\nThe Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and at the main express carriers. The 2012 LPI data are based on the 2011 survey, which was administered to nearly 1,000 respondents at international logistics companies in 143 countries (domestic performance indicators). The international LPI covers 155 countries. The LPI assesses both large companies and small and medium enterprises. Most of the responses are from small and medium enterprises, with large companies (those with 250 employees or more) accounting for roughly 18 percent of responses. The respondents include groups of professionals who are directly involved in day-today operations, from company headquarters and from country offices such as senior executives, area or country managers, and department managers. Many of the respondents are at corporate or regional headquarters or at country branch offices. The rest are at local branch offices or independent firms. The majority of respondents are involved in providing most logistics services as their main line of work such as warehousing and distribution, customer-tailored logistics solutions, courier services, bulk or break bulk cargo transport, and less-than-full container, full-container, or full-trailer load transport. \n\nFor the lead time to export, respondents were asked for quantitative information on their countries' international supply chains by picking choices from a dropdown menu. When a response indicates a single value, the answer is coded as the logarithm of that value. When a response indicates a range, the answer is coded as the logarithm of the midpoint of that range. Country scores are produced by exponentiating the average of responses in logarithms across all respondents for a given country. This method is equivalent to taking a geometric average in levels. Scores for regions, income groups, and LPI quintiles are simple averages of the relevant country scores.","theme":"inter","source_group":"wb"},{"code":"LP.IMP.DURS.MD","name":"Délai d'importation, cas médian (jours)","description":"Le délai d’importation est le temps médian (la valeur pour 50 pour cent des expéditions) entre le port de déchargement et l’arrivée chez le destina...","source_link":"https://donnees.banquemondiale.org/indicateur/LP.IMP.DURS.MD?locations=CI","methodology":"Methodology: Data on lead time to import are from the Logistics Performance Index (LPI) survey. Respondents provided separate values for the best case (10 percent of shipments) and the median case (50 percent of shipments) of shipments from the port of discharge or equivalent to the buyer's warehouse.\n\nThe Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and at the main express carriers. The 2012 LPI data are based on the 2011 survey, which was administered to nearly 1,000 respondents at international logistics companies in 143 countries (domestic performance indicators). The international LPI covers 155 countries. The LPI assesses both large companies and small and medium enterprises. Most of the responses are from small and medium enterprises, with large companies (those with 250 employees or more) accounting for roughly 18 percent of responses. The respondents include groups of professionals who are directly involved in day-today operations, from company headquarters and from country offices such as senior executives, area or country managers, and department managers. Many of the respondents are at corporate or regional headquarters or at country branch offices. The rest are at local branch offices or independent firms. The majority of respondents are involved in providing most logistics services as their main line of work such as warehousing and distribution, customer-tailored logistics solutions, courier services, bulk or break bulk cargo transport, and less-than-full container, full-container, or full-trailer load transport.\n\nFor the lead time to import, respondents were asked for quantitative information on their countries' international supply chains by picking choices from a dropdown menu. When a response indicates a single value, the answer is coded as the logarithm of that value. When a response indicates a range, the answer is coded as the logarithm of the midpoint of that range. Country scores are produced by exponentiating the average of responses in logarithms across all respondents for a given country. This method is equivalent to taking a geometric average in levels. Scores for regions, income groups, and LPI quintiles are simple averages of the relevant country scores.","theme":"inter","source_group":"wb"},{"code":"SE.LPV.PRIM","name":"Pauvreté des apprentissages : Proportion d'enfants en fin d'année primaire ayant des compétences minimales en lecture ajustées en fonction des enfants non scolarisés ( %)","description":"La part des enfants de 10 ans qui ne savent pas lire et comprendre un court passage d’un matériel adapté à leur âge – en d’autres termes, ceux qui ...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.LPV.PRIM?locations=CI","methodology":"Methodology: The learning poverty indicator brings together schooling and learning indicators. It starts with the share of children in school who haven’t achieved minimum reading proficiency (Learning Deprived) and adjusts it by the proportion of children who are out of school (Schooling Deprived). \nFormally, Learning Poverty is calculated as: [LD* (1-SD)] + [1 * SD]\nwhere LP = Learning poverty; LD = Learning deprivation or the share of children at the end of primary who read at below the minimum proficiency level, as defined by the Global Alliance to Monitor Learning (GAML) in the context of the SDG 4.1.1 monitoring; SD = Schooling deprivation or the share of primary-school-age children who are out-of-school (OOS) and in which all OOS are regarded as being below the minimum proficiency level.\nBecause out-of-school children are treated as non-proficient in reading, learning poverty will always be higher than the share of children in school who haven't achieved minimum reading proficiency. For countries with a very low schooling deprivation, the learning deprivation value will be very close to Learning Poverty. \nEstimating the current level of global and regional learning poverty requires deciding how to define “current.” We include results of assessments within four years before or after a set anchor year. This decision is driven by data availability. International and regional large-scale learning assessments used for SDG 4.1.1b reporting are carried out only every 3 to 4 years. And even where assessments have been carried out recently, there is a lag of a couple of years before the data are available. This band is intended as a moving window. In the original 2019 release, the anchor year used was 2015 (Assessments between 2011 and 2019 are included in the learning poverty estimate). In the 2022 Global Update, the anchor year was moved to 2019 (assessments between 2015 and 2023 are included).\nAggregations for each region comprise the average learning poverty of countries with available data, weighted by their population ages 10–14 years old. To obtain a global estimate, we weight the regional aggregations by the 10–14-year-old population regardless of data availability. This is equivalent to imputing missing country data using regional values.\nStatistical concept(s): Minimum Proficiency Level (MPL) in Reading","theme":"education","source_group":"wb"},{"code":"SE.LPV.PRIM.FE","name":"Pauvreté des apprentissages : proportion d'enfants de sexe féminin en fin d'année primaire ayant des compétences minimales en lecture, ajustée en fonction des enfants non scolarisés ( %)","description":"La part des filles de 10 ans qui ne savent pas lire et comprendre un court extrait d’un texte adapté à leur âge – en d’autres termes, celles qui se...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.LPV.PRIM.FE?locations=CI","methodology":"Methodology: The learning poverty indicator brings together schooling and learning indicators. It starts with the share of children in school who haven’t achieved minimum reading proficiency (Learning Deprived) and adjusts it by the proportion of children who are out of school (Schooling Deprived). \nFormally, Learning Poverty is calculated as: [LD* (1-SD)] + [1 * SD]\nwhere LP = Learning poverty; LD = Learning deprivation or the share of children at the end of primary who read at below the minimum proficiency level, as defined by the Global Alliance to Monitor Learning (GAML) in the context of the SDG 4.1.1 monitoring; SD = Schooling deprivation or the share of primary-school-age children who are out-of-school (OOS) and in which all OOS are regarded as being below the minimum proficiency level.\nBecause out-of-school children are treated as non-proficient in reading, learning poverty will always be higher than the share of children in school who haven't achieved minimum reading proficiency. For countries with a very low schooling deprivation, the learning deprivation value will be very close to Learning Poverty. \nEstimating the current level of global and regional learning poverty requires deciding how to define “current.” We include results of assessments within four years before or after a set anchor year. This decision is driven by data availability. International and regional large-scale learning assessments used for SDG 4.1.1b reporting are carried out only every 3 to 4 years. And even where assessments have been carried out recently, there is a lag of a couple of years before the data are available. This band is intended as a moving window. In the original 2019 release, the anchor year used was 2015 (Assessments between 2011 and 2019 are included in the learning poverty estimate). In the 2022 Global Update, the anchor year was moved to 2019 (assessments between 2015 and 2023 are included).\nAggregations for each region comprise the average learning poverty of countries with available data, weighted by their population ages 10–14 years old. To obtain a global estimate, we weight the regional aggregations by the 10–14-year-old population regardless of data availability. This is equivalent to imputing missing country data using regional values.\nStatistical concept(s): Minimum Proficiency Level (MPL) in Reading","theme":"education","source_group":"wb"},{"code":"SE.LPV.PRIM.MA","name":"Pauvreté des apprentissages : proportion d'enfants de sexe masculin en âge de terminer l'école primaire ayant des compétences minimales en lecture, ajustée en fonction des enfants non scolarisés ( %)","description":"La part des garçons de 10 ans qui ne savent pas lire et comprendre un court extrait d’un texte adapté à leur âge – en d’autres termes, ceux qui se ...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.LPV.PRIM.MA?locations=CI","methodology":"Methodology: The learning poverty indicator brings together schooling and learning indicators. It starts with the share of children in school who haven’t achieved minimum reading proficiency (Learning Deprived) and adjusts it by the proportion of children who are out of school (Schooling Deprived). \nFormally, Learning Poverty is calculated as: [LD* (1-SD)] + [1 * SD]\nwhere LP = Learning poverty; LD = Learning deprivation or the share of children at the end of primary who read at below the minimum proficiency level, as defined by the Global Alliance to Monitor Learning (GAML) in the context of the SDG 4.1.1 monitoring; SD = Schooling deprivation or the share of primary-school-age children who are out-of-school (OOS) and in which all OOS are regarded as being below the minimum proficiency level.\nBecause out-of-school children are treated as non-proficient in reading, learning poverty will always be higher than the share of children in school who haven't achieved minimum reading proficiency. For countries with a very low schooling deprivation, the learning deprivation value will be very close to Learning Poverty. \nEstimating the current level of global and regional learning poverty requires deciding how to define “current.” We include results of assessments within four years before or after a set anchor year. This decision is driven by data availability. International and regional large-scale learning assessments used for SDG 4.1.1b reporting are carried out only every 3 to 4 years. And even where assessments have been carried out recently, there is a lag of a couple of years before the data are available. This band is intended as a moving window. In the original 2019 release, the anchor year used was 2015 (Assessments between 2011 and 2019 are included in the learning poverty estimate). In the 2022 Global Update, the anchor year was moved to 2019 (assessments between 2015 and 2023 are included).\nAggregations for each region comprise the average learning poverty of countries with available data, weighted by their population ages 10–14 years old. To obtain a global estimate, we weight the regional aggregations by the 10–14-year-old population regardless of data availability. This is equivalent to imputing missing country data using regional values.\nStatistical concept(s): Minimum Proficiency Level (MPL) in Reading","theme":"education","source_group":"wb"},{"code":"FR.INR.LEND","name":"Taux d'intérêt débiteur ( %)","description":"Le taux débiteur est le taux d’escompte qui répond habituellement aux besoins de financement à court et moyen terme du secteur privé.","source_link":"https://donnees.banquemondiale.org/indicateur/FR.INR.LEND?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"ER.H2O.FWST.ZS","name":"Niveau de stress hydrique : prélèvement d'eau douce en proportion des ressources en eau douce disponibles","description":"Le niveau de stress hydrique : les prélèvements d'eau douce en proportion des ressources en eau douce disponibles sont le rapport entre le total de...","source_link":"https://donnees.banquemondiale.org/indicateur/ER.H2O.FWST.ZS?locations=CI","methodology":"Methodology: Proportion of total renewable water resources withdrawn is the total volume of groundwater and surface water withdrawn from their sources for human use (in the agricultural, municipal and industrial sectors), expressed as a percentage of the total actual renewable water resources. The terms water resources and water withdrawal are understood as freshwater resources and freshwater withdrawal. Water withdrawal is estimated for the following three main sectors: agriculture, municipalities (including domestic water withdrawal) and industries, at country level and expressed in km3/year. The total actual renewable water resources for a country or region are defined as the sum of internal renewable water resources and the external renewable water resources, also expressed in km3/year. The indicator is computed by dividing total water withdrawal by total actual renewable water resources minus environmental requirements and expressed in percentage points.\n\n\n\n\n\n\n\n\n\n\n\nTotal freshwater withdrawal is the volume of freshwater extracted from its source (rivers, lakes, aquifers) for agriculture, industries and municipalities. It is estimated at the country level for the following three main sectors: agriculture, municipalities (including domestic water withdrawal) and industries. Freshwater withdrawal includes primary freshwater (not withdrawn before), secondary freshwater (previously withdrawn and returned to rivers and groundwater, such as discharged wastewater and agricultural drainage water) and fossil groundwater. It does not include non-conventional water, i.e. direct use of treated wastewater, direct use of agricultural drainage water and desalinated water. Total freshwater withdrawal is in general calculated as being the sum of total water withdrawal by sector minus direct use of wastewater, direct use of agricultural drainage water and use of desalinated water.\n\n\n\n\n\n\n\n\n\n\n\nTotal renewable freshwater resources are expressed as the sum of internal and external renewable water resources. The terms “water resources” and “water withdrawal” are understood here as freshwater resources and freshwater withdrawal. Internal renewable water resources are defined as the long-term average annual flow of rivers and recharge of groundwater for a given country generated from endogenous precipitation. External renewable water resources refer to the flows of water entering the country, taking into consideration the quantity of flows reserved to upstream and downstream countries through agreements or treaties.\n\n\n\n\n\n\n\n\n\n\n\nEnvironmental water requirements (Env.) are the quantities of water required to sustain freshwater and estuarine ecosystems. Water quality and also the resulting ecosystem services are excluded from this formulation which is confined to water volumes. This does not imply that quality and the support to societies which are dependent on environmental flows are not important and should not be taken care of. Methods of computation of Env. are extremely variable and range from global estimates to comprehensive assessments for river reaches. Water volumes can be expressed in the same units as the total freshwater withdrawal, and then as percentages of the available water resources.","theme":"territory","source_group":"wb"},{"code":"SP.DYN.LE00.FE.IN","name":"Espérance de vie à la naissance, femme (années)","description":"L'espérance de vie à la naissance indique le nombre d'années qu'un nouveau-né vivrait si les schémas de mortalité dominants au moment de sa naissan...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.LE00.FE.IN?locations=CI","methodology":"Methodology: Life expectancy at birth is derived from life tables and is based on sex- and age-specific death rates.\nStatistical concept(s): Life expectancy at birth used here is the average number of years a newborn is expected to live if mortality patterns at the time of its birth remain constant in the future. It reflects the overall mortality level of a population, and summarizes the mortality pattern that prevails across all age groups in a given year. It is calculated in a period life table which provides a snapshot of a population's mortality pattern at a given time. It therefore does not reflect the mortality pattern that a person actually experiences during his/her life, which can be calculated in a cohort life table.\nHigh mortality in young age groups significantly lowers the life expectancy at birth. But if a person survives his/her childhood of high mortality, he/she may live much longer. For example, in a population with a life expectancy at birth of 50, there may be few people dying at age 50. The life expectancy at birth may be low due to the high childhood mortality so that once a person survives his/her childhood, he/she may live much longer than 50 years.","theme":"sante","source_group":"wb"},{"code":"SP.DYN.LE00.MA.IN","name":"Espérance de vie à la naissance, hommes (années)","description":"L'espérance de vie à la naissance indique le nombre d'années qu'un nouveau-né vivrait si les schémas de mortalité dominants au moment de sa naissan...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.LE00.MA.IN?locations=CI","methodology":"Methodology: Life expectancy at birth is derived from life tables and is based on sex- and age-specific death rates.\nStatistical concept(s): Life expectancy at birth used here is the average number of years a newborn is expected to live if mortality patterns at the time of its birth remain constant in the future. It reflects the overall mortality level of a population, and summarizes the mortality pattern that prevails across all age groups in a given year. It is calculated in a period life table which provides a snapshot of a population's mortality pattern at a given time. It therefore does not reflect the mortality pattern that a person actually experiences during his/her life, which can be calculated in a cohort life table.\nHigh mortality in young age groups significantly lowers the life expectancy at birth. But if a person survives his/her childhood of high mortality, he/she may live much longer. For example, in a population with a life expectancy at birth of 50, there may be few people dying at age 50. The life expectancy at birth may be low due to the high childhood mortality so that once a person survives his/her childhood, he/she may live much longer than 50 years.","theme":"sante","source_group":"wb"},{"code":"SP.DYN.LE00.IN","name":"Espérance de vie à la naissance, total (années)","description":"L'espérance de vie à la naissance indique le nombre d'années qu'un nouveau-né vivrait si les schémas de mortalité dominants au moment de sa naissan...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.LE00.IN?locations=CI","methodology":"Methodology: Life expectancy at birth is derived from life tables and is based on sex- and age-specific death rates, or derived from male and female life expectancy at birth.\nStatistical concept(s): Life expectancy at birth used here is the average number of years a newborn is expected to live if mortality patterns at the time of its birth remain constant in the future. It reflects the overall mortality level of a population, and summarizes the mortality pattern that prevails across all age groups in a given year. It is calculated in a period life table which provides a snapshot of a population's mortality pattern at a given time. It therefore does not reflect the mortality pattern that a person actually experiences during his/her life, which can be calculated in a cohort life table.\nHigh mortality in young age groups significantly lowers the life expectancy at birth. But if a person survives his/her childhood of high mortality, he/she may live much longer. For example, in a population with a life expectancy at birth of 50, there may be few people dying at age 50. The life expectancy at birth may be low due to the high childhood mortality so that once a person survives his/her childhood, he/she may live much longer than 50 years.","theme":"sante","source_group":"wb"},{"code":"SH.MMR.RISK.ZS","name":"Risque de décès maternel au cours de la vie ( %)","description":"Le risque de décès maternel au cours de la vie est la probabilité qu’une jeune femme de 15 ans finisse par mourir d’une cause maternelle, en suppos...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.MMR.RISK.ZS?locations=CI","methodology":"Methodology: The estimates are based on an exercise by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) which consists of World Health Organization (WHO), United Nations Children's Fund (UNICEF), World Bank, and United Nations Population Fund (UNFPA), and include country-level time series data. For countries without complete registration data but with other types of data and for countries with no data, maternal mortality is estimated with a regression model using available national maternal mortality data and socioeconomic information.\nStatistical concept(s): Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\nMaternal mortality is generally of unknown reliability, as are many other cause-specific mortality indicators. Household surveys such as Demographic and Health Surveys attempt to measure maternal mortality by asking respondents about survivorship of sisters. The main disadvantage of this method is that the estimates of maternal mortality that it produces pertain to any time within the past few years before the survey, making them unsuitable for monitoring recent changes or observing the impact of interventions. In addition, measurement of maternal mortality is subject to many types of errors. Even in high-income countries with reliable vital registration systems, misclassification of maternal deaths has been found to lead to serious underestimation.","theme":"sante","source_group":"wb"},{"code":"SH.MMR.RISK","name":"Risque de décès maternel au cours de la vie (1 sur : le taux varie selon les pays)","description":"Le risque de décès maternel au cours de la vie est la probabilité qu’une jeune femme de 15 ans finisse par mourir d’une cause maternelle, en suppos...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.MMR.RISK?locations=CI","methodology":"Methodology: The estimates are based on an exercise by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) which consists of World Health Organization (WHO), United Nations Children's Fund (UNICEF), World Bank, and United Nations Population Fund (UNFPA), and include country-level time series data. For countries without complete registration data but with other types of data and for countries with no data, maternal mortality is estimated with a regression model using available national maternal mortality data and socioeconomic information.\nStatistical concept(s): Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\nMaternal mortality is generally of unknown reliability, as are many other cause-specific mortality indicators. Household surveys such as Demographic and Health Surveys attempt to measure maternal mortality by asking respondents about survivorship of sisters. The main disadvantage of this method is that the estimates of maternal mortality that it produces pertain to any time within the past few years before the survey, making them unsuitable for monitoring recent changes or observing the impact of interventions. In addition, measurement of maternal mortality is subject to many types of errors. Even in high-income countries with reliable vital registration systems, misclassification of maternal deaths has been found to lead to serious underestimation.","theme":"sante","source_group":"wb"},{"code":"IS.SHP.GCNW.XQ","name":"Indice de connectivité du transport maritime de ligne (valeur maximale en 2004 = 100)","description":"L’indice de connectivité des transports maritimes réguliers mesure dans quelle mesure les pays sont connectés aux réseaux maritimes mondiaux.","source_link":"https://donnees.banquemondiale.org/indicateur/IS.SHP.GCNW.XQ?locations=CI","methodology":"Methodology: The Liner Shipping Connectivity Index captures how well countries are connected to global shipping networks. Starting in 2020 the index was improved and is published as a quarterly series with the index set at 100 for the country with the highest average in the first quarter of 2006. It is computed by the United Nations Conference on Trade and Development (UNCTAD) based on six components of the maritime transport sector: number of ships, their container-carrying capacity, maximum vessel size, number of services, the number of country-pairs with a direct connection, and number of companies that deploy container ships in a country's ports. The data are derived from Containerisation International Online (www.ci-online.co.uk). For each of the six components, a country's value is divided by the maximum value of that component in Q1 2006, and for each country, the average of the six components is calculated. This average is then divided by the maximum average for Q1 2006 and multiplied by 100. In this way, the index generates the value 100 for the country with the highest average index of the six components in Q1 2006. Annual values of the index equal the values of the first quarter of the same corresponding year.","theme":"territory","source_group":"wb"},{"code":"CM.MKT.LDOM.NO","name":"Sociétés nationales cotées, total","description":"Les sociétés nationales cotées, y compris les sociétés étrangères exclusivement cotées, sont celles dont les actions sont cotées en bourse à la fin...","source_link":"https://donnees.banquemondiale.org/indicateur/CM.MKT.LDOM.NO?locations=CI","methodology":"Methodology: A company is considered domestic when it is incorporated in the same country as where the exchange is located. The only exception is the case of foreign companies which are exclusively listed on an exchange (i.e., the foreign company is not listed on any other exchange as defined in the domestic market capitalization definition).\nStatistical concept(s):  A company is considered domestic when it is incorporated in the same country as where the exchange is located. The only exception is the case of foreign companies which are exclusively listed on an exchange (i.e., the foreign company is not listed on any other exchange as defined in the domestic market capitalization definition).","theme":"business","source_group":"wb"},{"code":"SE.ADT.LITR.FE.ZS","name":"Taux d'alphabétisation, femmes adultes ( % des femmes âgées de 15 ans et plus)","description":"Le taux d'alphabétisation des adultes est le pourcentage de personnes âgées de 15 ans et plus qui peuvent à la fois lire et écrire en comprenant un...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.ADT.LITR.FE.ZS?locations=CI","methodology":"Methodology: The indicator is calculated by the number of literate adults divided by the total number of adults, excluding adults with unknown literacy status.  \n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.\nStatistical concept(s): Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.","theme":"education","source_group":"wb"},{"code":"SE.ADT.LITR.MA.ZS","name":"Taux d'alphabétisation, hommes adultes ( % des hommes âgés de 15 ans et plus)","description":"Le taux d'alphabétisation des adultes est le pourcentage de personnes âgées de 15 ans et plus qui peuvent à la fois lire et écrire en comprenant un...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.ADT.LITR.MA.ZS?locations=CI","methodology":"Methodology: The indicator is calculated by the number of literate adults divided by the total number of adults, excluding adults with unknown literacy status.  \n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.\nStatistical concept(s): Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.","theme":"education","source_group":"wb"},{"code":"SE.ADT.LITR.ZS","name":"Taux d'alphabétisation, total des adultes ( % des personnes âgées de 15 ans et plus)","description":"Le taux d'alphabétisation des adultes est le pourcentage de personnes âgées de 15 ans et plus qui peuvent à la fois lire et écrire en comprenant un...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.ADT.LITR.ZS?locations=CI","methodology":"Methodology: The indicator is calculated by the number of literate adults divided by the total number of adults, excluding adults with unknown literacy status.  \n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.\nStatistical concept(s): Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.","theme":"education","source_group":"wb"},{"code":"SE.ADT.1524.LT.FM.ZS","name":"Taux d'alphabétisation, jeunes (15-24 ans), indice de parité hommes-femmes (IPS)","description":"L'indice de parité entre les sexes pour le taux d'alphabétisation des jeunes est le rapport entre les femmes et les hommes âgés de 15 à 24 ans, cap...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.ADT.1524.LT.FM.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by dividing female youth literacy rate by male youth literacy rate. \nLiteracy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.\nStatistical concept(s): The Gender Parity Index (GPI) indicates parity between girls and boys. A GPI of less than 1 suggests girls are more disadvantaged than boys in learning opportunities and a GPI of greater than 1 suggests the other way around.   Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.","theme":"education","source_group":"wb"},{"code":"SE.ADT.1524.LT.FE.ZS","name":"Taux d'alphabétisation, jeunes femmes ( % des femmes âgées de 15 à 24 ans)","description":"Le taux d'alphabétisation des jeunes est le pourcentage de personnes âgées de 15 à 24 ans qui peuvent à la fois lire et écrire en comprenant une dé...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.ADT.1524.LT.FE.ZS?locations=CI","methodology":"Methodology: The indicator is calculated by the number of literate youths divided by the total number of youths, excluding youths with unknown literacy status.  \n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.\nStatistical concept(s): Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.","theme":"education","source_group":"wb"},{"code":"SE.ADT.1524.LT.MA.ZS","name":"Taux d'alphabétisation, jeunes hommes ( % des hommes âgés de 15 à 24 ans)","description":"Le taux d'alphabétisation des jeunes est le pourcentage de personnes âgées de 15 à 24 ans qui peuvent à la fois lire et écrire en comprenant une dé...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.ADT.1524.LT.MA.ZS?locations=CI","methodology":"Methodology: The indicator is calculated by the number of literate youths divided by the total number of youths, excluding youths with unknown literacy status.  \n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.\nStatistical concept(s): Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.","theme":"education","source_group":"wb"},{"code":"SE.ADT.1524.LT.ZS","name":"Taux d'alphabétisation, total des jeunes ( % de la population âgée de 15 à 24 ans)","description":"Le taux d'alphabétisation des jeunes est le pourcentage de personnes âgées de 15 à 24 ans qui peuvent à la fois lire et écrire en comprenant une dé...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.ADT.1524.LT.ZS?locations=CI","methodology":"Methodology: The data is calculated by dividing the number of literate persons by the total number of persons in the same age group, excluding persons with unknown literacy status.\n\nData on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.\nStatistical concept(s): Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.","theme":"education","source_group":"wb"},{"code":"AG.PRD.LVSK.XD","name":"Indice de la production animale (2014-2016 = 100)","description":"L'indice de la production animale comprend la viande et le lait de toutes origines, les produits laitiers tels que le fromage et les œufs, le miel,...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.PRD.LVSK.XD?locations=CI","methodology":"Methodology: The agricultural production index is prepared by the Food and Agriculture Organization of the United Nations (FAO). The FAO indices of agricultural production show the relative level of the aggregate volume of agricultural production for each year in comparison with the base period 2014-2016. They are based on the sum of price-weighted quantities of different agricultural commodities produced after deductions of quantities used as seed and feed weighted in a similar manner. The resulting aggregate represents, therefore, disposable production for any use except as seed and feed. All the indices at the country, regional and world levels are calculated by the Laspeyres formula*. Production quantities of each commodity are weighted by 2014-2016 average international commodity prices and summed for each year. To obtain the index, the aggregate for a given year is divided by the average aggregate for the base period 2014-2016. Since the FAO indices are based on the concept of agriculture as a single enterprise, amounts of seed and feed are subtracted from the production data to avoid double counting, once in the production data and once with the crops or livestock produced from them. Deductions for seed (in the case of eggs, for hatching) and for livestock and poultry feed apply to both domestically produced and imported commodities. They cover only primary agricultural products destined to animal feed (e.g. maize, potatoes, milk, etc.). Processed and semi-processed feed items such as bran, oilcakes, meals and molasses have been completely excluded from the calculations at all stages. It should be noted that when calculating indices of agricultural, food and nonfood production, all intermediate primary inputs of agricultural origin are deducted. However, for indices of any other commodity group, only inputs originating from within the same group are deducted; thus, only seed is removed from the group \"crops\" and from all crop subgroups, such as cereals, oil crops, etc.; and both feed and seed originating from within the livestock sector (e.g. milk feed, hatching eggs) are removed from the group \"livestock products\". For the main two livestock subgroups, namely, meat and milk, only feed originating from the respective subgroup is removed. Indices which take into account deductions for feed and seed are referred to as ''net''. Indices calculated without any deductions for feed and seed are referred to as ''gross\". The \"international commodity prices\" are used in order to avoid the use of exchange rates for obtaining continental and world aggregates, and also to improve and facilitate international comparative analysis of productivity at the national level. These\" international prices,\" expressed in so-called \"international dollars,\" are derived using a Geary-Khamis formula** for the agricultural sector. This method assigns a single \"price\" to each commodity. For example, one metric ton of wheat has the same price regardless of the country where it was produced. The currency unit in which the prices are expressed has no influence on the indices published. The commodities covered in the computation of indices of agricultural production are all crops and livestock products originating in each country. Practically all products are covered, with the main exception of fodder crops. \n\n\n\n\n\n\n\n\n\n\n\n* A Laspeyres Index is known as a \"base-weighted\" or \"fixed-weighted\" index because the price increases are weighted by the quantities in the base period. The Consumer Price Index is an example of a Laspeyres Index. http://www.usna.edu/Users/econ/rbrady/312%20Materials/LaspeyresCalc.pdf\n\n\n\n\n\n** Geary-Khamis formula is an aggregation method in which category \"international prices\" (reflecting relative category values) and country purchasing power parities (PPPs), (depicting relative country price levels) are estimated simultaneously from a system of linear equations. http://stats.oecd.org/glossary/detail.asp?ID=5528\nStatistical concept(s):","theme":"primary","source_group":"wb"},{"code":"LP.LPI.TRAC.XQ","name":"Indice de performance logistique : capacité à suivre et à tracer les envois (1 = faible à 5 = élevé)","description":"Les données proviennent de l'enquête Logistics Performance Index menée par la Banque mondiale en partenariat avec des institutions universitaires e...","source_link":"https://donnees.banquemondiale.org/indicateur/LP.LPI.TRAC.XQ?locations=CI","methodology":"Methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics.  The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5.  The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets.  The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions.  \nStatistical concept(s): The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.","theme":"inter","source_group":"wb"},{"code":"LP.LPI.LOGS.XQ","name":"Indice de performance logistique : Compétence et qualité des services logistiques (1 = faible à 5 = élevé)","description":"Les données proviennent de l'enquête Logistics Performance Index menée par la Banque mondiale en partenariat avec des institutions universitaires e...","source_link":"https://donnees.banquemondiale.org/indicateur/LP.LPI.LOGS.XQ?locations=CI","methodology":"Methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics.  The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5.  The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets.  The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions.  \nStatistical concept(s): The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.","theme":"inter","source_group":"wb"},{"code":"LP.LPI.ITRN.XQ","name":"Indice de performance logistique : Facilité d'organisation d'expéditions à des prix compétitifs (1 = faible à 5 = élevé)","description":"Les données proviennent de l'enquête Logistics Performance Index menée par la Banque mondiale en partenariat avec des institutions universitaires e...","source_link":"https://donnees.banquemondiale.org/indicateur/LP.LPI.ITRN.XQ?locations=CI","methodology":"Methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics.  The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5.  The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets.  The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions.  \nStatistical concept(s): The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.","theme":"inter","source_group":"wb"},{"code":"LP.LPI.CUST.XQ","name":"Indice de performance logistique : Efficacité du processus de dédouanement (1 = faible à 5 = élevé)","description":"Les données proviennent de l'enquête Logistics Performance Index menée par la Banque mondiale en partenariat avec des institutions universitaires e...","source_link":"https://donnees.banquemondiale.org/indicateur/LP.LPI.CUST.XQ?locations=CI","methodology":"Methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics.  The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5.  The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets.  The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions.  \nStatistical concept(s): The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.","theme":"inter","source_group":"wb"},{"code":"LP.LPI.TIME.XQ","name":"Indice de performance logistique : Fréquence à laquelle les expéditions parviennent au destinataire dans les délais prévus ou prévus (1 = faible à 5 = élevée)","description":"Les données proviennent de l'enquête Logistics Performance Index menée par la Banque mondiale en partenariat avec des institutions universitaires e...","source_link":"https://donnees.banquemondiale.org/indicateur/LP.LPI.TIME.XQ?locations=CI","methodology":"Methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics.  The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5.  The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets.  The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions.  \nStatistical concept(s): The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.","theme":"inter","source_group":"wb"},{"code":"LP.LPI.OVRL.XQ","name":"Indice de performance logistique : Globalement (1 = faible à 5 = élevé)","description":"Le score global de l'indice de performance logistique reflète les perceptions de la logistique d'un pays sur la base de l'efficacité du processus d...","source_link":"https://donnees.banquemondiale.org/indicateur/LP.LPI.OVRL.XQ?locations=CI","methodology":"Methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics.  The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5.  The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets.  The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions.  \nStatistical concept(s): The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.","theme":"inter","source_group":"wb"},{"code":"LP.LPI.INFR.XQ","name":"Indice de performance logistique : qualité des infrastructures liées au commerce et aux transports (1 = faible à 5 = élevée)","description":"Les données proviennent de l'enquête Logistics Performance Index menée par la Banque mondiale en partenariat avec des institutions universitaires e...","source_link":"https://donnees.banquemondiale.org/indicateur/LP.LPI.INFR.XQ?locations=CI","methodology":"Methodology: The indicator presents data from Logistics Performance Surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics.  The Logistics Performance Index (LPI) uses a structured online survey of logistics professionals at multinational freight forwarders and the main express carriers. The 2023 International LPI covers 139 countries. Each survey respondent rates eight overseas markets on six core components of logistics performance (the efficiency of customs and border management clearance, the quality of trade and transport infrastructure, the ease of arranging competitively priced shipments, the competence and quality of logistics services, the ability to track and trace consignments, and the frequency shipments reach consignees within scheduled or expected delivery times). The components are rated on a scale (lowest score to highest score) from 1 to 5.  The eight countries are chosen based on the most important export and import markets of the country where the respondent is located, on random selection, and - for landlocked countries - on neighboring countries that form part of the land bridge connecting them with international markets.  The method used to select the group of countries rated by each respondent varies by the characteristics of the country where the respondent is located. If respondents did not provide information for all six components, interpolation is used to fill in missing values. The missing values are replaced with the country mean response for each question, adjusted by the respondent's average deviation from the country mean in the answered questions.  \nStatistical concept(s): The LPI is constructed from the six indicators using principal component analysis (PCA), a standard statistical technique used to reduce the dimensionality of a dataset. In the LPI, the inputs for PCA are country scores the questions covering the main six components, averaged across all respondents providing data on a given overseas market. Scores are normalized by subtracting the sample mean and dividing by the standard deviation before conducting PCA. The output from PCA is a single indicator - the LPI - that is a weighted average of those scores. The weights are chosen to maximize the percentage of variation in the LPI's original six indicators. To construct the international LPI, normalized scores for each of the six original indicators are multiplied by their component loadings and then summed. The component loadings represent the weight given to each original indicator in constructing the international LPI. Since the loadings are similar for all six, the international LPI is close to a simple average of the indicators. To account for the sampling error created by the LPI's survey-based dataset, LPI scores are presented with approximate 80 percent confidence intervals.","theme":"inter","source_group":"wb"},{"code":"SH.STA.BRTW.ZS","name":"Bébés de faible poids à la naissance ( % des naissances)","description":"Les bébés ayant un faible poids à la naissance sont des nouveau-nés pesant moins de 2 500 grammes et dont la mesure est prise dans la première heur...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.BRTW.ZS?locations=CI","methodology":"Methodology: Household Surveys including DHS, MICS and other national surveys\nStatistical concept(s): Low birthweight babies are more likely to die during their first month of life and those who survived face lifelong consequences including a higher risk of stunted growth, lower IQ ,and adult-onset chronic conditions such as obesity and diabetes.","theme":"sante","source_group":"wb"},{"code":"SE.SEC.CMPT.LO.FE.ZS","name":"Taux d'achèvement du premier cycle de l'enseignement secondaire, filles ( % de la tranche d'âge concernée)","description":"Le taux d’achèvement du premier cycle du secondaire est mesuré comme le taux brut d’admission à la dernière année du premier cycle du secondaire (g...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.CMPT.LO.FE.ZS?locations=CI","methodology":"Methodology: Lower secondary completion rate is calculated as the number of new entrants (enrollment minus repeaters) in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The indicator represents the influence of policies regarding entry and progress through the initial stages of primary or lower secondary education on the completion of the terminal grade at the respective level. The presumption is that students who enroll in the final grade for the first time will successfully finish that grade, thereby completing the designated level of education.","theme":"education","source_group":"wb"},{"code":"SE.SEC.CMPT.LO.MA.ZS","name":"Taux d'achèvement du premier cycle de l'enseignement secondaire, hommes ( % de la tranche d'âge concernée)","description":"Le taux d’achèvement du premier cycle du secondaire est mesuré comme le taux brut d’admission à la dernière année du premier cycle du secondaire (g...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.CMPT.LO.MA.ZS?locations=CI","methodology":"Methodology: Lower secondary completion rate is calculated as the number of new entrants (enrollment minus repeaters) in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The indicator represents the influence of policies regarding entry and progress through the initial stages of primary or lower secondary education on the completion of the terminal grade at the respective level. The presumption is that students who enroll in the final grade for the first time will successfully finish that grade, thereby completing the designated level of education.","theme":"education","source_group":"wb"},{"code":"SE.SEC.CMPT.LO.ZS","name":"Taux d'achèvement du premier cycle de l'enseignement secondaire, total ( % de la tranche d'âge concernée)","description":"Le taux d’achèvement du premier cycle du secondaire est mesuré comme le taux brut d’admission à la dernière année du premier cycle du secondaire (g...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.CMPT.LO.ZS?locations=CI","methodology":"Methodology: Lower secondary completion rate is calculated as the number of new entrants (enrollment minus repeaters) in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The indicator represents the influence of policies regarding entry and progress through the initial stages of primary or lower secondary education on the completion of the terminal grade at the respective level. The presumption is that students who enroll in the final grade for the first time will successfully finish that grade, thereby completing the designated level of education.","theme":"education","source_group":"wb"},{"code":"SE.SEC.AGES","name":"Âge d'entrée à l'école secondaire I (années)","description":"L’âge d’entrée au premier cycle du secondaire est l’âge auquel les élèves entreraient dans le premier cycle du secondaire, en supposant qu’ils aien...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.AGES?locations=CI","methodology":"Methodology: Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator provides insights into the demand for educational services across various educational levels. Additionally, it serves as a crucial data point necessary for the generation of numerous educational indicators.","theme":"education","source_group":"wb"},{"code":"NV.MNF.MTRN.ZS.UN","name":"Machines et matériel de transport ( % de la valeur ajoutée dans l'industrie manufacturière)","description":"La fabrication de machines et de matériel de transport comprend les industries classées dans les divisions 29 à 35 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.MNF.MTRN.ZS.UN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"SE.LPV.PRIM.SD.MA","name":"Enfants de sexe masculin en âge de fréquenter l'école primaire non scolarisés ( %)","description":"La proportion d’enfants de sexe masculin en âge d’aller à l’école primaire qui ne sont pas scolarisés ou qui sont privés de scolarité.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.LPV.PRIM.SD.MA?locations=CI","methodology":"Methodology: Schooling Deprivation is derived using enrollment rates computed by UIS using administrative records and follows the SDG 4.1.4 indicator. To ensure country coverage of data, we consider other enrollment definitions to use for learning poverty, if the first-best option is not available. \nWe construct an enrollment dataset from 1990 to the year of the current release, relying on multiple enrollment definitions. Our dataset is constructed from UIS (UNESCO Institute of Statistics), and other sources suggested by World Bank regional or country education specialists. Data sources are typically from administrative records (school registers or school censuses) for data on enrolment by age, and UNPD population estimates for school-age population (UIS). Enrolment by single years of age in all levels of education and the total primary-school-age population are used to compute enrollment rates.\nWe follow this hierarchy of enrollment definitions: Country specialist validated data > Adjusted Net Enrollment Rate (ANER) > Total Net Enrollment Rate (TNER) > Net enrollment rate (NER) > Gross Enrollment Rate (GER; if the gross enrollment rate is higher than 100%, it is adjusted to be 100%).\nOur preferred measure of school participation is ANER, because it accounts for some primary school aged children who might enter primary school early and advance to secondary school before they reach the official upper age limit of primary education. Adjusted net enrollment is a measure of both “stock” and “flow” and accounts for both age- and grade-based distortions, as it is the percent of primary school age children enrolled either in primary or secondary education, as opposed to gross enrollment which is the share of children of any age that are enrolled in primary school, or net enrollment which is the share of primary school age children that are enrolled in primary school. The next-best indicator is used if ANER is unavailable. In some cases, country specialists will provide a data point that reflects enrollment in the country better than UIS statistics which is used. In future Learning Poverty releases, the enrollment hierarchy may be adjusted as availability of indicator definitions change. \n\n\nThe enrollment year used is the one that best pairs with the assessment year used to compute Learning Deprivation. The year of the preferred assessment is the base. If the same enrollment year is not available, we use a step function to fill the data in with the value of the closest year. If there is data available for two years equally close to the year to fill, the older value is used. This procedure to extrapolate enrollment for missing values is required for us to pair the proficiency measure with enrollment measures from the same year, or its best proxy when enrollment is not available for the same year of the assessment.\nStatistical concept(s): Minimum Proficiency Level (MPL) in Reading","theme":"education","source_group":"wb"},{"code":"SE.LPV.PRIM.LD.MA","name":"Élèves de sexe masculin n'ayant pas les compétences minimales en lecture à la fin de l'enseignement primaire ( %). Seuil GAML bas","description":"La proportion d'élèves de sexe masculin à la fin de l'école primaire qui sont en dessous du niveau minimum de compétence (MPL) en lecture ou en app...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.LPV.PRIM.LD.MA?locations=CI","methodology":"Methodology: Learning assessments used to calculate Learning Poverty have a minimum proficiency level (MPL) benchmarked by Global Alliance to Monitor Learning (GAML) under the leadership of the UNESCO Institute of Statistics (UIS), which occurred within the reporting window. To operationalize this concept, the current SDG monitoring process is followed by defining “proficiency” as reaching at least the Low International Benchmark on the international PIRLS literacy assessment. \nPIRLS is the major global primary-age assessment focused on reading, and if all countries participated in it, the task of constructing global estimates of minimum proficiency would be trivial, as it would require aggregating results from a single cross-national assessment. However, most countries participating in PIRLS are high-income, and only a small minority of low- and middle-income countries participate in the assessment. One of the main contributions of the GAML process is that it has overcome this data gap by benchmarking several major cross-national assessments—and increasingly national learning assessments as well—against the standard. \nThe MPL for each learning assessment is used to calculate the reading proficiency rate for that country, which is the share of students scoring at or above the minimum proficiency level, and conversely to calculate the learning deprivation.\nThe Proficiency and Grade Levels used for each assessment is as follows: PIRLS (grade 4) - Level 2 (Low international benchmark, 400 points); TIMSS (grade 4) - Level 2 (Low international benchmark, 400 points); LLECE (SERCE, grade 6) - Level 3 (513.66 points); PASEC (grades 5 and 6) - Level 4 (595.1 points); SEA-PLM (grade 5) - Level 6 and above; National Learning Assessment (grade 4, 5 and 6) - Varies by country. \nWhen a given country had administered multiple types of learning assessments, a hierarchy is applied in the order listed below to ensure best comparability across countries: International or Regional Learning Assessment for Reading (PIRLS, LLECE, PASEC, SEA-PLM) > TIMSS Science > Statistical or Pairwise Linking Exercises > AMPL-bs, Policy Linked National Learning Assessments or Policy Linked Service Delivery Indicators (SDIs) > Non-Policy Linked NLAs (Interim Reporting).\nNote that as the GAML and joint coalitions continue their efforts to improve learning data coverage, the hierarchy may be revised.\nStatistical concept(s): Minimum Proficiency Level (MPL) in Reading","theme":"education","source_group":"wb"},{"code":"EN.MAM.THRD.NO","name":"Espèces de mammifères menacées","description":"Les espèces de mammifères sont des mammifères à l'exclusion des baleines et des marsouins.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.MAM.THRD.NO?locations=CI","methodology":"Methodology: Species assessed as Critically Endangered (CR), Endangered (EN) or Vulnerable (VU) are referred to as \"threatened\" species. The International Union for Conservation of Nature (IUCN) Red List of Threatened Species collects and disseminates information on the global threated species.\nProportion of threatened species is only reported for the more completely evaluated groups (i.e., >90% of species evaluated). Also, the reported percentage of threatened species for each group is presented as a best estimate within a range of possible values bounded by lower and upper estimates:\nLower estimate = % threatened extant species if all Data Deficient species are not threatened, i.e., (CR + EN + VU) / (total assessed - EX)\nBest estimate = % threatened extant species if Data Deficient species are equally threatened as data sufficient species, i.e., (CR + EN + VU) / (total assessed - EX - DD)\nUpper estimate = % threatened extant species if all Data Deficient species are threatened, i.e., (CR + EN + VU + DD) / (total assessed - EX)\nAdditional information on ecology and habitat preferences, threats, and conservation action are also collated and assessed as part of Red List process.\nStatistical concept(s):","theme":"territory","source_group":"wb"},{"code":"IC.MNG.IND","name":"Indice des pratiques de gestion","description":"Indice composite qui combine les informations de huit indicateurs de pratiques de gestion inclus dans le questionnaire des enquêtes auprès des entr...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.MNG.IND?locations=CI","methodology":"The Management Practices Index is a composite index that combines information from eight management practices indicators included in the Enterprise Surveys questionnaire. \n\nThe detailed methodology is available in the Enterprise Surveys Indicator Description document: https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Indicator-Description.pdf\n\nThe World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.\n\nSince 2005-2006, the WBES implemented by the Enterprise Analysis Unit follow the Global Methodology. Earlier datasets from differing survey instruments have been matched to a standard instrument for dissemination on the website and data portal. Note that data users should exercise caution when comparing raw data and point estimates between surveys that did and surveys that did not adhere to the WBES Global Methodology.\n\nPrivate contractors conduct the WBES on behalf of the World Bank. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but anonymity is never compromised. The mode of data collection is face-to-face interviews (in-person or virtual).\n\nThe WBES is answered by business owners and top managers. The survey respondents might sometimes involve accountants and human resource managers to answer some questions.\n•\tFirms classified with ISIC Rev. 4 codes 10-33, 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95. These are firms in manufacturing, construction, retail, wholesale, hotels, restaurants, transport, storage, communications, professional services, and IT.*\n•\tFormal (registered) companies with five or more workers.\n•\tFirms that have at least 1% of private ownership.\n\nOccasionally, for a few economies, other sectors are included, such as education or health.\n\n(Starting from August 2022, the WBES uses ISIC Rev. 4 (instead of Rev.3.1) for categorizing business activity.  Henceforth, businesses under Section M of ISIC Rev. 4, i.e., professional, scientific, and technical activities, became eligible to participate.)\n\nThe standard WBES questionnaire covers over 15 topics, including firm characteristics, gender participation, access to finance, annual sales, among others. See the questionnaire here.\nOver 90% of the questions are fact-based, while the remaining 10% assess the respondents’ opinions on obstacles to their firm’s growth and performance.\n\nThe WBES uses stratified random sampling, with the following strata:\n•\tfirm size, most frequently: small (5-19 workers), medium (20-99), and large (100+)\n•\tbusiness sector\n•\tgeographic region within an economy\n\nIdeally, the survey sample frame is derived from the universe of eligible firms obtained from the economy’s statistical office. Sometimes the master list of firms is obtained from other government agencies such as tax or business licensing authorities. In some cases, the list of firms is obtained from business associations or marketing databases. In a few cases, the sample frame is created via block enumeration, where the World Bank “manually” constructs a list of eligible firms after 1) partitioning an economy’s cities of major economic activity into clusters and blocks, and 2) randomly selecting a subset of blocks which will then be enumerated. Since 2005-06, the publicly available survey documentation details the source of the sample frame.\n\nThe WBES also provides panel data, i.e., interviews with the same firms across multiple years. When conducting a new WBES, maximal effort is expended to re-interview at least half of the firms from the prior WBES. For these panel firms, sampling weights are adjusted to consider the resulting altered probabilities of inclusion in the sample frame.","theme":"business","source_group":"wb"},{"code":"TX.VAL.MANF.ZS.UN","name":"Exportations de produits manufacturés ( % des exportations de marchandises)","description":"Les produits manufacturés comprennent les produits des sections 5 (produits chimiques), 6 (produits manufacturés de base), 7 (machines et matériel ...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MANF.ZS.UN?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MANF.ZS.UN","name":"Importations de produits manufacturés ( % des importations de marchandises)","description":"Les produits manufacturés comprennent les produits des sections 5 (produits chimiques), 6 (produits manufacturés de base), 7 (machines et matériel ...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MANF.ZS.UN?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"NV.IND.MANF.ZS","name":"Industrie manufacturière, valeur ajoutée (en % du PIB)","description":"L'industrie manufacturière comprend les industries classées dans la grande division C de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.MANF.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"NV.IND.MANF.KD.ZG","name":"Industrie manufacturière, valeur ajoutée (croissance annuelle en %)","description":"L'industrie manufacturière comprend les industries classées dans la grande division C de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.MANF.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"NV.IND.MANF.KD","name":"Industrie manufacturière, valeur ajoutée (en dollars constants de 2015)","description":"L'industrie manufacturière comprend les industries classées dans la grande division C de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.MANF.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"NV.IND.MANF.KN","name":"Fabrication, valeur ajoutée (UCL constantes)","description":"L'industrie manufacturière comprend les industries classées dans la grande division C de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.MANF.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"NV.IND.MANF.CN","name":"Fabrication, valeur ajoutée (LCU actuelle)","description":"L'industrie manufacturière comprend les industries classées dans la grande division C de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.MANF.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"NV.IND.MANF.CD","name":"Industrie manufacturière, valeur ajoutée (en dollars américains courants)","description":"L'industrie manufacturière comprend les industries classées dans la grande division C de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.IND.MANF.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"ER.MRN.PTMR.ZS","name":"Aires marines protégées ( % des eaux territoriales)","description":"Les zones marines protégées sont des zones de terrain intertidal ou subtidal - ainsi que les eaux sus-jacentes, la flore, la faune et les caractéri...","source_link":"https://donnees.banquemondiale.org/indicateur/ER.MRN.PTMR.ZS?locations=CI","methodology":"Methodology: This indicator is calculated using all the nationally designated protected areas recorded in the World Database on Protected Areas (WDPA) whose location and extent is known. The WDPA database is stored within a Geographic Information System (GIS) that stores information about protected areas such as their name, type and date of designation, documented area, geographic location (point) and/or boundary (polygon). \nDesignating an area as protected does not mean that protection is in force. And for small countries that have only protected areas smaller than 1,000 hectares, the size limit in the definition leads to an underestimate of protected areas. Nationally protected areas are defined using the six IUCN management categories for areas of at least 1,000 hectares: scientific reserves and strict nature reserves with limited public access; national parks of national or international significance and not materially affected by human activity; natural monuments and natural landscapes with unique aspects; managed nature reserves and wildlife sanctuaries; protected landscapes (which may include cultural landscapes); and areas managed mainly for the sustainable use of natural systems to ensure long-term protection and maintenance of biological diversity.\n\n\n\n\n\n\n\n\n\n\n\nA GIS analysis is used to calculate terrestrial and marine protection. For this a global protected area layer is created by combining the polygons and points recorded in the WDPA. Circular buffers are created around points based on the known extent of protected areas for which no polygon is available. Annual protected area layers are created by dissolving the global protected area layer by the known year of establishment of protected areas recorded in the WDPA. The annual protected area layers are overlaid with country/territory boundaries, coastlines and buffered coastlines (delineating the territorial waters) to obtain the absolute coverage (in square kilometers) of protected areas by country/territory per year from 1990 to present. The total area of a country's/territory's terrestrial protected areas and marine protected areas in territorial waters is divided by the total area of its land areas (including inland waters) and territorial waters to obtain the relative coverage (percentage) of protected areas.\nStatistical concept(s):","theme":"territory","source_group":"wb"},{"code":"CM.MKT.LCAP.GD.ZS","name":"Capitalisation boursière des sociétés nationales cotées ( % du PIB)","description":"La capitalisation boursière (également connue sous le nom de valeur marchande) correspond au cours de l'action multiplié par le nombre d'actions en...","source_link":"https://donnees.banquemondiale.org/indicateur/CM.MKT.LCAP.GD.ZS?locations=CI","methodology":"Methodology: Market capitalization figures include: shares of listed domestic companies; shares of foreign companies which are exclusively listed on an exchange (i.e., the foreign company is not listed on any other exchange); common and preferred shares of domestic companies; and shares without voting rights. Market capitalization figures exclude: collective investment funds ; rights, warrants, ETFs, convertible instruments ; options, futures ; foreign listed shares other than exclusively listed ones; companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status; and companies admitted to trading (i.e., companies whose shares are traded at the exchange but not listed at the exchange).\nStatistical concept(s):  Market capitalization figures include: shares of listed domestic companies; shares of foreign companies which are exclusively listed on an exchange (i.e., the foreign company is not listed on any other exchange); common and preferred shares of domestic companies; and shares without voting rights. Market capitalization figures exclude: collective investment funds ; rights, warrants, ETFs, convertible instruments ; options, futures ; foreign listed shares other than exclusively listed ones; companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status; and companies admitted to trading (i.e., companies whose shares are traded at the exchange but not listed at the exchange).","theme":"business","source_group":"wb"},{"code":"CM.MKT.LCAP.CD","name":"Capitalisation boursière des sociétés nationales cotées en bourse ($ US courants)","description":"La capitalisation boursière (également connue sous le nom de valeur marchande) correspond au cours de l'action multiplié par le nombre d'actions en...","source_link":"https://donnees.banquemondiale.org/indicateur/CM.MKT.LCAP.CD?locations=CI","methodology":"Methodology: Market capitalization figures include: shares of listed domestic companies; shares of foreign companies which are exclusively listed on an exchange (i.e., the foreign company is not listed on any other exchange); common and preferred shares of domestic companies; and shares without voting rights. Market capitalization figures exclude: collective investment funds ; rights, warrants, ETFs, convertible instruments ; options, futures ; foreign listed shares other than exclusively listed ones; companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status; and companies admitted to trading (i.e., companies whose shares are traded at the exchange but not listed at the exchange).\nStatistical concept(s): Market capitalization figures include: shares of listed domestic companies; shares of foreign companies which are exclusively listed on an exchange (i.e., the foreign company is not listed on any other exchange); common and preferred shares of domestic companies; and shares without voting rights. Market capitalization figures exclude: collective investment funds ; rights, warrants, ETFs, convertible instruments ; options, futures ; foreign listed shares other than exclusively listed ones; companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status; and companies admitted to trading (i.e., companies whose shares are traded at the exchange but not listed at the exchange).","theme":"business","source_group":"wb"},{"code":"SH.STA.MMRT","name":"Taux de mortalité maternelle (estimation modélisée, pour 100 000 naissances vivantes)","description":"Le taux de mortalité maternelle est le nombre de femmes qui meurent de causes liées à la grossesse pendant leur grossesse ou dans les 42 jours suiv...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.MMRT?locations=CI","methodology":"Methodology: The estimates are based on an exercise by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) which consists of World Health Organization (WHO), United Nations Children's Fund (UNICEF), World Bank, and United Nations Population Fund (UNFPA), and include country-level time series data. For countries without complete registration data but with other types of data and for countries with no data, maternal mortality is estimated with a regression model using available national maternal mortality data and socioeconomic information.\nStatistical concept(s): Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\nMaternal mortality is generally of unknown reliability, as are many other cause-specific mortality indicators. Household surveys such as Demographic and Health Surveys attempt to measure maternal mortality by asking respondents about survivorship of sisters. The main disadvantage of this method is that the estimates of maternal mortality that it produces pertain to any time within the past few years before the survey, making them unsuitable for monitoring recent changes or observing the impact of interventions. In addition, measurement of maternal mortality is subject to many types of errors. Even in high-income countries with reliable vital registration systems, misclassification of maternal deaths has been found to lead to serious underestimation.","theme":"sante","source_group":"wb"},{"code":"SH.STA.MMRT.NE","name":"Taux de mortalité maternelle (estimation nationale, pour 100 000 naissances vivantes)","description":"Le taux de mortalité maternelle est le nombre de femmes qui meurent de causes liées à la grossesse pendant leur grossesse ou dans les 42 jours suiv...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.MMRT.NE?locations=CI","methodology":"Methodology: The national estimates of maternal mortality ratios are based on national surveys, vital registration records, and surveillance data or are derived from community and hospital records.\nStatistical concept(s): Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries. Maternal mortality ratios are generally of unknown reliability, as are many other cause-specific mortality indicators. Household surveys such as Demographic and Health Surveys attempt to measure maternal mortality by asking respondents about survivorship of sisters. The main disadvantage of this method is that the estimates of maternal mortality that it produces pertain to any time within the past few years before the survey, making them unsuitable for monitoring recent changes or observing the impact of interventions. In addition, measurement of maternal mortality is subject to many types of errors. Even in high-income countries with reliable vital registration systems, misclassification of maternal deaths has been found to lead to serious underestimation.","theme":"sante","source_group":"wb"},{"code":"TX.MNF.TECH.ZS.UN","name":"Exportations de moyennes et hautes technologies ( % des exportations de produits manufacturés)","description":"Part des exportations de produits manufacturés de moyenne et haute technologie dans les exportations totales de produits manufacturés.","source_link":"https://donnees.banquemondiale.org/indicateur/TX.MNF.TECH.ZS.UN?locations=CI","methodology":"Methodology: The data from UN COMTRADE is downloaded in SITC Revision 3, 3-digit, by reporting country, year, partner code, commodity and flow (export and re-export). SITC medium technology: 266, 267, 512, 513, 533, 553, 554, 562, 571, 572, 573, 574, 575, 579, 581, 582, 583, 591, 593, 597, 598, 653, 671, 672, 678, 711, 712,713, 714, 721, 722, 723, 724, 725, 726, 727, 728, 731, 733, 735, 737, 741, 742, 743, 744, 745, 746, 747, 748, 749, 761, 762, 763, 772, 773, 775, 778, 781, 782, 783, 784, 785, 786, 791, 793, 811, 812, 813, 872, 873, 882, 884, 885; SITC high technology: 525, 541, 542, 716, 718, 751, 752, 759, 764, 771, 774, 776, 792, 871, 874, 881, 891. Net-exports are calculated as exports minus re-exports. Manufactured exports, is the sum of the four categories resource-based exports, low-tech exports, medium tech exports and high-tech exports; and medium-high technology exports, is the sum of medium tech exports and high-tech exports. The world value of manufacturing exports is the sum of all manufacturing net exports. For additional information please see Table B.2.1 in Appendix B of UNIDO (2017): http://stat.unido.org/content/publications/volume-i%252c-competitive-industrial-performance-report-2016","theme":"inter","source_group":"wb"},{"code":"NV.MNF.TECH.ZS.UN","name":"Valeur ajoutée manufacturière de moyenne et haute technologie ( % de la valeur ajoutée manufacturière)","description":"La part de la valeur ajoutée des industries de moyenne et haute technologie dans la valeur ajoutée totale du secteur manufacturier","source_link":"https://donnees.banquemondiale.org/indicateur/NV.MNF.TECH.ZS.UN?locations=CI","methodology":"Methodology: The indicator is calculated as the share of the sum of the value added from medium and high-tech industry economic activities to manufacturing value added. The medium and high-tech industry is defined using OECD classification as the following by International Standard Industrial Classification of All Economic Activities (ISIC) Revision 3 and Revision 4 Division respectively: ISIC Rev. 3 (24, 29, 30, 31, 32, 33, 34, 35 excluding 351). Manufacturing value added is the value added of manufacturing industry, which is Section C of ISIC Rev.4, and Section D of ISIC Rev.3.  Data can be found in UNIDO INDSTAT4 Database by ISIC Revision 3 and ISIC Revision 4 respectively. Data are collected using General Industrial Statistics Questionnaire which is filled by NSOs and submitted to UNIDO annually. Data for OECD countries are obtained directly from OECD. Country data are also collected from official publications and official web-sites. For additional information please see Table B.2.2 in Appendix B of UNIDO (2017): http://stat.unido.org/content/publications/volume-i%252c-competitive-industrial-performance-report-2016","theme":"secondary","source_group":"wb"},{"code":"TX.VAL.MRCH.CD.WT","name":"Exportations de marchandises (en dollars américains courants)","description":"Les exportations de marchandises comprennent les biens dont la propriété économique passe d'un résident à un non-résident et qui ne sont pas inclus...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.CD.WT?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.WL.CD","name":"Exportations de marchandises de l'économie déclarante (en dollars américains courants)","description":"Les exportations de marchandises de l'économie déclarante correspondent au total des exportations de marchandises de l'économie déclarante vers le ...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.WL.CD?locations=CI","methodology":"Methodology: \"This indicator presents the total value of all merchandise exports made by the reporting country over a given period, typically a calendar year. Exports are This This indicator presents the total value of all merchandise exports made by the reporting country over a given period, typically a calendar year. Exports are measured in nominal terms using current U.S. dollars and represent the total value of goods crossing the economic border of the country for sale, exchange, or further processing abroad. Data are reported by national customs authorities and compiled by statistical offices.\n\nExport values are recorded on a free-on-board (FOB) basis, which includes the cost of goods up to the point of shipment, excluding transportation and insurance costs beyond the exporting country. All merchandise goods are included, regardless of their final use in the destination country. Re-exports may be included or excluded depending on national reporting practices; when excluded, the values represent domestic exports only. Goods exported for processing, assembly, or resale are included if ownership is transferred to a foreign entity.\n\nThis indicator provides a comprehensive view of the country’s trade performance, export capacity, and integration into the global market. Changes in total exports can reflect economic cycles, shifts in production and competitiveness, changes in external demand, or exchange rate dynamics. Policymakers, economists, and trade analysts often rely on this measure to assess external sector performance, inform macroeconomic modeling, or design export promotion strategies.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.RS.ZS","name":"Exportations de marchandises de l'économie déclarante, résiduelles ( % des exportations totales de marchandises)","description":"Les exportations résiduelles de marchandises par l'économie déclarante correspondent au total des exportations de marchandises de l'économie déclar...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.RS.ZS?locations=CI","methodology":"Methodology: \"This indicator presents the total value of all merchandise exports made by the reporting country over a given period, typically a calendar year. Exports are This This indicator presents the total value of all merchandise exports made by the reporting country over a given period, typically a calendar year. Exports are measured in nominal terms using current U.S. dollars and represent the total value of goods crossing the economic border of the country for sale, exchange, or further processing abroad. Data are reported by national customs authorities and compiled by statistical offices.\n\nExport values are recorded on a free-on-board (FOB) basis, which includes the cost of goods up to the point of shipment, excluding transportation and insurance costs beyond the exporting country. All merchandise goods are included, regardless of their final use in the destination country. Re-exports may be included or excluded depending on national reporting practices; when excluded, the values represent domestic exports only. Goods exported for processing, assembly, or resale are included if ownership is transferred to a foreign entity.\n\nThis indicator provides a comprehensive view of the country’s trade performance, export capacity, and integration into the global market. Changes in total exports can reflect economic cycles, shifts in production and competitiveness, changes in external demand, or exchange rate dynamics. Policymakers, economists, and trade analysts often rely on this measure to assess external sector performance, inform macroeconomic modeling, or design export promotion strategies.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.AL.ZS","name":"Exportations de marchandises vers les économies du monde arabe ( % des exportations totales de marchandises)","description":"Les exportations de marchandises vers les économies du monde arabe correspondent à la somme des exportations de marchandises de l’économie déclaran...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.AL.ZS?locations=CI","methodology":"Methodology: This indicator expresses the percentage of a country’s total merchandise exports that are destined for a specific group of economies, such as high-income countries, the Arab World, or various regional and development classifications. It is calculated as the ratio between the value of goods exported to the specified group and the total value of all merchandise exports of the reporting economy in the same period. All export values are expressed in current U.S. dollars and originate from customs records collected by national authorities.\n\nThe destination of merchandise exports is identified through shipping documentation and export declarations, typically using the last known destination country at the time of customs clearance. Classification of partner economies is based on lists reflecting regional membership, development level, or income groupings as used at the time of reporting. For example, high-income economies are defined by income thresholds, while other groups like the Arab World are identified by political-geographic criteria.\n\nExport data are usually reported on a free-on-board (FOB) basis, meaning the value reflects the cost of goods at the point of shipment, excluding insurance and freight beyond the port of departure. The indicator provides a measure of export market concentration and can be used to analyze changes in trade orientation, dependency on particular economic groups, or regional integration strategies. Policymakers, analysts, and trade negotiators may use this metric to monitor shifts in export destinations due to new trade agreements, geopolitical developments, supply chain changes, or shifts in global demand. Fluctuations may also reflect external shocks such as sanctions or disruptions in partner economies.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.HI.ZS","name":"Exportations de marchandises vers les pays à revenu élevé ( % des exportations totales de marchandises)","description":"Les exportations de marchandises vers les économies à revenu élevé correspondent à la somme des exportations de marchandises de l’économie déclaran...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.HI.ZS?locations=CI","methodology":"Methodology: This indicator expresses the percentage of a country’s total merchandise exports that are destined for a specific group of economies, such as high-income countries, the Arab World, or various regional and development classifications. It is calculated as the ratio between the value of goods exported to the specified group and the total value of all merchandise exports of the reporting economy in the same period. All export values are expressed in current U.S. dollars and originate from customs records collected by national authorities.\n\nThe destination of merchandise exports is identified through shipping documentation and export declarations, typically using the last known destination country at the time of customs clearance. Classification of partner economies is based on lists reflecting regional membership, development level, or income groupings as used at the time of reporting. For example, high-income economies are defined by income thresholds, while other groups like the Arab World are identified by political-geographic criteria.\n\nExport data are usually reported on a free-on-board (FOB) basis, meaning the value reflects the cost of goods at the point of shipment, excluding insurance and freight beyond the port of departure. The indicator provides a measure of export market concentration and can be used to analyze changes in trade orientation, dependency on particular economic groups, or regional integration strategies. Policymakers, analysts, and trade negotiators may use this metric to monitor shifts in export destinations due to new trade agreements, geopolitical developments, supply chain changes, or shifts in global demand. Fluctuations may also reflect external shocks such as sanctions or disruptions in partner economies.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.R1.ZS","name":"Exportations de marchandises vers les pays à revenu faible ou intermédiaire de l'Asie de l'Est et du Pacifique (en % des exportations totales de marchandises)","description":"Les exportations de marchandises vers les économies à revenu faible et intermédiaire de la région Asie de l’Est et Pacifique correspondent à la som...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.R1.ZS?locations=CI","methodology":"Methodology: This indicator expresses the percentage of a country’s total merchandise exports that are destined for a specific group of economies, such as high-income countries, the Arab World, or various regional and development classifications. It is calculated as the ratio between the value of goods exported to the specified group and the total value of all merchandise exports of the reporting economy in the same period. All export values are expressed in current U.S. dollars and originate from customs records collected by national authorities.\n\nThe destination of merchandise exports is identified through shipping documentation and export declarations, typically using the last known destination country at the time of customs clearance. Classification of partner economies is based on lists reflecting regional membership, development level, or income groupings as used at the time of reporting. For example, high-income economies are defined by income thresholds, while other groups like the Arab World are identified by political-geographic criteria.\n\nExport data are usually reported on a free-on-board (FOB) basis, meaning the value reflects the cost of goods at the point of shipment, excluding insurance and freight beyond the port of departure. The indicator provides a measure of export market concentration and can be used to analyze changes in trade orientation, dependency on particular economic groups, or regional integration strategies. Policymakers, analysts, and trade negotiators may use this metric to monitor shifts in export destinations due to new trade agreements, geopolitical developments, supply chain changes, or shifts in global demand. Fluctuations may also reflect external shocks such as sanctions or disruptions in partner economies.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.R2.ZS","name":"Exportations de marchandises vers les pays à revenu faible ou intermédiaire d'Europe et d'Asie centrale ( % des exportations totales de marchandises)","description":"Les exportations de marchandises vers les économies à revenu faible et intermédiaire d’Europe et d’Asie centrale correspondent à la somme des expor...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.R2.ZS?locations=CI","methodology":"Methodology: This indicator expresses the percentage of a country’s total merchandise exports that are destined for a specific group of economies, such as high-income countries, the Arab World, or various regional and development classifications. It is calculated as the ratio between the value of goods exported to the specified group and the total value of all merchandise exports of the reporting economy in the same period. All export values are expressed in current U.S. dollars and originate from customs records collected by national authorities.\n\nThe destination of merchandise exports is identified through shipping documentation and export declarations, typically using the last known destination country at the time of customs clearance. Classification of partner economies is based on lists reflecting regional membership, development level, or income groupings as used at the time of reporting. For example, high-income economies are defined by income thresholds, while other groups like the Arab World are identified by political-geographic criteria.\n\nExport data are usually reported on a free-on-board (FOB) basis, meaning the value reflects the cost of goods at the point of shipment, excluding insurance and freight beyond the port of departure. The indicator provides a measure of export market concentration and can be used to analyze changes in trade orientation, dependency on particular economic groups, or regional integration strategies. Policymakers, analysts, and trade negotiators may use this metric to monitor shifts in export destinations due to new trade agreements, geopolitical developments, supply chain changes, or shifts in global demand. Fluctuations may also reflect external shocks such as sanctions or disruptions in partner economies.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.R3.ZS","name":"Exportations de marchandises vers les pays à revenu faible ou intermédiaire d'Amérique latine et des Caraïbes ( % des exportations totales de marchandises)","description":"Les exportations de marchandises vers les économies à revenu faible et intermédiaire d’Amérique latine et des Caraïbes correspondent à la somme des...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.R3.ZS?locations=CI","methodology":"Methodology: This indicator expresses the percentage of a country’s total merchandise exports that are destined for a specific group of economies, such as high-income countries, the Arab World, or various regional and development classifications. It is calculated as the ratio between the value of goods exported to the specified group and the total value of all merchandise exports of the reporting economy in the same period. All export values are expressed in current U.S. dollars and originate from customs records collected by national authorities.\n\nThe destination of merchandise exports is identified through shipping documentation and export declarations, typically using the last known destination country at the time of customs clearance. Classification of partner economies is based on lists reflecting regional membership, development level, or income groupings as used at the time of reporting. For example, high-income economies are defined by income thresholds, while other groups like the Arab World are identified by political-geographic criteria.\n\nExport data are usually reported on a free-on-board (FOB) basis, meaning the value reflects the cost of goods at the point of shipment, excluding insurance and freight beyond the port of departure. The indicator provides a measure of export market concentration and can be used to analyze changes in trade orientation, dependency on particular economic groups, or regional integration strategies. Policymakers, analysts, and trade negotiators may use this metric to monitor shifts in export destinations due to new trade agreements, geopolitical developments, supply chain changes, or shifts in global demand. Fluctuations may also reflect external shocks such as sanctions or disruptions in partner economies.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.R4.ZS","name":"Exportations de marchandises vers les pays à revenu faible et intermédiaire du Moyen-Orient et de l'Afrique du Nord (en % des exportations totales de marchandises)","description":"Les exportations de marchandises vers les économies à revenu faible et intermédiaire du Moyen-Orient et d'Afrique du Nord correspondent à la somme ...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.R4.ZS?locations=CI","methodology":"Methodology: This indicator expresses the percentage of a country’s total merchandise exports that are destined for a specific group of economies, such as high-income countries, the Arab World, or various regional and development classifications. It is calculated as the ratio between the value of goods exported to the specified group and the total value of all merchandise exports of the reporting economy in the same period. All export values are expressed in current U.S. dollars and originate from customs records collected by national authorities.\n\nThe destination of merchandise exports is identified through shipping documentation and export declarations, typically using the last known destination country at the time of customs clearance. Classification of partner economies is based on lists reflecting regional membership, development level, or income groupings as used at the time of reporting. For example, high-income economies are defined by income thresholds, while other groups like the Arab World are identified by political-geographic criteria.\n\nExport data are usually reported on a free-on-board (FOB) basis, meaning the value reflects the cost of goods at the point of shipment, excluding insurance and freight beyond the port of departure. The indicator provides a measure of export market concentration and can be used to analyze changes in trade orientation, dependency on particular economic groups, or regional integration strategies. Policymakers, analysts, and trade negotiators may use this metric to monitor shifts in export destinations due to new trade agreements, geopolitical developments, supply chain changes, or shifts in global demand. Fluctuations may also reflect external shocks such as sanctions or disruptions in partner economies.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.R5.ZS","name":"Exportations de marchandises vers les pays à revenu faible ou intermédiaire d'Asie du Sud ( % des exportations totales de marchandises)","description":"Les exportations de marchandises vers les économies à revenu faible et intermédiaire d'Asie du Sud correspondent à la somme des exportations de mar...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.R5.ZS?locations=CI","methodology":"Methodology: This indicator expresses the percentage of a country’s total merchandise exports that are destined for a specific group of economies, such as high-income countries, the Arab World, or various regional and development classifications. It is calculated as the ratio between the value of goods exported to the specified group and the total value of all merchandise exports of the reporting economy in the same period. All export values are expressed in current U.S. dollars and originate from customs records collected by national authorities.\n\nThe destination of merchandise exports is identified through shipping documentation and export declarations, typically using the last known destination country at the time of customs clearance. Classification of partner economies is based on lists reflecting regional membership, development level, or income groupings as used at the time of reporting. For example, high-income economies are defined by income thresholds, while other groups like the Arab World are identified by political-geographic criteria.\n\nExport data are usually reported on a free-on-board (FOB) basis, meaning the value reflects the cost of goods at the point of shipment, excluding insurance and freight beyond the port of departure. The indicator provides a measure of export market concentration and can be used to analyze changes in trade orientation, dependency on particular economic groups, or regional integration strategies. Policymakers, analysts, and trade negotiators may use this metric to monitor shifts in export destinations due to new trade agreements, geopolitical developments, supply chain changes, or shifts in global demand. Fluctuations may also reflect external shocks such as sanctions or disruptions in partner economies.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.R6.ZS","name":"Exportations de marchandises vers les pays à revenu faible ou intermédiaire d'Afrique subsaharienne (en % des exportations totales de marchandises)","description":"Les exportations de marchandises vers les économies à revenu faible et intermédiaire d’Afrique subsaharienne correspondent à la somme des exportati...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.R6.ZS?locations=CI","methodology":"Methodology: This indicator expresses the percentage of a country’s total merchandise exports that are destined for a specific group of economies, such as high-income countries, the Arab World, or various regional and development classifications. It is calculated as the ratio between the value of goods exported to the specified group and the total value of all merchandise exports of the reporting economy in the same period. All export values are expressed in current U.S. dollars and originate from customs records collected by national authorities.\n\nThe destination of merchandise exports is identified through shipping documentation and export declarations, typically using the last known destination country at the time of customs clearance. Classification of partner economies is based on lists reflecting regional membership, development level, or income groupings as used at the time of reporting. For example, high-income economies are defined by income thresholds, while other groups like the Arab World are identified by political-geographic criteria.\n\nExport data are usually reported on a free-on-board (FOB) basis, meaning the value reflects the cost of goods at the point of shipment, excluding insurance and freight beyond the port of departure. The indicator provides a measure of export market concentration and can be used to analyze changes in trade orientation, dependency on particular economic groups, or regional integration strategies. Policymakers, analysts, and trade negotiators may use this metric to monitor shifts in export destinations due to new trade agreements, geopolitical developments, supply chain changes, or shifts in global demand. Fluctuations may also reflect external shocks such as sanctions or disruptions in partner economies.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.OR.ZS","name":"Exportations de marchandises vers les pays à revenu faible ou intermédiaire en dehors de la région ( % des exportations totales de marchandises)","description":"Les exportations de marchandises vers les économies à revenu faible et intermédiaire hors région correspondent à la somme des exportations de march...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.OR.ZS?locations=CI","methodology":"Methodology: This indicator expresses the percentage of a country’s total merchandise exports that are destined for a specific group of economies, such as high-income countries, the Arab World, or various regional and development classifications. It is calculated as the ratio between the value of goods exported to the specified group and the total value of all merchandise exports of the reporting economy in the same period. All export values are expressed in current U.S. dollars and originate from customs records collected by national authorities.\n\nThe destination of merchandise exports is identified through shipping documentation and export declarations, typically using the last known destination country at the time of customs clearance. Classification of partner economies is based on lists reflecting regional membership, development level, or income groupings as used at the time of reporting. For example, high-income economies are defined by income thresholds, while other groups like the Arab World are identified by political-geographic criteria.\n\nExport data are usually reported on a free-on-board (FOB) basis, meaning the value reflects the cost of goods at the point of shipment, excluding insurance and freight beyond the port of departure. The indicator provides a measure of export market concentration and can be used to analyze changes in trade orientation, dependency on particular economic groups, or regional integration strategies. Policymakers, analysts, and trade negotiators may use this metric to monitor shifts in export destinations due to new trade agreements, geopolitical developments, supply chain changes, or shifts in global demand. Fluctuations may also reflect external shocks such as sanctions or disruptions in partner economies.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.MRCH.WR.ZS","name":"Exportations de marchandises vers les pays à revenu faible ou intermédiaire de la région ( % des exportations totales de marchandises)","description":"Les exportations de marchandises vers les économies à revenu faible et intermédiaire au sein d’une région correspondent à la somme des exportations...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MRCH.WR.ZS?locations=CI","methodology":"Methodology: This indicator expresses the percentage of a country’s total merchandise exports that are destined for a specific group of economies, such as high-income countries, the Arab World, or various regional and development classifications. It is calculated as the ratio between the value of goods exported to the specified group and the total value of all merchandise exports of the reporting economy in the same period. All export values are expressed in current U.S. dollars and originate from customs records collected by national authorities.\n\nThe destination of merchandise exports is identified through shipping documentation and export declarations, typically using the last known destination country at the time of customs clearance. Classification of partner economies is based on lists reflecting regional membership, development level, or income groupings as used at the time of reporting. For example, high-income economies are defined by income thresholds, while other groups like the Arab World are identified by political-geographic criteria.\n\nExport data are usually reported on a free-on-board (FOB) basis, meaning the value reflects the cost of goods at the point of shipment, excluding insurance and freight beyond the port of departure. The indicator provides a measure of export market concentration and can be used to analyze changes in trade orientation, dependency on particular economic groups, or regional integration strategies. Policymakers, analysts, and trade negotiators may use this metric to monitor shifts in export destinations due to new trade agreements, geopolitical developments, supply chain changes, or shifts in global demand. Fluctuations may also reflect external shocks such as sanctions or disruptions in partner economies.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.CD.WT","name":"Importations de marchandises (en dollars américains courants)","description":"Les importations de marchandises comprennent les biens dont la propriété économique passe d'un non-résident à un résident et qui ne sont pas inclus...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.CD.WT?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.WL.CD","name":"Importations de marchandises par l'économie déclarante (en dollars courants des États-Unis)","description":"Les importations de marchandises de l'économie déclarante correspondent au total des importations de marchandises de l'économie déclarante en prove...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.WL.CD?locations=CI","methodology":"Methodology: This indicator represents the total value of merchandise imports reported by a country over a specified period, typically a calendar year. The value includes all goods that physically enter the country’s economic territory and are intended for consumption, processing, or re-export. Data are expressed in nominal terms using current U.S. dollars. The data source is primarily customs administrative records submitted by importers, compiled by national statistical or trade authorities.\n\nThe reported value of imports generally includes the cost of goods plus insurance and freight (CIF), which reflects the full landed value at the port of entry. The general trade system is used in most cases, meaning that imports into bonded warehouses and free zones are also included. The data exclude services and focus solely on physical goods crossing borders. Corrections may be applied for coverage limitations, underreporting, valuation discrepancies, or misclassifications to improve comparability.\n\nSome versions of the indicator may exclude re-imports, which are goods previously exported and returned to the country without significant transformation. This distinction ensures that the import figures do not overstate economic activity by counting the same goods more than once. Users of the indicator include government agencies monitoring trade flows, businesses analyzing sourcing strategies, and researchers studying trade balances. It also provides input for calculating the balance of trade and understanding integration into global markets.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.RS.ZS","name":"Importations de marchandises de l'économie déclarante, résiduelles ( % des importations totales de marchandises)","description":"Les résidus des importations de marchandises par l'économie déclarante correspondent au total des importations de marchandises de l'économie déclar...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.RS.ZS?locations=CI","methodology":"Methodology: This indicator represents the total value of merchandise imports reported by a country over a specified period, typically a calendar year. The value includes all goods that physically enter the country’s economic territory and are intended for consumption, processing, or re-export. Data are expressed in nominal terms using current U.S. dollars. The data source is primarily customs administrative records submitted by importers, compiled by national statistical or trade authorities.\n\nThe reported value of imports generally includes the cost of goods plus insurance and freight (CIF), which reflects the full landed value at the port of entry. The general trade system is used in most cases, meaning that imports into bonded warehouses and free zones are also included. The data exclude services and focus solely on physical goods crossing borders. Corrections may be applied for coverage limitations, underreporting, valuation discrepancies, or misclassifications to improve comparability.\n\nSome versions of the indicator may exclude re-imports, which are goods previously exported and returned to the country without significant transformation. This distinction ensures that the import figures do not overstate economic activity by counting the same goods more than once. Users of the indicator include government agencies monitoring trade flows, businesses analyzing sourcing strategies, and researchers studying trade balances. It also provides input for calculating the balance of trade and understanding integration into global markets.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.AL.ZS","name":"Importations de marchandises en provenance des économies du monde arabe ( % des importations totales de marchandises)","description":"Les importations de marchandises en provenance des économies du monde arabe correspondent à la somme des importations de marchandises de l'économie...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.AL.ZS?locations=CI","methodology":"Methodology: This indicator measures the percentage of total merchandise imports by the reporting country that originate from economies in the Arab World. The purpose is to assess the relative importance of trade with economies in the Arab World economies within the broader context of global imports. The numerator includes the total value of goods imported from economies in the Arab World, while the denominator includes all merchandise imports received by the reporting economy within the reference year. Both values are recorded in current U.S. dollars and typically sourced from national customs declarations.\n\nThe origin of merchandise imports is determined based on standard customs procedures, such as certificates of origin and supporting shipping documentation. Goods are generally recorded on a cost-insurance-freight (CIF) basis, meaning the import value includes the cost of the goods as well as transportation and insurance costs incurred up to the point of entry into the importing country. This ensures that comparisons across economies reflect the total landed value of imports.\n\nThe classification of economies in the Arab World follows the grouping conventions available at the time of reporting. Where applicable, economies are grouped according to income level, regional affiliation, or development status. The indicator enables monitoring of trade exposure and diversification by identifying which country groupings supply a significant portion of merchandise goods. In some cases, governments may also use this metric to guide trade policy, tariff design, or regional cooperation strategies. Fluctuations in the share may reflect changes in trade agreements, exchange rates, supply chain dependencies, or global demand for specific products.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.HI.ZS","name":"Importations de marchandises en provenance des pays à revenu élevé ( % des importations totales de marchandises)","description":"Les importations de marchandises en provenance des économies à revenu élevé correspondent à la somme des importations de marchandises de l’économie...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.HI.ZS?locations=CI","methodology":"Methodology: This indicator measures the percentage of total merchandise imports by the reporting country that originate from high-income economies. The purpose is to assess the relative importance of trade with high-income economies economies within the broader context of global imports. The numerator includes the total value of goods imported from high-income economies, while the denominator includes all merchandise imports received by the reporting economy within the reference year. Both values are recorded in current U.S. dollars and typically sourced from national customs declarations.\n\nThe origin of merchandise imports is determined based on standard customs procedures, such as certificates of origin and supporting shipping documentation. Goods are generally recorded on a cost-insurance-freight (CIF) basis, meaning the import value includes the cost of the goods as well as transportation and insurance costs incurred up to the point of entry into the importing country. This ensures that comparisons across economies reflect the total landed value of imports.\n\nThe classification of high-income economies follows the grouping conventions available at the time of reporting. Where applicable, economies are grouped according to income level, regional affiliation, or development status. The indicator enables monitoring of trade exposure and diversification by identifying which country groupings supply a significant portion of merchandise goods. In some cases, governments may also use this metric to guide trade policy, tariff design, or regional cooperation strategies. Fluctuations in the share may reflect changes in trade agreements, exchange rates, supply chain dependencies, or global demand for specific products.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.R1.ZS","name":"Importations de marchandises en provenance des pays à revenu faible ou intermédiaire de l'Asie de l'Est et du Pacifique (en % des importations totales de marchandises)","description":"Les importations de marchandises en provenance des économies à revenu faible et intermédiaire de la région Asie de l’Est et Pacifique correspondent...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.R1.ZS?locations=CI","methodology":"Methodology: This indicator measures the percentage of total merchandise imports by the reporting country that originate from low- and middle-income economies in East Asia & Pacific. The purpose is to assess the relative importance of trade with low- and middle-income economies in East Asia & Pacific economies within the broader context of global imports. The numerator includes the total value of goods imported from low- and middle-income economies in East Asia & Pacific, while the denominator includes all merchandise imports received by the reporting economy within the reference year. Both values are recorded in current U.S. dollars and typically sourced from national customs declarations.\n\nThe origin of merchandise imports is determined based on standard customs procedures, such as certificates of origin and supporting shipping documentation. Goods are generally recorded on a cost-insurance-freight (CIF) basis, meaning the import value includes the cost of the goods as well as transportation and insurance costs incurred up to the point of entry into the importing country. This ensures that comparisons across economies reflect the total landed value of imports.\n\nThe classification of low- and middle-income economies in East Asia & Pacific follows the grouping conventions available at the time of reporting. Where applicable, economies are grouped according to income level, regional affiliation, or development status. The indicator enables monitoring of trade exposure and diversification by identifying which country groupings supply a significant portion of merchandise goods. In some cases, governments may also use this metric to guide trade policy, tariff design, or regional cooperation strategies. Fluctuations in the share may reflect changes in trade agreements, exchange rates, supply chain dependencies, or global demand for specific products.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.R2.ZS","name":"Importations de marchandises en provenance des pays à revenu faible ou intermédiaire d'Europe et d'Asie centrale (en % des importations totales de marchandises)","description":"Les importations de marchandises en provenance des économies à revenu faible et intermédiaire d'Europe et d'Asie centrale correspondent à la somme ...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.R2.ZS?locations=CI","methodology":"Methodology: This indicator measures the percentage of total merchandise imports by the reporting country that originate from low- and middle-income economies in Europe & Central Asia. The purpose is to assess the relative importance of trade with low- and middle-income economies in Europe & Central Asia economies within the broader context of global imports. The numerator includes the total value of goods imported from low- and middle-income economies in Europe & Central Asia, while the denominator includes all merchandise imports received by the reporting economy within the reference year. Both values are recorded in current U.S. dollars and typically sourced from national customs declarations.\n\nThe origin of merchandise imports is determined based on standard customs procedures, such as certificates of origin and supporting shipping documentation. Goods are generally recorded on a cost-insurance-freight (CIF) basis, meaning the import value includes the cost of the goods as well as transportation and insurance costs incurred up to the point of entry into the importing country. This ensures that comparisons across economies reflect the total landed value of imports.\n\nThe classification of low- and middle-income economies in Europe & Central Asia follows the grouping conventions available at the time of reporting. Where applicable, economies are grouped according to income level, regional affiliation, or development status. The indicator enables monitoring of trade exposure and diversification by identifying which country groupings supply a significant portion of merchandise goods. In some cases, governments may also use this metric to guide trade policy, tariff design, or regional cooperation strategies. Fluctuations in the share may reflect changes in trade agreements, exchange rates, supply chain dependencies, or global demand for specific products.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.R3.ZS","name":"Importations de marchandises en provenance des pays à revenu faible ou intermédiaire d'Amérique latine et des Caraïbes ( % des importations totales de marchandises)","description":"Les importations de marchandises en provenance des économies à revenu faible et intermédiaire d'Amérique latine et des Caraïbes correspondent à la ...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.R3.ZS?locations=CI","methodology":"Methodology: This indicator measures the percentage of total merchandise imports by the reporting country that originate from low- and middle-income economies in Latin America & the Caribbean. The purpose is to assess the relative importance of trade with low- and middle-income economies in Latin America & the Caribbean economies within the broader context of global imports. The numerator includes the total value of goods imported from low- and middle-income economies in Latin America & the Caribbean, while the denominator includes all merchandise imports received by the reporting economy within the reference year. Both values are recorded in current U.S. dollars and typically sourced from national customs declarations.\n\nThe origin of merchandise imports is determined based on standard customs procedures, such as certificates of origin and supporting shipping documentation. Goods are generally recorded on a cost-insurance-freight (CIF) basis, meaning the import value includes the cost of the goods as well as transportation and insurance costs incurred up to the point of entry into the importing country. This ensures that comparisons across economies reflect the total landed value of imports.\n\nThe classification of low- and middle-income economies in Latin America & the Caribbean follows the grouping conventions available at the time of reporting. Where applicable, economies are grouped according to income level, regional affiliation, or development status. The indicator enables monitoring of trade exposure and diversification by identifying which country groupings supply a significant portion of merchandise goods. In some cases, governments may also use this metric to guide trade policy, tariff design, or regional cooperation strategies. Fluctuations in the share may reflect changes in trade agreements, exchange rates, supply chain dependencies, or global demand for specific products.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.R4.ZS","name":"Importations de marchandises en provenance des pays à revenu faible ou intermédiaire du Moyen-Orient et de l'Afrique du Nord (en % des importations totales de marchandises)","description":"Les importations de marchandises en provenance des économies à revenu faible et intermédiaire du Moyen-Orient et d'Afrique du Nord correspondent à ...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.R4.ZS?locations=CI","methodology":"Methodology: This indicator measures the percentage of total merchandise imports by the reporting country that originate from low- and middle-income economies in Middle East & North Africa. The purpose is to assess the relative importance of trade with low- and middle-income economies in Middle East & North Africa economies within the broader context of global imports. The numerator includes the total value of goods imported from low- and middle-income economies in Middle East & North Africa, while the denominator includes all merchandise imports received by the reporting economy within the reference year. Both values are recorded in current U.S. dollars and typically sourced from national customs declarations.\n\nThe origin of merchandise imports is determined based on standard customs procedures, such as certificates of origin and supporting shipping documentation. Goods are generally recorded on a cost-insurance-freight (CIF) basis, meaning the import value includes the cost of the goods as well as transportation and insurance costs incurred up to the point of entry into the importing country. This ensures that comparisons across economies reflect the total landed value of imports.\n\nThe classification of low- and middle-income economies in Middle East & North Africa follows the grouping conventions available at the time of reporting. Where applicable, economies are grouped according to income level, regional affiliation, or development status. The indicator enables monitoring of trade exposure and diversification by identifying which country groupings supply a significant portion of merchandise goods. In some cases, governments may also use this metric to guide trade policy, tariff design, or regional cooperation strategies. Fluctuations in the share may reflect changes in trade agreements, exchange rates, supply chain dependencies, or global demand for specific products.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.R5.ZS","name":"Importations de marchandises en provenance des pays à revenu faible ou intermédiaire d'Asie du Sud (en % des importations totales de marchandises)","description":"Les importations de marchandises en provenance des économies à revenu faible et intermédiaire d'Asie du Sud correspondent à la somme des importatio...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.R5.ZS?locations=CI","methodology":"Methodology: This indicator measures the percentage of total merchandise imports by the reporting country that originate from low- and middle-income economies in South Asia. The purpose is to assess the relative importance of trade with low- and middle-income economies in South Asia economies within the broader context of global imports. The numerator includes the total value of goods imported from low- and middle-income economies in South Asia, while the denominator includes all merchandise imports received by the reporting economy within the reference year. Both values are recorded in current U.S. dollars and typically sourced from national customs declarations.\n\nThe origin of merchandise imports is determined based on standard customs procedures, such as certificates of origin and supporting shipping documentation. Goods are generally recorded on a cost-insurance-freight (CIF) basis, meaning the import value includes the cost of the goods as well as transportation and insurance costs incurred up to the point of entry into the importing country. This ensures that comparisons across economies reflect the total landed value of imports.\n\nThe classification of low- and middle-income economies in South Asia follows the grouping conventions available at the time of reporting. Where applicable, economies are grouped according to income level, regional affiliation, or development status. The indicator enables monitoring of trade exposure and diversification by identifying which country groupings supply a significant portion of merchandise goods. In some cases, governments may also use this metric to guide trade policy, tariff design, or regional cooperation strategies. Fluctuations in the share may reflect changes in trade agreements, exchange rates, supply chain dependencies, or global demand for specific products.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.R6.ZS","name":"Importations de marchandises en provenance des pays à revenu faible ou intermédiaire d'Afrique subsaharienne ( % des importations totales de marchandises)","description":"Les importations de marchandises en provenance des économies à revenu faible et intermédiaire d'Afrique subsaharienne correspondent à la somme des ...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.R6.ZS?locations=CI","methodology":"Methodology: This indicator measures the percentage of total merchandise imports by the reporting country that originate from low- and middle-income economies in Sub-Saharan Africa. The purpose is to assess the relative importance of trade with low- and middle-income economies in Sub-Saharan Africa economies within the broader context of global imports. The numerator includes the total value of goods imported from low- and middle-income economies in Sub-Saharan Africa, while the denominator includes all merchandise imports received by the reporting economy within the reference year. Both values are recorded in current U.S. dollars and typically sourced from national customs declarations.\n\nThe origin of merchandise imports is determined based on standard customs procedures, such as certificates of origin and supporting shipping documentation. Goods are generally recorded on a cost-insurance-freight (CIF) basis, meaning the import value includes the cost of the goods as well as transportation and insurance costs incurred up to the point of entry into the importing country. This ensures that comparisons across economies reflect the total landed value of imports.\n\nThe classification of low- and middle-income economies in Sub-Saharan Africa follows the grouping conventions available at the time of reporting. Where applicable, economies are grouped according to income level, regional affiliation, or development status. The indicator enables monitoring of trade exposure and diversification by identifying which country groupings supply a significant portion of merchandise goods. In some cases, governments may also use this metric to guide trade policy, tariff design, or regional cooperation strategies. Fluctuations in the share may reflect changes in trade agreements, exchange rates, supply chain dependencies, or global demand for specific products.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.OR.ZS","name":"Importations de marchandises en provenance des économies à revenu faible ou intermédiaire en dehors de la région ( % des importations totales de marchandises)","description":"Les importations de marchandises en provenance d’économies à revenu faible ou intermédiaire hors région correspondent à la somme des importations d...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.OR.ZS?locations=CI","methodology":"Methodology: This indicator measures the percentage of total merchandise imports by the reporting country that originate from low- and middle-income economies outside region. The purpose is to assess the relative importance of trade with low- and middle-income economies outside region economies within the broader context of global imports. The numerator includes the total value of goods imported from low- and middle-income economies outside region, while the denominator includes all merchandise imports received by the reporting economy within the reference year. Both values are recorded in current U.S. dollars and typically sourced from national customs declarations.\n\nThe origin of merchandise imports is determined based on standard customs procedures, such as certificates of origin and supporting shipping documentation. Goods are generally recorded on a cost-insurance-freight (CIF) basis, meaning the import value includes the cost of the goods as well as transportation and insurance costs incurred up to the point of entry into the importing country. This ensures that comparisons across economies reflect the total landed value of imports.\n\nThe classification of low- and middle-income economies outside region follows the grouping conventions available at the time of reporting. Where applicable, economies are grouped according to income level, regional affiliation, or development status. The indicator enables monitoring of trade exposure and diversification by identifying which country groupings supply a significant portion of merchandise goods. In some cases, governments may also use this metric to guide trade policy, tariff design, or regional cooperation strategies. Fluctuations in the share may reflect changes in trade agreements, exchange rates, supply chain dependencies, or global demand for specific products.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MRCH.WR.ZS","name":"Importations de marchandises en provenance des pays à revenu faible ou intermédiaire de la région (en % des importations totales de marchandises)","description":"Les importations de marchandises en provenance des économies à revenu faible et intermédiaire au sein d'une région correspondent à la somme des imp...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MRCH.WR.ZS?locations=CI","methodology":"Methodology: This indicator measures the percentage of total merchandise imports by the reporting country that originate from low- and middle-income economies within region. The purpose is to assess the relative importance of trade with low- and middle-income economies within region economies within the broader context of global imports. The numerator includes the total value of goods imported from low- and middle-income economies within region, while the denominator includes all merchandise imports received by the reporting economy within the reference year. Both values are recorded in current U.S. dollars and typically sourced from national customs declarations.\n\nThe origin of merchandise imports is determined based on standard customs procedures, such as certificates of origin and supporting shipping documentation. Goods are generally recorded on a cost-insurance-freight (CIF) basis, meaning the import value includes the cost of the goods as well as transportation and insurance costs incurred up to the point of entry into the importing country. This ensures that comparisons across economies reflect the total landed value of imports.\n\nThe classification of low- and middle-income economies within region follows the grouping conventions available at the time of reporting. Where applicable, economies are grouped according to income level, regional affiliation, or development status. The indicator enables monitoring of trade exposure and diversification by identifying which country groupings supply a significant portion of merchandise goods. In some cases, governments may also use this metric to guide trade policy, tariff design, or regional cooperation strategies. Fluctuations in the share may reflect changes in trade agreements, exchange rates, supply chain dependencies, or global demand for specific products.","theme":"inter","source_group":"wb"},{"code":"TG.VAL.TOTL.GD.ZS","name":"Commerce de marchandises ( % du PIB)","description":"Le commerce de marchandises générales comprend les biens dont la propriété économique est changée entre un résident et un non-résident et qui ne so...","source_link":"https://donnees.banquemondiale.org/indicateur/TG.VAL.TOTL.GD.ZS?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"EN.GHG.CH4.ZG.AR5","name":"Émissions de méthane (CH4) (total), à l'exclusion de l'UTCATF (variation en % par rapport à 1990)","description":"Variation des émissions (en %) de l'année en cours par rapport aux émissions de méthane (CH4), l'un des six gaz à effet de serre (GES) de l'année d...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CH4.ZG.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CH4.MT.CE.AR5","name":"Émissions de méthane (CH4) (totales) hors UTCATF (Mt d'équivalents en CO2)","description":"Une mesure des émissions annuelles de méthane (CH4), l'un des six gaz à effet de serre (GES) de Kyoto, provenant des secteurs de l'agriculture, de ...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CH4.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CH4.AG.MT.CE.AR5","name":"Émissions de méthane (CH4) provenant de l'agriculture (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles de méthane (CH4), l'un des six gaz à effet de serre (GES) de Kyoto, provenant du secteur agricole.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CH4.AG.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CH4.BU.MT.CE.AR5","name":"Émissions de méthane (CH4) provenant du bâtiment (énergie) (Mt CO2e)","description":"Une mesure des émissions annuelles de méthane (CH4), l'un des six gaz à effet de serre (GES) de Kyoto, du secteur du bâtiment (sous-secteur du sect...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CH4.BU.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CH4.FE.MT.CE.AR5","name":"Émissions de méthane (CH4) provenant des émissions fugitives (énergie) (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles de méthane (CH4), l'un des six gaz à effet de serre (GES) de Kyoto, provenant des émissions fugitives (sous-sect...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CH4.FE.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CH4.IC.MT.CE.AR5","name":"Émissions de méthane (CH4) provenant de la combustion industrielle (énergie) (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles de méthane (CH4), l'un des six gaz à effet de serre (GES) de Kyoto, provenant de la combustion industrielle (sou...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CH4.IC.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CH4.IP.MT.CE.AR5","name":"Émissions de méthane (CH4) provenant des procédés industriels (Mt CO2e)","description":"Une mesure des émissions annuelles de méthane (CH4), l'un des six gaz à effet de serre (GES) de Kyoto, provenant des processus industriels, y compr...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CH4.IP.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CH4.PI.MT.CE.AR5","name":"Émissions de méthane (CH4) provenant de l'industrie de l'électricité (énergie) (Mt CO2e)","description":"Une mesure des émissions annuelles de méthane (CH4), l'un des six gaz à effet de serre (GES) de Kyoto, provenant de la production d'électricité et ...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CH4.PI.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CH4.TR.MT.CE.AR5","name":"Émissions de méthane (CH4) provenant des transports (énergie) (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles de méthane (CH4), l'un des six gaz à effet de serre (GES) de Kyoto, provenant du secteur des transports (sous-se...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CH4.TR.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.CH4.WA.MT.CE.AR5","name":"Émissions de méthane (CH4) provenant des déchets (Mt CO2e)","description":"Une mesure des émissions annuelles de méthane (CH4), l'un des six gaz à effet de serre (GES) de Kyoto, provenant du secteur des déchets.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.CH4.WA.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"MS.MIL.XPND.GD.ZS","name":"Dépenses militaires ( % du PIB)","description":"Les données sur les dépenses militaires du SIPRI sont dérivées de la définition de l'OTAN, qui inclut toutes les dépenses courantes et en capital d...","source_link":"https://donnees.banquemondiale.org/indicateur/MS.MIL.XPND.GD.ZS?locations=CI","methodology":"Methodology: SIPRI military expenditure data includes military and civil personnel, including retirement pensions and social services for military personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, and weapons conversion and destruction. This definition cannot be applied for all countries, however, since that would require more detailed information than is available about military budgets and off-budget military expenditures (for example, whether military budgets cover civil defense, reserves and auxiliary forces, police and paramilitary forces, and military pensions).\n\nSIPRI data for the most recent years include two types of estimate which apply to all countries: (a) figures for the most recent years are for adopted budgets, budget estimates or revised estimates, and are revised, more often than not, in subsequent years; and (b) the deflator used for the latest year in the series is an estimate SIPRI's primary source of military expenditure data is official data provided by national governments. These data are derived from budget documents, defense white papers, and other public documents from official government agencies, including government responses to questionnaires sent by SIPRI, the UNODA, or the Organization for Security and Co-operation in Europe. Secondary sources include international statistics, such as those of NATO and the IMF's Government Finance Statistics Yearbook. Other secondary sources include country reports of the Economist Intelligence Unit, country reports by IMF staff, and specialist journals and newspapers.\n\nThe data on military expenditures as a share of GDP are SIPRI estimates. The SIPRI military expenditure figures are presented on a calendar-year basis. The only exception is the USA, for which statistics report data on a fiscal-year basis. Calendar-year data are calculated on the assumption of an even rate of expenditure throughout the fiscal year. The ratio of military expenditure to GDP is calculated in domestic currency at current prices and for calendar years.\n\nThe SIPRI military expenditure figures are presented on a calendar-year basis. The only exception is the USA, for which statistics report data on a fiscal-year basis. Calendar-year data are calculated on the assumption of an even rate of expenditure throughout the fiscal year.","theme":"politique","source_group":"wb"},{"code":"MS.MIL.XPND.ZS","name":"Dépenses militaires (en % des dépenses publiques)","description":"Les données sur les dépenses militaires du SIPRI sont dérivées de la définition de l'OTAN, qui inclut toutes les dépenses courantes et en capital d...","source_link":"https://donnees.banquemondiale.org/indicateur/MS.MIL.XPND.ZS?locations=CI","methodology":"Methodology: SIPRI military expenditure data includes military and civil personnel, including retirement pensions and social services for military personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, and weapons conversion and destruction. This definition cannot be applied for all countries, however, since that would require more detailed information than is available about military budgets and off-budget military expenditures (for example, whether military budgets cover civil defense, reserves and auxiliary forces, police and paramilitary forces, and military pensions).\n\nSIPRI data for the most recent years include two types of estimate which apply to all countries: (a) figures for the most recent years are for adopted budgets, budget estimates or revised estimates, and are revised, more often than not, in subsequent years; and (b) the deflator used for the latest year in the series is an estimate.\n\nSIPRI's primary source of military expenditure data is official data provided by national governments. These data are derived from budget documents, defense white papers, and other public documents from official government agencies, including government responses to questionnaires sent by SIPRI, the UNODA, or the Organization for Security and Co-operation in Europe. Secondary sources include international statistics, such as those of NATO and the IMF's Government Finance Statistics Yearbook. Other secondary sources include country reports of the Economist Intelligence Unit, country reports by IMF staff, and specialist journals and newspapers.\n\nThe SIPRI military expenditure figures are presented on a calendar-year basis. The only exception is the USA, for which statistics report data on a fiscal-year basis. Calendar-year data are calculated on the assumption of an even rate of expenditure throughout the fiscal year.","theme":"politique","source_group":"wb"},{"code":"MS.MIL.XPND.CN","name":"Dépenses militaires (LCU courantes)","description":"Les données sur les dépenses militaires du SIPRI sont dérivées de la définition de l'OTAN, qui inclut toutes les dépenses courantes et en capital d...","source_link":"https://donnees.banquemondiale.org/indicateur/MS.MIL.XPND.CN?locations=CI","methodology":"Methodology: SIPRI military expenditure data includes military and civil personnel, including retirement pensions and social services for military personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, and weapons conversion and destruction. This definition cannot be applied for all countries, however, since that would require more detailed information than is available about military budgets and off-budget military expenditures (for example, whether military budgets cover civil defense, reserves and auxiliary forces, police and paramilitary forces, and military pensions).\n\nSIPRI data for the most recent years include two types of estimate which apply to all countries: (a) figures for the most recent years are for adopted budgets, budget estimates or revised estimates, and are revised, more often than not, in subsequent years; and (b) the deflator used for the latest year in the series is an estimate SIPRI's primary source of military expenditure data is official data provided by national governments. These data are derived from budget documents, defense white papers, and other public documents from official government agencies, including government responses to questionnaires sent by SIPRI, the UNODA, or the Organization for Security and Co-operation in Europe. Secondary sources include international statistics, such as those of NATO and the IMF's Government Finance Statistics Yearbook. Other secondary sources include country reports of the Economist Intelligence Unit, country reports by IMF staff, and specialist journals and newspapers.\n\nThe data on military expenditures as a share of GDP are SIPRI estimates. The SIPRI military expenditure figures are presented on a calendar-year basis. The only exception is the USA, for which statistics report data on a fiscal-year basis. Calendar-year data are calculated on the assumption of an even rate of expenditure throughout the fiscal year. The ratio of military expenditure to GDP is calculated in domestic currency at current prices and for calendar years.\n\nThe SIPRI military expenditure figures are presented on a calendar-year basis. The only exception is the USA, for which statistics report data on a fiscal-year basis. Calendar-year data are calculated on the assumption of an even rate of expenditure throughout the fiscal year.\n\nMore source and methodology information for the military expenditure data compiled by SIPRI can be accessed on the SIPRI website: https://www.sipri.org/databases/milex/sources-and-methods","theme":"politique","source_group":"wb"},{"code":"MS.MIL.XPND.CD","name":"Dépenses militaires (USD courants)","description":"Les données sur les dépenses militaires du SIPRI sont dérivées de la définition de l'OTAN, qui inclut toutes les dépenses courantes et en capital d...","source_link":"https://donnees.banquemondiale.org/indicateur/MS.MIL.XPND.CD?locations=CI","methodology":"Methodology: SIPRI military expenditure data includes military and civil personnel, including retirement pensions and social services for military personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). Excluded are civil defense and current expenditures for previous military activities, such as for veterans' benefits, demobilization, and weapons conversion and destruction. This definition cannot be applied for all countries, however, since that would require more detailed information than is available about military budgets and off-budget military expenditures (for example, whether military budgets cover civil defense, reserves and auxiliary forces, police and paramilitary forces, and military pensions).\n\nSIPRI data for the most recent years include two types of estimate which apply to all countries: (a) figures for the most recent years are for adopted budgets, budget estimates or revised estimates, and are revised, more often than not, in subsequent years; and (b) the deflator used for the latest year in the series is an estimate.\n\nSIPRI's primary source of military expenditure data is official data provided by national governments. These data are derived from budget documents, defense white papers, and other public documents from official government agencies, including government responses to questionnaires sent by SIPRI, the UNODA, or the Organization for Security and Co-operation in Europe. Secondary sources include international statistics, such as those of NATO and the IMF's Government Finance Statistics Yearbook. Other secondary sources include country reports of the Economist Intelligence Unit, country reports by IMF staff, and specialist journals and newspapers.\n\nThe SIPRI military expenditure figures are presented on a calendar-year basis. The only exception is the USA, for which statistics report data on a fiscal-year basis. Calendar-year data are calculated on the assumption of an even rate of expenditure throughout the fiscal year.","theme":"politique","source_group":"wb"},{"code":"NY.GDP.MINR.RT.ZS","name":"Rentes minières (en % du PIB)","description":"Les rentes minières sont la différence entre la valeur de production d’un stock de minéraux aux prix mondiaux et leurs coûts totaux de production.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.MINR.RT.ZS?locations=CI","methodology":"Methodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).","theme":"secondary","source_group":"wb"},{"code":"IT.CEL.SETS","name":"Abonnements cellulaires mobiles","description":"Les abonnements à la téléphonie mobile cellulaire sont des abonnements à un service public de téléphonie mobile qui donnent accès au PSTN à l'aide ...","source_link":"https://donnees.banquemondiale.org/indicateur/IT.CEL.SETS?locations=CI","methodology":"Methodology: Refers to the subscriptions to a public mobile telephone service and provides access to Public Switched Telephone Network (PSTN) using cellular technology, including number of pre-paid SIM cards active during the past three months. This includes both analogue and digital cellular systems (IMT-2000 (Third Generation, 3G) and 4G subscriptions, but excludes mobile broadband subscriptions via data cards or USB modems. Subscriptions to public mobile data services, private trunked mobile radio, telepoint or radio paging, and telemetry services should also be excluded. This should include all mobile cellular subscriptions that offer voice communications.\n\nData on mobile cellular subscribers are derived using administrative data that countries (usually the regulatory telecommunication authority or the Ministry in charge of telecommunications) regularly, and at least annually, collect from telecommunications operators.\n\nData for this indicator are readily available for approximately 90 percent of countries, either through ITU's World Telecommunication Indicators questionnaires or from official information available on the Ministry or Regulator's website. For the rest, information can be aggregated through operators' data (mainly through annual reports) and complemented by market research reports. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx\nStatistical concept(s): Data can be collected from all licensed mobile-cellular operators in the country, and then aggregated at the country level. If retail mobile-cellular services are also provided by nonfacilities-based operators (i.e., mobile virtual network operators), care should be taken to avoid double counting. One difficulty that may arise is that operators may have different definitions of ‘active’ and therefore may not be able to provide the data according to the recommended definition (i.e., used in the last three months).","theme":"tertiary","source_group":"wb"},{"code":"IT.CEL.SETS.P2","name":"Abonnements cellulaires mobiles (pour 100 personnes)","description":"Les abonnements à la téléphonie mobile cellulaire sont des abonnements à un service public de téléphonie mobile qui donnent accès au PSTN à l'aide ...","source_link":"https://donnees.banquemondiale.org/indicateur/IT.CEL.SETS.P2?locations=CI","methodology":"Methodology: Refers to the subscriptions to a public mobile telephone service and provides access to Public Switched Telephone Network (PSTN) using cellular technology, including number of pre-paid SIM cards active during the past three months. This includes both analogue and digital cellular systems (IMT-2000 (Third Generation, 3G) and 4G subscriptions, but excludes mobile broadband subscriptions via data cards or USB modems. Subscriptions to public mobile data services, private trunked mobile radio, telepoint or radio paging, and telemetry services should also be excluded. This should include all mobile cellular subscriptions that offer voice communications.\n\nData on mobile cellular subscribers are derived using administrative data that countries (usually the regulatory telecommunication authority or the Ministry in charge of telecommunications) regularly, and at least annually, collect from telecommunications operators.\n\nData for this indicator are readily available for approximately 90 percent of countries, either through ITU's World Telecommunication Indicators questionnaires or from official information available on the Ministry or Regulator's website. For the rest, information can be aggregated through operators' data (mainly through annual reports) and complemented by market research reports.\n\nMobile cellular subscriptions (per 100 people) indicator is derived by all mobile subscriptions divided by the country's population and multiplied by 100. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx\nStatistical concept(s): Data can be collected from all licensed mobile-cellular operators in the country, and then aggregated at the country level. If retail mobile-cellular services are also provided by nonfacilities-based operators (i.e., mobile virtual network operators), care should be taken to avoid double counting. One difficulty that may arise is that operators may have different definitions of ‘active’ and therefore may not be able to provide the data according to the recommended definition (i.e., used in the last three months). This indicator can be divided by the population and multiplied by 100 to obtain mobile cellular subscriptions per 100 people.","theme":"tertiary","source_group":"wb"},{"code":"FM.AST.PRVT.GD.ZS","name":"Crédit au secteur privé (en % du PIB)","description":"Le crédit intérieur au secteur privé fait référence aux ressources financières fournies au secteur privé, par exemple par le biais de prêts, d'acha...","source_link":"https://donnees.banquemondiale.org/indicateur/FM.AST.PRVT.GD.ZS?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"SH.STA.TRAF.P5","name":"Mortalité due aux accidents de la route (pour 100 000 habitants)","description":"La mortalité causée par les accidents de la route est estimée au nombre de décès par accident de la route pour 100 000 habitants.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.TRAF.P5?locations=CI","methodology":"Methodology: The methods used for analyzing causes of death vary based on the type of data available from different countries. For countries with high-quality vital registration systems that include information on cause of death, the data submitted by member states to the WHO Mortality Database is utilized, with necessary adjustments made for factors such as under-reporting of deaths, unknown age and sex, and ill-defined causes of death. In contrast, for countries lacking high-quality death registration data, cause of death estimates are derived using alternative sources, including household surveys with verbal autopsy, sample or sentinel registration systems, and special studies.","theme":"sante","source_group":"wb"},{"code":"SH.DYN.NCOM.ZS","name":"Mortalité par MCV, cancer, diabète ou CRD entre 30 et 70 ans exacts ( %)","description":"La mortalité par maladie cardiovasculaire, cancer, diabète ou maladie respiratoire chronique correspond au pourcentage de personnes de 30 ans qui m...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.NCOM.ZS?locations=CI","methodology":"Methodology: The probability of death between the exact ages of 30 and 70 is calculated using cause-specific mortality rates for each 5-year age group, applying standard life table methods. The estimates are derived from the WHO Global Health Estimates (GHE). These estimates represent WHO's best calculations, using standard categories, definitions, and methods to ensure cross-country comparability. They may not align with official national estimates.","theme":"sante","source_group":"wb"},{"code":"SH.DYN.NCOM.FE.ZS","name":"Mortalité par MCV, cancer, diabète ou MRC entre 30 et 70 ans, femmes ( %)","description":"La mortalité par maladie cardiovasculaire, cancer, diabète ou maladie respiratoire chronique correspond au pourcentage de personnes de 30 ans qui m...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.NCOM.FE.ZS?locations=CI","methodology":"Methodology: The probability of death between the exact ages of 30 and 70 is calculated using cause-specific mortality rates for each 5-year age group, applying standard life table methods. The estimates are derived from the WHO Global Health Estimates (GHE). These estimates represent WHO's best calculations, using standard categories, definitions, and methods to ensure cross-country comparability. They may not align with official national estimates.","theme":"sante","source_group":"wb"},{"code":"SH.DYN.NCOM.MA.ZS","name":"Mortalité par MCV, cancer, diabète ou MRC entre 30 et 70 ans, hommes ( %)","description":"La mortalité par maladie cardiovasculaire, cancer, diabète ou maladie respiratoire chronique correspond au pourcentage de personnes de 30 ans qui m...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.NCOM.MA.ZS?locations=CI","methodology":"Methodology: The probability of death between the exact ages of 30 and 70 is calculated using cause-specific mortality rates for each 5-year age group, applying standard life table methods. The estimates are derived from the WHO Global Health Estimates (GHE). These estimates represent WHO's best calculations, using standard categories, definitions, and methods to ensure cross-country comparability. They may not align with official national estimates.","theme":"sante","source_group":"wb"},{"code":"SH.STA.AIRP.P5","name":"Taux de mortalité attribuable à la pollution de l'air domestique et de l'air ambiant, normalisé selon l'âge (pour 100 000 habitants)","description":"Le taux de mortalité attribué à la pollution de l’air domestique et ambiant est le nombre de décès attribuables aux effets conjoints de la pollutio...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.AIRP.P5?locations=CI","methodology":"Methodology: Burden of disease (or in the present case attributable mortality) is calculated by first combining information on the increased (or relative) risk of a disease resulting from exposure, with information on how widespread the exposure is in the population (e.g.  the annual mean concentration of particulate matter to which the population is exposed). This allows calculation of the 'population attributable fraction' (PAF), which is the fraction of disease seen in a given population that can be attributed  to the exposure (e.g in this case the annual mean concentration of particulate matter). Applying this fraction to the total burden of disease (e.g. cardiopulmonary disease expressed as deaths or DALYs), gives the total number of deaths or DALYs that results from exposure to that particular risk factor (in the example given above, to ambient air pollution). To estimate the combined effects of risk factors, a joint population attributable fraction is calculated, as described in Ezzati et al (2003).","theme":"sante","source_group":"wb"},{"code":"SH.STA.AIRP.FE.P5","name":"Taux de mortalité attribuable à la pollution de l'air domestique et de l'air ambiant, normalisé selon l'âge, femmes (pour 100 000 femmes)","description":"Le taux de mortalité attribué à la pollution de l’air domestique et ambiant est le nombre de décès attribuables aux effets conjoints de la pollutio...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.AIRP.FE.P5?locations=CI","methodology":"Methodology: Burden of disease (or in the present case attributable mortality) is calculated by first combining information on the increased (or relative) risk of a disease resulting from exposure, with information on how widespread the exposure is in the population (e.g.  the annual mean concentration of particulate matter to which the population is exposed). This allows calculation of the 'population attributable fraction' (PAF), which is the fraction of disease seen in a given population that can be attributed  to the exposure (e.g in this case the annual mean concentration of particulate matter). Applying this fraction to the total burden of disease (e.g. cardiopulmonary disease expressed as deaths or DALYs), gives the total number of deaths or DALYs that results from exposure to that particular risk factor (in the example given above, to ambient air pollution). To estimate the combined effects of risk factors, a joint population attributable fraction is calculated, as described in Ezzati et al (2003).","theme":"sante","source_group":"wb"},{"code":"SH.STA.AIRP.MA.P5","name":"Taux de mortalité attribuable à la pollution de l'air domestique et de l'air ambiant, normalisé selon l'âge, hommes (pour 100 000 hommes)","description":"Le taux de mortalité attribué à la pollution de l’air domestique et ambiant est le nombre de décès attribuables aux effets conjoints de la pollutio...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.AIRP.MA.P5?locations=CI","methodology":"Methodology: Burden of disease (or in the present case attributable mortality) is calculated by first combining information on the increased (or relative) risk of a disease resulting from exposure, with information on how widespread the exposure is in the population (e.g.  the annual mean concentration of particulate matter to which the population is exposed). This allows calculation of the 'population attributable fraction' (PAF), which is the fraction of disease seen in a given population that can be attributed  to the exposure (e.g in this case the annual mean concentration of particulate matter). Applying this fraction to the total burden of disease (e.g. cardiopulmonary disease expressed as deaths or DALYs), gives the total number of deaths or DALYs that results from exposure to that particular risk factor (in the example given above, to ambient air pollution). To estimate the combined effects of risk factors, a joint population attributable fraction is calculated, as described in Ezzati et al (2003).","theme":"sante","source_group":"wb"},{"code":"SH.STA.POIS.P5","name":"Taux de mortalité attribuable à une intoxication non intentionnelle (pour 100 000 habitants)","description":"Le taux de mortalité attribué aux empoisonnements involontaires correspond au nombre de décès dus à des empoisonnements involontaires sur une année...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.POIS.P5?locations=CI","methodology":"Methodology: The estimates for unintentional poisoning mortality are derived from the WHO Global Health Estimates (GHE). For countries with high-quality vital registration systems that include information on cause of death, the data submitted by member states to the WHO Mortality Database are used, with necessary adjustments for factors such as under-reporting of deaths, unknown age and sex, and ill-defined causes of death. For countries lacking high-quality death registration data, cause of death estimates are calculated using alternative sources, including household surveys with verbal autopsy, sample or sentinel registration systems, and special studies. These estimates represent WHO's best calculations, using standard categories, definitions, and methods to ensure cross-country comparability. They may not align with official national estimates. The complete methodology can be found at the following: https://www.who.int/docs/defaultsource/gho-documents/global-health-estimates/ghe2019_cod_methods.pdf","theme":"sante","source_group":"wb"},{"code":"SH.STA.POIS.P5.FE","name":"Taux de mortalité attribuable à une intoxication non intentionnelle, femmes (pour 100 000 femmes)","description":"Le taux de mortalité attribué aux empoisonnements involontaires est le nombre de femmes décédées par empoisonnement involontaire au cours d'une ann...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.POIS.P5.FE?locations=CI","methodology":"Methodology: The estimates for unintentional poisoning mortality are derived from the WHO Global Health Estimates (GHE). For countries with high-quality vital registration systems that include information on cause of death, the data submitted by member states to the WHO Mortality Database are used, with necessary adjustments for factors such as under-reporting of deaths, unknown age and sex, and ill-defined causes of death. For countries lacking high-quality death registration data, cause of death estimates are calculated using alternative sources, including household surveys with verbal autopsy, sample or sentinel registration systems, and special studies. These estimates represent WHO's best calculations, using standard categories, definitions, and methods to ensure cross-country comparability. They may not align with official national estimates. The complete methodology can be found at the following: https://www.who.int/docs/defaultsource/gho-documents/global-health-estimates/ghe2019_cod_methods.pdf","theme":"sante","source_group":"wb"},{"code":"SH.STA.POIS.P5.MA","name":"Taux de mortalité attribuable à une intoxication non intentionnelle, hommes (pour 100 000 hommes)","description":"Le taux de mortalité attribué aux empoisonnements involontaires correspond au nombre d'hommes qui meurent chaque année par empoisonnement involonta...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.POIS.P5.MA?locations=CI","methodology":"Methodology: The estimates for unintentional poisoning mortality are derived from the WHO Global Health Estimates (GHE). For countries with high-quality vital registration systems that include information on cause of death, the data submitted by member states to the WHO Mortality Database are used, with necessary adjustments for factors such as under-reporting of deaths, unknown age and sex, and ill-defined causes of death. For countries lacking high-quality death registration data, cause of death estimates are calculated using alternative sources, including household surveys with verbal autopsy, sample or sentinel registration systems, and special studies. These estimates represent WHO's best calculations, using standard categories, definitions, and methods to ensure cross-country comparability. They may not align with official national estimates. The complete methodology can be found at the following: https://www.who.int/docs/defaultsource/gho-documents/global-health-estimates/ghe2019_cod_methods.pdf","theme":"sante","source_group":"wb"},{"code":"SH.STA.WASH.P5","name":"Taux de mortalité attribué à l'eau insalubre, à l'assainissement insalubre et au manque d'hygiène (pour 100 000 habitants)","description":"Le taux de mortalité attribué à une eau insalubre, à un assainissement insalubre et au manque d'hygiène correspond aux décès imputables à l'eau ins...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.WASH.P5?locations=CI","methodology":"Methodology: To estimate the portion of deaths from diarrhea and acute respiratory infections attributable to unsafe water, sanitation, and hygiene (WASH), a comparative risk assessment approach is used. This involves calculating the attributable disease deaths by combining information on the increased (or relative) risk of a disease resulting from exposure with the prevalence of that exposure in the population. This calculation yields the 'population attributable fraction' (PAF), which represents the fraction of disease in a population that can be attributed to the exposure, in this case, unsafe WASH.\n\n\nBy applying the PAF to the total deaths from diarrhea or acute respiratory infections, the number of deaths resulting from inadequate WASH can be determined. Additionally, deaths from protein-energy malnutrition attributable to inadequate WASH are estimated by evaluating the impacts of repeated infectious diarrhea episodes on nutritional status, particularly stunting. All deaths from intestinal nematode infections are attributed to inadequate WASH due to their transmission pathway.","theme":"sante","source_group":"wb"},{"code":"SP.DYN.AMRT.FE","name":"Taux de mortalité, adultes, femmes (pour 1 000 femmes adultes)","description":"Le taux de mortalité adulte, chez les femmes, est la probabilité de mourir entre 15 et 60 ans, c'est-à-dire la probabilité qu'une femme de 15 ans d...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.AMRT.FE?locations=CI","methodology":"Methodology: The indicator is calculated using number of survivors, l(x), at exact age x in a female period life table. The formula is: (l(60)-l(15))/(l(15))*1000.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data. Where reliable age-specific mortality data are available, life tables can be constructed from age-specific mortality data, and adult mortality rates can be calculated from life tables.","theme":"sante","source_group":"wb"},{"code":"SP.DYN.AMRT.MA","name":"Taux de mortalité, adultes, hommes (pour 1 000 hommes adultes)","description":"Le taux de mortalité adulte, chez les hommes, est la probabilité de mourir entre 15 et 60 ans, c'est-à-dire la probabilité qu'un homme de 15 ans dé...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.AMRT.MA?locations=CI","methodology":"Methodology: The indicator is calculated using number of survivors, l(x), at exact age x in a male period life table. The formula is: (l(60)-l(15))/(l(15))*1000.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data. Where reliable age-specific mortality data are available, life tables can be constructed from age-specific mortality data, and adult mortality rates can be calculated from life tables.","theme":"sante","source_group":"wb"},{"code":"SP.DYN.IMRT.IN","name":"Taux de mortalité infantile (pour 1 000 naissances vivantes)","description":"Le taux de mortalité infantile est le nombre d’enfants qui meurent avant d’atteindre l’âge d’un an, pour 1 000 naissances vivantes au cours d’une a...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.IMRT.IN?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SP.DYN.IMRT.FE.IN","name":"Taux de mortalité infantile féminine (pour 1 000 naissances vivantes)","description":"Le taux de mortalité infantile chez les femmes est le nombre de nourrissons de sexe féminin qui meurent avant d'atteindre l'âge d'un an, pour 1 000...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.IMRT.FE.IN?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SP.DYN.IMRT.MA.IN","name":"Taux de mortalité infantile masculine (pour 1 000 naissances vivantes)","description":"Le taux de mortalité infantile chez les garçons est le nombre d'enfants de sexe masculin qui meurent avant d'atteindre l'âge d'un an, pour 1 000 na...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.IMRT.MA.IN?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.DYN.NMRT","name":"Taux de mortalité néonatale (pour 1 000 naissances vivantes)","description":"Le taux de mortalité néonatale est le nombre de nouveau-nés qui meurent avant d'atteindre l'âge de 28 jours, pour 1 000 naissances vivantes au cour...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.NMRT?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.DYN.MORT","name":"Taux de mortalité des moins de 5 ans (pour 1 000 naissances vivantes)","description":"Le taux de mortalité des moins de cinq ans est la probabilité pour 1 000 qu’un nouveau-né meure avant d’atteindre l’âge de cinq ans, s’il est soumi...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.MORT?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.DYN.MORT.FE","name":"Taux de mortalité des moins de 5 ans chez les femmes (pour 1 000 naissances vivantes)","description":"Le taux de mortalité des moins de cinq ans chez les femmes est la probabilité pour 1 000 qu'un nouveau-né de sexe féminin décède avant d'atteindre ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.MORT.FE?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.DYN.MORT.MA","name":"Taux de mortalité des moins de 5 ans chez les hommes (pour 1 000 naissances vivantes)","description":"Le taux de mortalité des enfants de moins de cinq ans chez les hommes est la probabilité pour 1 000 qu'un nouveau-né de sexe masculin meure avant d...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.MORT.MA?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SI.POV.MPUN","name":"Taux de pauvreté multidimensionnelle (PNUD) ( % de la population)","description":"Le ratio de pauvreté multidimensionnelle (PNUD) est le pourcentage d'une population vivant dans la pauvreté selon l'indice de pauvreté multidimensi...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.POV.MPUN?locations=CI","methodology":"Methodology: The global MPI, published annually since 2010, captures acute multidimensional poverty in developing regions of the world (Alkire and Santos, 2014). This measure is based on the dual-cutoff counting methodology developed by Alkire and Foster (2011). The global MPI is composed of three dimensions (health, education, and living standards) and 10 corresponding indicators (nutrition, child mortality, school attendance, years of schooling, electricity, drinking water, sanitation, cooking fuel, housing, and assets). The global MPI begins by constructing a deprivation profile for each household and person in it that tracks deprivations in each of the 10 indicators. For example, a household and all people living in it are deprived if any child is stunted or any child or adult for whom data are available is underweight; if any child died in the past five years; if any school-aged child is not attending school up to the age at which he or she would complete class 8 or no household member has completed six years of schooling; or if the household lacks access to electricity, an improved source of drinking water within a 30 minute walk round trip, an improved sanitation facility that is not shared, nonsolid cooking fuel, durable housing materials, and basic assets such as a radio, animal cart, phone, television, computer, refrigerator, bicycle or motorcycle. All indicators are equally weighted within each dimension, so the health and education indicators are weighted 1/6 each, and the standard of living indicators are weighted 1/18 each. A person’s deprivation score is the sum of the weighted deprivations she or he experiences. The global MPI identifies people as multidimensionally poor if their deprivation score is 1/3 or higher. MPI values are the product of the incidence (H, or the proportion of population who live in multidimensional poverty) and intensity of poverty (A, or the average deprivation score among multidimensionally poor people). MPI = H × A. The MPI ranges from 0 to 1, and higher values imply higher poverty. MPI values decline when fewer people are poor or when poor people have fewer deprivations.\nStatistical concept(s): The UNDP's multidimensional poverty index (MPI) summarizes the incidence of multiple dimensions of poverty in a country. The MPI assesses deprivation in three dimensions of well-being (health, education, and living standards) and 10 corresponding indicators (nutrition, child mortality, school attendance, years of schooling, and access to electricity, safe drinking water, improved sanitation, good cooking fuel, good housing infrastructure).","theme":"social","source_group":"wb"},{"code":"SI.POV.MPWB","name":"Taux de pauvreté multidimensionnelle (Banque mondiale) ( % de la population)","description":"Le taux de pauvreté multidimensionnelle (Banque mondiale) est le pourcentage d'une population vivant dans la pauvreté selon la mesure de pauvreté m...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.POV.MPWB?locations=CI","methodology":"Methodology: The World Bank's Multidimensional Poverty Measure (MPM) seeks to understand poverty beyond monetary deprivations by including access to education and basic infrastructure along with the monetary headcount ratio at the $3.00 international poverty line.\nThe measure takes inspiration and guidance from other prominent global multidimensional measures, particularly the Multidimensional Poverty Index (MPI) developed by the United Nations Development Programme (UNDP) and Oxford University but differs from them in one important aspect: it includes monetary poverty less than $3.00 per day, the new International Poverty Line at 2021 PPP (Purchasing Power Parity), as one of the dimensions. \nThe MPM is composed of six indicators: consumption or income, educational attainment, educational enrollment, drinking water, sanitation, and electricity. These are mapped into three dimensions of well-being: monetary, education, and basic infrastructure services.\nThe three MPM dimensions are weighted equally, and within each dimension each indicator is also weighted equally. Individuals are considered multidimensionally deprived if they fall short of the threshold in at least one dimension or in a combination of indicators equivalent in weight to a full dimension. In other words, households will be considered poor if they are deprived in indicators whose weight adds up to 1/3 or more. Because the monetary dimension is measured using only one indicator, anyone who is income poor is automatically also poor under the multidimensional poverty measure. \nSummarizing the information on the different deprivations into a single index proves useful in making comparisons across populations and across time. However, any aggregation of indicators into a single index always involves a decision on how each indicator is to be weighted.\nStatistical concept(s): The World Bank’s multi-dimensional poverty measure (MPM) summarizes the incidence of multiple dimensions of poverty in a country. It captures the idea that poverty is multi-faceted, including both monetary and non-monetary aspects. It assesses deprivation in three dimensions of well-being (monetary poverty, education, and basic infrastructure) and 6 corresponding indicators (monetary poverty, educational attainment, educational enrollment, access to electricity, access to improved sanitation, access to safe drinking water).","theme":"social","source_group":"wb"},{"code":"DT.TDS.MLAT.PG.ZS","name":"Service de la dette multilatérale ( % du service de la dette publique et garantie par l'État)","description":"Le service de la dette multilatérale correspond au remboursement du principal et des intérêts à la Banque mondiale, aux banques régionales de dével...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.TDS.MLAT.PG.ZS?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.TDS.MLAT.CD","name":"Service de la dette multilatérale (ATD, $ US courants)","description":"Les prêts multilatéraux publics et garantis par l'État comprennent les prêts et crédits de la Banque mondiale, des banques régionales de développem...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.TDS.MLAT.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"NY.GDP.NGAS.RT.ZS","name":"Rentes du gaz naturel ( % du PIB)","description":"Les rentes du gaz naturel correspondent à la différence entre la valeur de la production de gaz naturel aux prix régionaux et les coûts totaux de p...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.NGAS.RT.ZS?locations=CI","methodology":"Methodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).","theme":"secondary","source_group":"wb"},{"code":"GC.AST.TOTL.GD.ZS","name":"Acquisition nette d'actifs financiers ( % du PIB)","description":"L'acquisition nette d'actifs financiers publics comprend les créances financières intérieures et étrangères, les DTS et les lingots d'or détenus pa...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.AST.TOTL.GD.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.AST.TOTL.CN","name":"Acquisition nette d'actifs financiers (LCU courante)","description":"L'acquisition nette d'actifs financiers publics comprend les créances financières intérieures et étrangères, les DTS et les lingots d'or détenus pa...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.AST.TOTL.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"TT.PRI.MRCH.XD.WD","name":"Indice des termes de l'échange du troc net (2015 = 100)","description":"L'indice des termes de l'échange nets du troc est calculé comme le rapport en pourcentage des indices de valeur unitaire des exportations aux indic...","source_link":"https://donnees.banquemondiale.org/indicateur/TT.PRI.MRCH.XD.WD?locations=CI","methodology":"Methodology: The Net Barter Terms of Trade Index (base year 2015 = 100) is calculated as the ratio of an export price index to an import price index, multiplied by 100. This index measures the rate at which a country can exchange its exports for imports. A value greater than 100 means the terms of trade have improved relative to the base year, allowing the country to obtain more imports for a given level of exports. Conversely, a value below 100 indicates that the terms have worsened.\n\nExport and import price indexes are derived from unit value data or sampled transaction-level data, depending on country-specific reporting practices. The price indexes may be computed using fixed or chain-weighted methods. To ensure temporal comparability, the export and import series are indexed to a common base year (2015 = 100).\n\nThe terms of trade index is sensitive to fluctuations in global commodity prices, exchange rate movements, and changes in trade composition. It is used to assess trade gains or losses, especially for countries reliant on exports of primary commodities. Although it does not capture changes in volumes traded, it provides insight into the relative value received for exports. Policymakers and researchers may use this indicator to monitor competitiveness and evaluate exposure to external shocks.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.AUSL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Australie (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.AUSL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.AUTL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Autriche (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.AUTL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.BELL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Belgique (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.BELL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.CANL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Canada (en dollars américains courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.CANL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.CZEL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, République tchèque (en dollars courants des États-Unis)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.CZEL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.DNKL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Danemark (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.DNKL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.ESTL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Estonie (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.ESTL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 32 members - 31 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.CECL.CD","name":"Flux nets d'aide bilatérale provenant des donateurs du CAD et des institutions de l'Union européenne (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.CECL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.FINL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Finlande (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.FINL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.FRAL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, France (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.FRAL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.DEUL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Allemagne (en dollars courants des États-Unis)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.DEUL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.GRCL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Grèce (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.GRCL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.HUNL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Hongrie (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.HUNL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.ISLL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Islande (en dollars courants des États-Unis)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.ISLL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.IRLL.CD","name":"Flux nets d'aide bilatérale provenant des donateurs du CAD, Irlande (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.IRLL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.ITAL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Italie (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.ITAL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.JPNL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Japon (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.JPNL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.KORL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Corée, République (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.KORL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.LTUL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Lituanie (en dollars courants des États-Unis)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.LTUL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 32 members - 31 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.LUXL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Luxembourg (en dollars courants des États-Unis)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.LUXL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.NLDL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Pays-Bas (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.NLDL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.NZLL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Nouvelle-Zélande (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.NZLL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.NORL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Norvège (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.NORL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.POLL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Pologne (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.POLL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.PRTL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Portugal (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.PRTL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.SVKL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, République slovaque (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.SVKL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.SVNL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Slovénie (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.SVNL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.ESPL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Espagne (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.ESPL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.SWEL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Suède (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.SWEL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.CHEL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Suisse (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.CHEL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.TOTL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Total (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.TOTL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.GBRL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, Royaume-Uni (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.GBRL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"DC.DAC.USAL.CD","name":"Flux nets d'aide bilatérale des donateurs du CAD, États-Unis (en dollars courants)","description":"Les flux nets d’aide bilatérale des donateurs du CAD correspondent aux décaissements nets d’aide publique au développement (APD) ou d’aide officiel...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.DAC.USAL.CD?locations=CI","methodology":"Methodology: The Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) has 30 members - 29 individual economies and 1 multilateral institution (European Union institutions).\n\nData are based on donor country reports of bilateral programs, which may differ from reports by recipient countries. Recipients may lack access to information on such aid expenditures as development-oriented research, stipends and tuition costs for aid-financed students in donor countries, and payment of experts hired by donor countries. Moreover, a full accounting would include donor country contributions to multilateral institutions, the flow of resources from multilateral institutions to recipient countries, and flows from countries that are not members of DAC.\n\nSome of the aid recipients are also aid donors. Development cooperation activities by non-DAC members have increased in recent years and in some cases surpass those of individual DAC members. Some non-DAC donors report their development cooperation activities to DAC on a voluntary basis, but many do not yet report their aid flows to DAC.","theme":"inter","source_group":"wb"},{"code":"BN.TRF.KOGT.CD","name":"Compte de capital net (balance des paiements, dollars américains courants)","description":"Le compte de capital net enregistre les acquisitions et les cessions d'actifs non financiers non produits, tels que les terrains vendus aux ambassa...","source_link":"https://donnees.banquemondiale.org/indicateur/BN.TRF.KOGT.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"FM.AST.DOMS.CN","name":"Crédit intérieur net (UCL courante)","description":"Le crédit intérieur net est la somme des créances nettes sur l’administration centrale et des créances sur d’autres secteurs de l’économie nationale.","source_link":"https://donnees.banquemondiale.org/indicateur/FM.AST.DOMS.CN?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"BN.KAC.EOMS.CD","name":"Erreurs et omissions nettes ($ US courants, BdP)","description":"Les erreurs et omissions nettes constituent une catégorie résiduelle nécessaire pour garantir que les comptes de la balance des paiements totalisen...","source_link":"https://donnees.banquemondiale.org/indicateur/BN.KAC.EOMS.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BN.FIN.TOTL.CD","name":"Compte financier net (balance des paiements, dollars américains courants)","description":"Le compte financier net présente les acquisitions et cessions nettes d’actifs et de passifs financiers.","source_link":"https://donnees.banquemondiale.org/indicateur/BN.FIN.TOTL.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"DT.NFL.BLAT.CD","name":"Flux financiers nets, bilatéraux (NFL, $ US courants)","description":"La dette bilatérale comprend les prêts des gouvernements et de leurs agences (y compris les banques centrales), les prêts d'organismes autonomes et...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.BLAT.CD?locations=CI","methodology":"Methodology: Data show concessional and nonconcessional financial flows from official bilateral sources. The Organisation for Economic Co-operation and Development's (OECD) Development Assistance Committee (DAC) defines concessional flows from bilateral donors as flows with a grant element of at least 25 percent; they are evaluated assuming a 10 percent nominal discount rate.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.MIBR.CD","name":"Flux financiers nets, BIRD (TNI, dollar américain courant)","description":"Les flux financiers nets reçus par l'emprunteur au cours de l'année sont les décaissements de prêts et crédits diminués des remboursements du princ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.MIBR.CD?locations=CI","methodology":"Methodology: The World Bank's International Bank for Reconstruction and Development (IBRD) lends to creditworthy countries at a variable base rate of six-month LIBOR plus a spread, either variable or fixed, for the life of the loan. The rate is reset every six months and applies to the interest period beginning on that date.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.MIDA.CD","name":"Flux financiers nets, IDA (NFL, $ US courants)","description":"Les flux financiers nets reçus par l'emprunteur au cours de l'année sont les décaissements de prêts et crédits diminués des remboursements du princ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.MIDA.CD?locations=CI","methodology":"Methodology: World Bank concessional lending is done by the International Development Association (IDA) based on gross national income (GNI) per capita and performance standards assessed by World Bank staff.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.IMFC.CD","name":"Flux financiers nets, concessionnels du FMI (NFL, $ US courants)","description":"Les flux financiers nets reçus par l'emprunteur au cours de l'année sont les décaissements de prêts et crédits diminués des remboursements du princ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.IMFC.CD?locations=CI","methodology":"Methodology: The International Monetary Fund (IMF) makes concessional funds available through its Extended Credit Facility (which replaced the Poverty Reduction and Growth Facility in 2010), the Standby Credit Facility, and the Rapid Credit Facility. Eligibility is based principally on a country's per capita income and eligibility under IDA.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.IMFN.CD","name":"Flux financiers nets, FMI non concessionnels (NFL, dollars américains courants)","description":"Les flux financiers nets reçus par l'emprunteur au cours de l'année sont les décaissements de prêts et crédits diminués des remboursements du princ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.IMFN.CD?locations=CI","methodology":"Methodology: Nonconcessional lending from the IMF is provided mainly through Stand-by Arrangements, the Flexible Credit Line, and the Extended Fund Facility.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.MLAT.CD","name":"Flux financiers nets, multilatéraux (NFL, $ US courants)","description":"Les prêts multilatéraux publics et garantis par l'État comprennent les prêts et crédits de la Banque mondiale, des banques régionales de développem...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.MLAT.CD?locations=CI","methodology":"Methodology: Data show concessional and nonconcessional financial flows from international financial institutions. International financial institutions fund nonconcessional lending operations primarily by selling low-interest, highly rated bonds backed by prudent lending and financial policies and the strong financial support of their members. Funds are then on-lent to developing countries at slightly higher interest rates with 15- to 20-year maturities. Lending terms vary with market conditions and institutional policies. Concessional flows from international financial institutions are credits provided through concessional lending facilities. Subsidies from donors or other resources reduce the cost of these loans. Grants are not included in net flows.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.MOTH.CD","name":"Flux financiers nets, autres (NFL, $ US courants)","description":"Les flux financiers nets reçus par l'emprunteur au cours de l'année sont les décaissements de prêts et crédits diminués des remboursements du princ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.MOTH.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.RDBC.CD","name":"Flux financiers nets, RDB concessionnel (NFL, $ US courants)","description":"Les flux financiers nets reçus par l'emprunteur au cours de l'année sont les décaissements de prêts et crédits diminués des remboursements du princ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.RDBC.CD?locations=CI","methodology":"Methodology: Regional Development Banks (RDB) share their lending information on a loan by loan basis with the World Bank through the World Bank's Debtor Reporting System (DRS). The Debt Data Team then compiles this information to produce this indicator.\nStatistical concept(s): Regional development banks also maintain concessional windows. Their loans are recorded according to each institution's classification and not according to the Organisation for Economic Co-operation and Development's (OECD) Development Assistance Committee (DAC) definition.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.RDBN.CD","name":"Flux financiers nets, RDB non concessionnels (NFL, $ US courants)","description":"Les flux financiers nets reçus par l'emprunteur au cours de l'année sont les décaissements de prêts et crédits diminués des remboursements du princ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.RDBN.CD?locations=CI","methodology":"Methodology: Regional Development Banks (RDB) share their lending information on a loan by loan basis with the World Bank through the World Bank's Debtor Reporting System (DRS). The Debt Data Team then compiles this information to produce this indicator.\nStatistical concept(s): Regional development banks also maintain concessional windows. Their loans are recorded according to each institution's classification and not according to the Organisation for Economic Co-operation and Development's (OECD) Development Assistance Committee (DAC) definition.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.DPNG.CD","name":"Flux nets sur la dette extérieure, privée non garantie (PNG) (NFL, $ US courants)","description":"La dette extérieure privée non garantie est une obligation extérieure d’un débiteur privé dont le remboursement n’est pas garanti par une entité pu...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.DPNG.CD?locations=CI","methodology":"Methodology: Countries that report to the World Bank’s Debtor Reporting System (DRS) submit their private nonguaranteed (PNG) on an aggregate basis. The Debt Data Team then compiles this information to produce this indicator.","theme":"finance","source_group":"wb"},{"code":"FM.AST.NFRG.CN","name":"Avoirs extérieurs nets (UCL courantes)","description":"Les avoirs extérieurs nets sont la somme des avoirs extérieurs détenus par les autorités monétaires et les banques de dépôt, moins leurs engagement...","source_link":"https://donnees.banquemondiale.org/indicateur/FM.AST.NFRG.CN?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"GC.LBL.TOTL.GD.ZS","name":"Engagement net des passifs, total ( % du PIB)","description":"L’augmentation nette des dettes publiques comprend le financement étranger (obtenu auprès de non-résidents) et le financement intérieur (obtenu aup...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.LBL.TOTL.GD.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.LBL.TOTL.CN","name":"Engagement net des passifs, total (LCU courant)","description":"L’augmentation nette des dettes publiques comprend le financement étranger (obtenu auprès de non-résidents) et le financement intérieur (obtenu aup...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.LBL.TOTL.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"SE.PRM.NINT.ZS","name":"Taux net d'admission en 1re année (en % de la population d'âge scolaire officiel)","description":"Le taux net d'admission en première année est le nombre de nouveaux inscrits en première année de l'enseignement primaire qui ont l'âge officiel d'...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.NINT.ZS?locations=CI","methodology":"Methodology: Net intake rate in the first grade of primary education is calculated by dividing the number of children of official primary school entrance age who enter grade 1 of primary education for the first time by the population of the same age, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.PRM.NINT.FE.ZS","name":"Taux net d'admission en 1re année, filles ( % de la population en âge d'être scolarisée)","description":"Le taux net d'admission en première année est le nombre de nouveaux inscrits en première année de l'enseignement primaire qui ont l'âge officiel d'...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.NINT.FE.ZS?locations=CI","methodology":"Methodology: Net intake rate in the first grade of primary education is calculated by dividing the number of children of official primary school entrance age who enter grade 1 of primary education for the first time by the population of the same age, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.PRM.NINT.MA.ZS","name":"Taux net d'admission en 1re année, garçons ( % de la population d'âge scolaire officiel)","description":"Le taux net d'admission en première année est le nombre de nouveaux inscrits en première année de l'enseignement primaire qui ont l'âge officiel d'...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.NINT.MA.ZS?locations=CI","methodology":"Methodology: Net intake rate in the first grade of primary education is calculated by dividing the number of children of official primary school entrance age who enter grade 1 of primary education for the first time by the population of the same age, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"GC.NFN.TOTL.GD.ZS","name":"Investissement net en actifs non financiers ( % du PIB)","description":"L'investissement net dans les actifs non financiers de l'État comprend les immobilisations, les stocks, les objets de valeur et les actifs non prod...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.NFN.TOTL.GD.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.NFN.TOTL.CN","name":"Investissement net en actifs non financiers (UCL courante)","description":"L'investissement net dans les actifs non financiers de l'État comprend les immobilisations, les stocks, les objets de valeur et les actifs non prod...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.NFN.TOTL.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.NLD.TOTL.GD.ZS","name":"Capacité (+) / besoin de financement (-) ( % du PIB)","description":"Le prêt net (+)/l'emprunt net (–) est égal aux recettes publiques moins les dépenses, moins l'investissement net en actifs non financiers.","source_link":"https://donnees.banquemondiale.org/indicateur/GC.NLD.TOTL.GD.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.NLD.TOTL.CN","name":"Capacité (+) / besoin de financement (-) (UCL courante)","description":"Le prêt net (+)/l'emprunt net (–) est égal aux recettes publiques moins les dépenses, moins l'investissement net en actifs non financiers.","source_link":"https://donnees.banquemondiale.org/indicateur/GC.NLD.TOTL.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"SM.POP.NETM","name":"Migration nette","description":"La migration nette est le total net des migrants au cours de la période, c'est-à-dire le nombre d'immigrants moins le nombre d'émigrants, y compris...","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.NETM?locations=CI","methodology":"Methodology: When there is insufficient data, net migration is derived through the difference between the overall population growth rate and the rate of natural increase (the difference between the birth rate and the death rate) during the same period. Such calculations are usually made for intercensal periods. The estimates are also derived from the data on foreign-born population - people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population - that is, people who are citizens of a country other than the country in which they reside - are used as estimates.\nStatistical concept(s): The United Nations Population Division provides data on net migration and migrant stock. Because data on migrant stock is difficult for countries to collect, the United Nations Population Division takes into account the past migration history of a country or area, the migration policy of a country, and the influx of refugees in recent periods when deriving estimates of net migration. The data to calculate these estimates come from a variety of sources, including border statistics, administrative records, surveys, and censuses.","theme":"demo","source_group":"wb"},{"code":"DC.ODA.TLDC.GN.ZS","name":"APD nette fournie aux pays les moins avancés ( % du RNB)","description":"L'aide publique au développement (APD) nette comprend les subventions ou les prêts aux pays et territoires en développement figurant sur la liste d...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.ODA.TLDC.GN.ZS?locations=CI","methodology":"Methodology: Disbursements by donors include both bilateral Official Development Assistance (ODA) flows to recipient countries and multilateral ODA contributions to eligible organizations. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is presented as a percentage of Gross National Income (GNI).","theme":"inter","source_group":"wb"},{"code":"DC.ODA.TLDC.CD","name":"APD nette fournie aux pays les moins avancés (en dollars courants)","description":"L'aide publique au développement (APD) nette comprend les subventions ou les prêts aux pays et territoires en développement figurant sur la liste d...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.ODA.TLDC.CD?locations=CI","methodology":"Methodology: Disbursements by donors include both bilateral Official Development Assistance (ODA) flows to recipient countries and multilateral ODA contributions to eligible organizations. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"inter","source_group":"wb"},{"code":"DC.ODA.TOTL.GN.ZS","name":"APD nette fournie, total ( % du RNB)","description":"L'aide publique au développement (APD) nette comprend les subventions ou les prêts aux pays et territoires en développement figurant sur la liste d...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.ODA.TOTL.GN.ZS?locations=CI","methodology":"Methodology: Disbursements by donors include both bilateral Official Development Assistance (ODA) flows to recipient countries and multilateral ODA contributions to eligible organizations. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is presented as a percentage of Gross National Income (GNI).","theme":"inter","source_group":"wb"},{"code":"DC.ODA.TOTL.KD","name":"APD nette fournie, total (en dollars constants de 2021)","description":"L'aide publique au développement (APD) nette comprend les subventions ou les prêts aux pays et territoires en développement figurant sur la liste d...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.ODA.TOTL.KD?locations=CI","methodology":"Methodology: Disbursements by donors include both bilateral Official Development Assistance (ODA) flows to recipient countries and multilateral ODA contributions to eligible organizations. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in constant U.S. dollar prices to account for inflation in the donor's currency and the changes in exchange rates with the U.S. dollar.","theme":"inter","source_group":"wb"},{"code":"DC.ODA.TOTL.CD","name":"APD nette fournie, total (en dollars américains courants)","description":"L'aide publique au développement (APD) nette comprend les subventions ou les prêts aux pays et territoires en développement figurant sur la liste d...","source_link":"https://donnees.banquemondiale.org/indicateur/DC.ODA.TOTL.CD?locations=CI","methodology":"Methodology: Disbursements by donors include both bilateral Official Development Assistance (ODA) flows to recipient countries and multilateral ODA contributions to eligible organizations. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"inter","source_group":"wb"},{"code":"DT.ODA.ODAT.XP.ZS","name":"APD nette reçue ( % des dépenses de l'administration centrale)","description":"L’aide publique au développement (APD) nette comprend les décaissements de prêts accordés à des conditions concessionnelles (nets des remboursement...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.ODA.ODAT.XP.ZS?locations=CI","methodology":"Methodology: Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nCentral government expense is cash payments for operating activities of the government in providing goods and services. It includes compensation of employees (such as wages and salaries), interest and subsidies, grants, social benefits, and other expenses such as rent and dividends.\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Net ODA received as a percent of central government expense is calculated using values in U.S. dollars converted using the DEC alternative conversion factor which is the underlying annual exchange rate used for the World Bank Atlas method.","theme":"inter","source_group":"wb"},{"code":"DT.ODA.ODAT.GN.ZS","name":"APD nette reçue (en % du RNB)","description":"L’aide publique au développement (APD) nette comprend les décaissements de prêts accordés à des conditions concessionnelles (nets des remboursement...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.ODA.ODAT.GN.ZS?locations=CI","methodology":"Methodology: The ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Net ODA received as a percent of GNI is calculated using values in U.S. dollars converted at official exchange rates.","theme":"inter","source_group":"wb"},{"code":"DT.ODA.ODAT.GI.ZS","name":"APD nette reçue ( % de la formation brute de capital)","description":"L’aide publique au développement (APD) nette comprend les décaissements de prêts accordés à des conditions concessionnelles (nets des remboursement...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.ODA.ODAT.GI.ZS?locations=CI","methodology":"Methodology: Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).Gross capital formation consists of outlays on additions to the conomy's fixed assets plus net changes in the level of inventories. It is generally obtained from industry reports of acquisitions and distinguishes only the broad categories of capital formation. Data on capital formation may be estimated from direct surveys of enterprises and administrative records or based on the commodity flow methods using data from production, trade and construction activities.\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Net ODA received as a percent of gross capital formation is calculated using values in U.S. dollars converted at official exchange rates.","theme":"inter","source_group":"wb"},{"code":"DT.ODA.ODAT.MP.ZS","name":"APD nette reçue ( % des importations de biens, de services et de revenus primaires)","description":"L’aide publique au développement (APD) nette comprend les décaissements de prêts accordés à des conditions concessionnelles (nets des remboursement...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.ODA.ODAT.MP.ZS?locations=CI","methodology":"Methodology: Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nData on imports are compiled from customs reports and balance of payments data. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services. They exclude compensation of employees and investment income (factor services in the 1969 SNA) and transfer payments.\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Net ODA received as a percent of imports of goods and services is calculated using values in U.S. dollars converted at official exchange rates.","theme":"inter","source_group":"wb"},{"code":"DT.ODA.ODAT.PC.ZS","name":"APD nette reçue par habitant (en dollars courants des États-Unis)","description":"L'aide publique au développement (APD) nette par habitant comprend les décaissements de prêts accordés à des conditions concessionnelles (nets des ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.ODA.ODAT.PC.ZS?locations=CI","methodology":"Methodology: Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nTotal population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship - except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. The values shown are midyear estimates. Net official development assistance per capita is net ODA divided by midyear population.\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat.\n\nThis definition excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance (ODA) estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database.","theme":"inter","source_group":"wb"},{"code":"DT.ODA.OATL.KD","name":"Aide publique nette reçue (en dollars constants de 2021)","description":"L’aide publique nette fait référence aux flux d’aide (nets de remboursements) des donateurs officiels vers les pays et territoires figurant dans la...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.ODA.OATL.KD?locations=CI","methodology":"Methodology: Net official aid refers to aid flows (net of repayments) from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. Data are in constant U.S. dollars.","theme":"inter","source_group":"wb"},{"code":"DT.ODA.OATL.CD","name":"Aide publique nette reçue (en dollars courants des États-Unis)","description":"L’aide publique nette fait référence aux flux d’aide (nets de remboursements) des donateurs officiels vers les pays et territoires figurant dans la...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.ODA.OATL.CD?locations=CI","methodology":"Methodology: Net official aid refers to aid flows (net of repayments) from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. Data are in current U.S. dollars.\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on donor reports on bilateral programs by DAC members using standard questionnaires issued by the DAC Secretariat. DAC has 24 members - 23 individual economies and 1 multilateral institution (European Union institutions). \n\nNet official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of DAC, by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Data are in current U.S. dollars.\n\nTotal net disbursements is the sum of grants, capital subscriptions (deposit basis), recoveries and total net loans and other long-term capital.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nNet official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance (ODA) estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Data are in current U.S. dollars.","theme":"inter","source_group":"wb"},{"code":"DT.ODA.ALLD.KD","name":"Aide publique au développement nette et aide publique reçue (en dollars constants de 2021)","description":"L’aide publique au développement (APD) nette comprend les décaissements de prêts accordés à des conditions concessionnelles (nets des remboursement...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.ODA.ALLD.KD?locations=CI","methodology":"Methodology: The flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on donor reports on bilateral programs by DAC members using standard questionnaires issued by the DAC Secretariat. DAC has 24 members - 23 individual economies and 1 multilateral institution (European Union institutions). \n\nNet official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of DAC, by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Data are in constant U.S. dollars.\n\nTotal net disbursements is the sum of grants, capital subscriptions (deposit basis), recoveries and total net loans and other long-term capital.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nNet official aid refers to aid flows (net of repayments) from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. Data are in current U.S. dollars.\n\nThe official development assistance (ODA) estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database.","theme":"inter","source_group":"wb"},{"code":"DT.ODA.ALLD.CD","name":"Aide publique au développement nette et aide publique reçue (en dollars courants)","description":"L’aide publique au développement (APD) nette comprend les décaissements de prêts accordés à des conditions concessionnelles (nets des remboursement...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.ODA.ALLD.CD?locations=CI","methodology":"Methodology: The flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on donor reports on bilateral programs by DAC members using standard questionnaires issued by the DAC Secretariat. DAC has 24 members - 23 individual economies and 1 multilateral institution (European Union institutions). \n\nNet official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of DAC, by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Data are in current U.S. dollars.\n\nTotal net disbursements is the sum of grants, capital subscriptions (deposit basis), recoveries and total net loans and other long-term capital.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nNet official aid refers to aid flows (net of repayments) from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. Data are in current U.S. dollars.\n\nThe official development assistance (ODA) estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database.","theme":"inter","source_group":"wb"},{"code":"DT.ODA.ODAT.KD","name":"Aide publique au développement nette reçue (en dollars constants de 2021)","description":"L’aide publique au développement (APD) nette comprend les décaissements de prêts accordés à des conditions concessionnelles (nets des remboursement...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.ODA.ODAT.KD?locations=CI","methodology":"Methodology: The flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on donor reports on bilateral programs by DAC members using standard questionnaires issued by the DAC Secretariat. DAC has 24 members - 23 individual economies and 1 multilateral institution (European Union institutions). \n\nNet official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of DAC, by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Data are in constant U.S. dollars.\n\nTotal net disbursements is the sum of grants, capital subscriptions (deposit basis), recoveries and total net loans and other long-term capital.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance (ODA) estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database.","theme":"inter","source_group":"wb"},{"code":"DT.ODA.ODAT.CD","name":"Aide publique au développement nette reçue (en dollars courants des États-Unis)","description":"L’aide publique au développement (APD) nette comprend les décaissements de prêts accordés à des conditions concessionnelles (nets des remboursement...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.ODA.ODAT.CD?locations=CI","methodology":"Methodology: The flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on donor reports on bilateral programs by DAC members using standard questionnaires issued by the DAC Secretariat. DAC has 24 members - 23 individual economies and 1 multilateral institution (European Union institutions). \n\nNet official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of DAC, by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Data are in current U.S. dollars.\n\nTotal net disbursements is the sum of grants, capital subscriptions (deposit basis), recoveries and total net loans and other long-term capital.\n\nThe ODA excludes nonconcessional flows from official creditors, which are classified as \"other official flows,\" and aid for military and anti-terrorism purposes. Transfer payments to private individuals, such as pensions, reparations, and insurance payouts, are in general not counted. In addition to financial flows, ODA includes technical cooperation, most expenditures for peacekeeping under UN mandates and assistance to refugees, contributions to multilateral institutions such as the United Nations and its specialized agencies, and concessional funding to multilateral development banks.\n\n\nFlows are transfers of resources, either in cash or in the form of commodities or services measured on a cash basis. Short-term capital transactions (with one year or less maturity) are not counted. Repayments of the principal (but not interest) of ODA loans are recorded as negative flows. Proceeds from official equity investments in a developing country are reported as ODA, while proceeds from their later sale are recorded as negative flows.\n\nThe official development assistance (ODA) estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database.","theme":"inter","source_group":"wb"},{"code":"DT.NFL.CERF.CD","name":"Flux officiels nets des agences des Nations Unies, CERF (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.CERF.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.FAOG.CD","name":"Flux officiels nets des agences des Nations Unies, FAO (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.FAOG.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.IAEA.CD","name":"Flux officiels nets des agences des Nations Unies, de l'AIEA (en dollars courants)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.IAEA.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.IFAD.CD","name":"Flux officiels nets des agences des Nations Unies, FIDA (en dollars courants US)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.IFAD.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.ILOG.CD","name":"Flux officiels nets des agences des Nations Unies, OIT (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.ILOG.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.SDGF.CD","name":"Flux officiels nets des agences de l'ONU, SDGFUND (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.SDGF.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.SPRP.CD","name":"Flux officiels nets des agences des Nations Unies, SPRP (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.SPRP.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNAI.CD","name":"Flux officiels nets des agences des Nations Unies et de l'ONUSIDA (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNAI.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNCD.CD","name":"Flux officiels nets des agences des Nations Unies, FENU (en dollars courants)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNCD.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNCV.CD","name":"Flux officiels nets des agences des Nations Unies, UNCOVID (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNCV.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNCTAD.CD","name":"Flux officiels nets des agences des Nations Unies, CNUCED (en dollars courants)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNCTAD.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNDP.CD","name":"Flux officiels nets des agences des Nations Unies, PNUD (en dollars courants)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNDP.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNEC.CD","name":"Flux officiels nets des organismes des Nations Unies, CEE (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNEC.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNEP.CD","name":"Flux officiels nets des agences des Nations Unies, PNUE (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNEP.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNFP.CD","name":"Flux officiels nets des agences des Nations Unies, FNUAP (en dollars courants)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNFP.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNCR.CD","name":"Flux officiels nets des agences des Nations Unies et du HCR (en dollars courants)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNCR.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNCF.CD","name":"Flux officiels nets provenant des agences des Nations Unies et de l'UNICEF (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNCF.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.\nStatistical concept(s): list()","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNID.CD","name":"Flux officiels nets des organismes des Nations Unies, UNIDIR (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNID.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNIDO.CD","name":"Flux officiels nets des agences des Nations Unies, de l'ONUDI (en dollars courants)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNIDO.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNPB.CD","name":"Flux officiels nets des agences des Nations Unies, FNUBNU (en dollars courants)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNPB.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNRW.CD","name":"Flux officiels nets des agences des Nations Unies, UNRWA (en dollars courants)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNRW.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNTA.CD","name":"Flux officiels nets des agences des Nations Unies, ATNU (en dollars courants)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNTA.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNWN.CD","name":"Flux officiels nets des agences des Nations Unies, ONU-Femmes (en dollars courants)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNWN.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.UNWT.CD","name":"Flux officiels nets des agences des Nations Unies, OMT (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.UNWT.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.WFPG.CD","name":"Flux officiels nets des agences des Nations Unies, PAM (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.WFPG.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.WHOL.CD","name":"Flux officiels nets des agences des Nations Unies et de l'OMS (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.WHOL.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.WITC.CD","name":"Flux officiels nets des agences des Nations Unies, OMC-ITC (en dollars courants des États-Unis)","description":"Les flux officiels nets des agences des Nations Unies correspondent aux décaissements nets du total des flux officiels des agences des Nations Unies.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.WITC.CD?locations=CI","methodology":"Methodology: Official flows from UN agencies indicate the net flow of funds. To calculate the net amount, the total disbursed during a specific accounting period is summed, and then any loan principal repayments (excluding interest) are subtracted. Disbursements represent the actual international transfer of financial resources, goods, or services at the donor's expense, occurring when funds are transferred to the service provider or recipient. For activities conducted within donor countries, such as training, disbursement is recorded once the funds are transferred. The data is expressed in U.S. dollars.","theme":"finance","source_group":"wb"},{"code":"BN.GSR.FCTY.CD","name":"Revenu primaire net ($ US courants, BdP)","description":"Le revenu primaire net comprend les composantes du revenu net du travail et du revenu net de la propriété et du revenu entrepreneurial du SCN.","source_link":"https://donnees.banquemondiale.org/indicateur/BN.GSR.FCTY.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"NY.GSR.NFCY.KN","name":"Revenu primaire net (revenu net tiré de l'étranger) (UCT constantes)","description":"Le revenu primaire net comprend les composantes du revenu net du travail et du revenu net de la propriété et du revenu entrepreneurial du SCN.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GSR.NFCY.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GSR.NFCY.CN","name":"Revenu primaire net (revenu net provenant de l'étranger) (LCU courante)","description":"Le revenu primaire net comprend les composantes du revenu net du travail et du revenu net de la propriété et du revenu entrepreneurial du SCN.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GSR.NFCY.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.GSR.NFCY.CD","name":"Revenu primaire net (revenu net provenant de l'étranger) (en dollars américains courants)","description":"Le revenu primaire net comprend les composantes du revenu net du travail et du revenu net de la propriété et du revenu entrepreneurial du SCN.","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GSR.NFCY.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"BN.TRF.CURR.CD","name":"Revenu secondaire net ($ US courants, balance des paiements)","description":"Le revenu secondaire net (en provenance de l'étranger) comprend les transferts de revenus entre les résidents du pays déclarant et le reste du mond...","source_link":"https://donnees.banquemondiale.org/indicateur/BN.TRF.CURR.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"NY.TRF.NCTR.KN","name":"Revenu secondaire net (transferts courants nets de l'étranger) (UCT constantes)","description":"Le revenu secondaire net (en provenance de l'étranger) comprend les transferts de revenus entre les résidents du pays déclarant et le reste du mond...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.TRF.NCTR.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.TRF.NCTR.CN","name":"Revenu secondaire net (transferts courants nets de l'étranger) (UCL courante)","description":"Le revenu secondaire net (en provenance de l'étranger) comprend les transferts de revenus entre les résidents du pays déclarant et le reste du mond...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.TRF.NCTR.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.TRF.NCTR.CD","name":"Revenu secondaire net (transferts courants nets de l'étranger) (en dollars courants des États-Unis)","description":"Le revenu secondaire net (en provenance de l'étranger) comprend les transferts de revenus entre les résidents du pays déclarant et le reste du mond...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.TRF.NCTR.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"BN.GSR.MRCH.CD","name":"Commerce net de biens ($ US courants, BdP)","description":"La balance du commerce international de biens est la différence entre les exportations et les importations de biens.","source_link":"https://donnees.banquemondiale.org/indicateur/BN.GSR.MRCH.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BN.GSR.GNFS.CD","name":"Commerce net de biens et de services ($ US courants, BdP)","description":"La balance du commerce international des biens et services est la différence entre les exportations et les importations de biens et services.","source_link":"https://donnees.banquemondiale.org/indicateur/BN.GSR.GNFS.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"IC.BUS.NDNS.ZS","name":"Densité des nouvelles entreprises (nouvelles inscriptions pour 1 000 personnes âgées de 15 à 64 ans)","description":"Le nombre d'entreprises à responsabilité limitée nouvellement enregistrées pour 1 000 personnes en âge de travailler (âgées de 15 à 64 ans) par ann...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BUS.NDNS.ZS?locations=CI","methodology":"Methodology: The Entrepreneurship Database has developed a data collection methodology to systematically measure entrepreneurial activity. To facilitate cross-country comparability, the Entrepreneurship Database employs a consistent unit of measurement, source of information, and concept of entrepreneurship that is applicable and available among the diverse sample of participating economies.\n\nThe data collection process involves telephone interviews and email correspondence with business registries. The main sources of information for this study are national business registries. In a limited number of cases where the business registry was unable to provide the data – most often due to an absence of digitized registration systems – the Entrepreneurship Database uses other alternatives sources, such as statistical agencies, tax and labor agencies, chambers of commerce, and publicly available data. \nStatistical concept(s): In order to measure entrepreneurship in a way that is universally comparable, the Entrepreneurship Database employs a methodology that can be applied across heterogeneous legal regimes and economic systems. The concept of entrepreneurship can cover a wide range of activities. For the purposes of this project, entrepreneurship is defined as the activities of an individual or a group of individuals aimed at initiating economic enterprise in the formal sector under a legal form of business.\n\nThe legal form of business refers to private companies with limited liability. Limited liability companies are those in which the financial liability of the firm’s members is limited to the value of their investment in the company. A limited liability company is a separate legal entity that has its own privileges and liabilities. Although the laws on business registration vary greatly across countries, the approach to legal entities is largely uniform: any business with a unique legal entity (or “corporate personhood”) separate from its owners must be registered.","theme":"business","source_group":"wb"},{"code":"IC.BUS.NREG","name":"Nouvelles entreprises enregistrées (nombre)","description":"Les nouvelles entreprises enregistrées correspondent au nombre de nouvelles sociétés à responsabilité limitée (ou son équivalent) enregistrées au c...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.BUS.NREG?locations=CI","methodology":"Methodology: The Entrepreneurship Database has developed a data collection methodology to systematically measure entrepreneurial activity. To facilitate cross-country comparability, the Entrepreneurship Database employs a consistent unit of measurement, source of information, and concept of entrepreneurship that is applicable and available among the diverse sample of participating economies.\n\nThe data collection process involves telephone interviews and email correspondence with business registries. The main sources of information for this study are national business registries. In a limited number of cases where the business registry was unable to provide the data – most often due to an absence of digitized registration systems – the Entrepreneurship Database uses other alternatives sources, such as statistical agencies, tax and labor agencies, chambers of commerce, and publicly available data. \nStatistical concept(s): In order to measure entrepreneurship in a way that is universally comparable, the Entrepreneurship Database employs a methodology that can be applied across heterogeneous legal regimes and economic systems. The concept of entrepreneurship can cover a wide range of activities. For the purposes of this project, entrepreneurship is defined as the activities of an individual or a group of individuals aimed at initiating economic enterprise in the formal sector under a legal form of business.\n\nThe legal form of business refers to private companies with limited liability. Limited liability companies are those in which the financial liability of the firm’s members is limited to the value of their investment in the company. A limited liability company is a separate legal entity that has its own privileges and liabilities. Although the laws on business registration vary greatly across countries, the approach to legal entities is largely uniform: any business with a unique legal entity (or “corporate personhood”) separate from its owners must be registered.","theme":"business","source_group":"wb"},{"code":"SH.VAC.TTNS.ZS","name":"Nouveau-nés protégés contre le tétanos ( %)","description":"Les nouveau-nés protégés contre le tétanos représentent le pourcentage de naissances de femmes en âge de procréer qui sont vaccinées contre le téta...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.VAC.TTNS.ZS?locations=CI","methodology":"Methodology: The data shown here are based on an assessment of national immunization coverage rates by the WHO and UNICEF. The assessment considered both administrative data from service providers and household survey data on children's immunization histories. Based on the data available, consideration of potential biases, and contributions of local experts, the most likely true level of immunization coverage was determined for each year.\nStatistical concept(s): Governments in developing countries usually finance immunization against measles and diphtheria, pertussis (whooping cough), and tetanus (DTP) as part of the basic public health package.","theme":"sante","source_group":"wb"},{"code":"EN.GHG.N2O.ZG.AR5","name":"Émissions de protoxyde d'azote (N2O) (total), à l'exclusion de l'UTCATF (variation en % par rapport à 1990)","description":"Variation des émissions (en %) de l'année en cours par rapport aux émissions de l'année de référence 1990 d'oxyde d'azote (N2O), l'un des six gaz à...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.N2O.ZG.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.N2O.MT.CE.AR5","name":"Émissions de protoxyde d'azote (N2O) (totales) à l'exclusion de l'ATCATF (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles d'oxyde d'azote (N2O), l'un des six gaz à effet de serre (GES) de Kyoto, provenant des secteurs de l'agriculture...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.N2O.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.N2O.AG.MT.CE.AR5","name":"Émissions de protoxyde d'azote (N2O) de l'agriculture (Mt CO2e)","description":"Une mesure des émissions annuelles d'oxyde nitreux (N2O), l'un des six gaz à effet de serre (GES) de Kyoto, provenant du secteur agricole.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.N2O.AG.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.N2O.BU.MT.CE.AR5","name":"Émissions de protoxyde d'azote (N2O) provenant du bâtiment (énergie) (Mt CO2e)","description":"Une mesure des émissions annuelles d'oxyde nitreux (N2O), l'un des six gaz à effet de serre (GES) de Kyoto, du secteur du bâtiment (sous-secteur du...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.N2O.BU.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.N2O.FE.MT.CE.AR5","name":"Émissions de protoxyde d'azote (N2O) provenant des émissions fugitives (énergie) (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles d'oxyde d'azote (N2O), l'un des six gaz à effet de serre (GES) de Kyoto, provenant des émissions fugitives (sous...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.N2O.FE.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.N2O.IC.MT.CE.AR5","name":"Émissions de protoxyde d'azote (N2O) provenant de la combustion industrielle (énergie) (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles d'oxyde nitreux (N2O), l'un des six gaz à effet de serre (GES) de Kyoto, provenant de la combustion industrielle...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.N2O.IC.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.N2O.IP.MT.CE.AR5","name":"Émissions de protoxyde d'azote (N2O) provenant des procédés industriels (Mt CO2e)","description":"Une mesure des émissions annuelles d'oxyde d'azote (N2O), l'un des six gaz à effet de serre (GES) de Kyoto, provenant des processus industriels, y ...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.N2O.IP.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.N2O.PI.MT.CE.AR5","name":"Émissions de protoxyde d'azote (N2O) de l'industrie de l'électricité (énergie) (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles d'oxyde nitreux (N2O), l'un des six gaz à effet de serre (GES) de Kyoto, provenant de la production d'électricit...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.N2O.PI.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.N2O.TR.MT.CE.AR5","name":"Émissions de protoxyde d'azote (N2O) provenant des transports (énergie) (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles d'oxyde d'azote (N2O), l'un des six gaz à effet de serre (GES) de Kyoto, provenant du secteur des transports (so...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.N2O.TR.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.N2O.WA.MT.CE.AR5","name":"Émissions de protoxyde d'azote (N2O) provenant des déchets (Mt CO2e)","description":"Une mesure des émissions annuelles d'oxyde nitreux (N2O), l'un des six gaz à effet de serre (GES) de Kyoto, provenant du secteur des déchets.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.N2O.WA.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"SH.DTH.1014","name":"Nombre de décès âgés de 10 à 14 ans","description":"Nombre de décès d'adolescents âgés de 10 à 14 ans","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DTH.1014?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.DTH.1519","name":"Nombre de décès chez les 15-19 ans","description":"Nombre de décès d'adolescents âgés de 15 à 19 ans","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DTH.1519?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.DTH.2024","name":"Nombre de décès : 20-24 ans","description":"Nombre de décès de jeunes âgés de 20 à 24 ans","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DTH.2024?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.DTH.0509","name":"Nombre de décès âgés de 5 à 9 ans","description":"Nombre de décès d'enfants âgés de 5 à 9 ans","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DTH.0509?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.DTH.IMRT","name":"Nombre de décès infantiles","description":"Nombre de nourrissons mourant avant l’âge d’un an.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DTH.IMRT?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.MMR.DTHS","name":"Nombre de décès maternels","description":"Un décès maternel fait référence au décès d'une femme pendant la grossesse ou dans les 42 jours suivant l'interruption de la grossesse, quels que s...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.MMR.DTHS?locations=CI","methodology":"Methodology: The estimates are based on an exercise by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) which consists of World Health Organization (WHO), United Nations Children's Fund (UNICEF), World Bank, and United Nations Population Fund (UNFPA), and include country-level time series data. For countries without complete registration data but with other types of data and for countries with no data, maternal mortality is estimated with a regression model using available national maternal mortality data and socioeconomic information.\nStatistical concept(s): Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\nMaternal mortality is generally of unknown reliability, as are many other cause-specific mortality indicators. Household surveys such as Demographic and Health Surveys attempt to measure maternal mortality by asking respondents about survivorship of sisters. The main disadvantage of this method is that the estimates of maternal mortality that it produces pertain to any time within the past few years before the survey, making them unsuitable for monitoring recent changes or observing the impact of interventions. In addition, measurement of maternal mortality is subject to many types of errors. Even in high-income countries with reliable vital registration systems, misclassification of maternal deaths has been found to lead to serious underestimation.","theme":"sante","source_group":"wb"},{"code":"SH.DTH.NMRT","name":"Nombre de décès néonatals","description":"Nombre de nouveau-nés décédés avant l'âge de 28 jours.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DTH.NMRT?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.SGR.PROC.P5","name":"Nombre d'interventions chirurgicales (pour 100 000 habitants)","description":"Le nombre d'interventions réalisées dans une salle d'opération pour 100 000 habitants par an dans chaque pays.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.SGR.PROC.P5?locations=CI","methodology":"Methodology: The number of procedures undertaken in an operating theatre per 100 000 population per year in each country. A procedure is defined as the incision, excision, or manipulation of tissue that needs regional or general anaesthesia, or profound sedation to control pain.\nStatistical concept(s): The Lancet Commission on Global Surgery, assembled in 2013 to assess surgical care around the world. Commissioners engaged in an iterative global consultative process with partners in over 110 countries to develop six core indicators of the strength of a surgical system. Two indicators assess a country’s preparedness to deliver safe surgery and anesthesia,  two assess the current delivery of safe care, and two assess the state of financial risk protection for those seeking surgery.","theme":"sante","source_group":"wb"},{"code":"SH.DTH.MORT","name":"Nombre de décès d'enfants de moins de cinq ans","description":"Nombre d'enfants qui meurent avant d'atteindre l'âge de cinq ans.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DTH.MORT?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"IC.TAX.METG","name":"Nombre de visites ou de rencontres requises avec des agents du fisc (moyenne pour les entreprises touchées)","description":"Nombre moyen de visites ou de réunions requises avec les agents du fisc.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.TAX.METG?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.\n\nPlease also refer to the methodology information on the Enterprise Surveys site: https://www.enterprisesurveys.org/en/methodology","theme":"business","source_group":"wb"},{"code":"SH.MED.NUMW.P3","name":"Infirmières et sages-femmes (pour 1 000 personnes)","description":"Les infirmières et les sages-femmes comprennent les infirmières professionnelles, les sages-femmes professionnelles, les infirmières auxiliaires, l...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.MED.NUMW.P3?locations=CI","methodology":"Methodology: National focal points share the data with WHO through the online NHWA data platform. The platform hosted in WHO, is built to facilitate data reporting on the indicators listed in the NHWA Handbook and data sharing across all the 3 levels of WHO.\nStatistical concept(s): Health systems - the combined arrangements of institutions and actions whose primary purpose is to promote, restore, or maintain health (World Health Organization, World Health Report 2000) - are increasingly being recognized as key to combating disease and improving the health status of populations. The World Bank's Healthy Development: Strategy for Health, Nutrition, and Population Results emphasizes the need to strengthen health systems, which are weak in many countries, in order to increase the effectiveness of programs aimed at reducing specific diseases and further reduce morbidity and mortality. To evaluate health systems, the World Health Organization (WHO) has recommended that key components - such as financing, service delivery, workforce, governance, and information - be monitored using several key indicators. The data are a subset of the key indicators. Monitoring health systems allows the effectiveness, efficiency, and equity of different health system models to be compared. Health system data also help identify weaknesses and strengths and areas that need investment, such as additional health facilities, better health information systems, or better trained human resources.\nData on health worker (physicians, nurses and midwives, and community health workers) density show the availability of medical personnel.","theme":"sante","source_group":"wb"},{"code":"PA.NUS.FCRF","name":"Taux de change officiel (UCL par dollar EU, moyenne de la période)","description":"Le taux de change officiel fait référence au taux de change déterminé par les autorités nationales ou au taux déterminé sur le marché des changes l...","source_link":"https://donnees.banquemondiale.org/indicateur/PA.NUS.FCRF?locations=CI","methodology":"Methodology: The exchange rate is the price of one currency divided by another. Official exchange rates and exchange rate arrangements are established by governments. Other exchange rates recognized by governments include market rates, which are determined largely by legal market forces, and for countries with multiple exchange arrangements, principal rates, secondary rates, and tertiary rates. Annual average exchange rates are derived as the simple average of daily exchange rates for a specified calendar year\nStatistical concept(s): The exchange rate is the price of one currency in terms of another. Official exchange rates and exchange rate arrangements are established by governments. Other exchange rates recognized by governments include market rates, which are determined largely by legal market forces, and for countries with multiple exchange arrangements, principal rates, secondary rates, and tertiary rates.","theme":"macro","source_group":"wb"},{"code":"NY.GDP.PETR.RT.ZS","name":"Rentes pétrolières ( % du PIB)","description":"Les rentes pétrolières correspondent à la différence entre la valeur de la production de pétrole brut aux prix régionaux et les coûts totaux de pro...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.PETR.RT.ZS?locations=CI","methodology":"Methodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).","theme":"secondary","source_group":"wb"},{"code":"TX.VAL.MMTL.ZS.UN","name":"Exportations de minerais et de métaux ( % des exportations de marchandises)","description":"Les minerais et les métaux comprennent les produits de la section 27 de la CTCI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.MMTL.ZS.UN?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.MMTL.ZS.UN","name":"Importations de minerais et de métaux ( % des importations de marchandises)","description":"Les minerais et les métaux comprennent les produits de la section 27 de la CTCI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.MMTL.ZS.UN?locations=CI","methodology":"Methodology: International merchandise trade statistics are compiled in accordance with international standards: International Merchandise Trade statistics – Concepts and Definitions 2010. Specific information on how countries compile their merchandise trade statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis for international merchandise trade statistics covers a specialized multipurpose domain of official statistics concerned with the provision of data on the movements of goods between countries and areas. Trade statistics are compiled to serve the needs of many users, including Governments; the business community; compilers of other economic statistics, such as balance of payments and national accounts; various regional, supranational and international organizations; researchers; and the public at large. Different users need different data, ranging from data sets by country and commodity at varying levels of detail to aggregated figures.","theme":"inter","source_group":"wb"},{"code":"GC.XPN.OTHR.ZS","name":"Autres charges ( % de la dépense)","description":"Les autres dépenses comprennent les dépenses en dividendes, loyers et autres dépenses diverses, y compris la provision pour la consommation de capi...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.OTHR.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.XPN.OTHR.CN","name":"Autres charges (LCU courantes)","description":"Les autres dépenses comprennent les dépenses en dividendes, loyers et autres dépenses diverses, y compris la provision pour la consommation de capi...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.OTHR.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"NV.MNF.OTHR.ZS.UN","name":"Autres industries manufacturières ( % de la valeur ajoutée dans l'industrie manufacturière)","description":"Les autres industries manufacturières, résiduelles, couvrent le bois et les produits connexes (CITI Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.MNF.OTHR.ZS.UN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"SM.POP.OPIP.EA","name":"Autres personnes ayant besoin d'une protection internationale par pays ou territoire d'asile","description":"Les autres personnes ayant besoin d’une protection internationale font référence aux personnes qui se trouvent hors de leur pays ou territoire d’or...","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.OPIP.EA?locations=CI","methodology":"Methodology: Data collection on other people in need of international protection involves methodologies similar to those used for refugees and asylum-seekers. \n\n\n\nData is primarily collected through administrative records, which track the number of individuals identified as needing international protection but who do not fall under the traditional definitions of refugees or asylum-seekers. These records are often supplemented by data from humanitarian operations and targeted surveys conducted in areas experiencing large-scale displacement.\n\n\n\nSince 2018, the Office of the United Nations High Commissioner for Refugees (UNHCR) has expanded its statistical frameworks to include this category, reflecting the growing recognition of the diverse forms of displacement and protection needs that exist beyond the traditional categories. The methodology for collecting and reporting data on these populations ensures that they are accurately represented in global statistics, and are comprehensive and comparable across different regions and timeframes, supporting more targeted and effective protection responses.","theme":"demo","source_group":"wb"},{"code":"SM.POP.OPIP.EO","name":"Autres personnes ayant besoin d'une protection internationale par pays ou territoire d'origine","description":"Les autres personnes ayant besoin d’une protection internationale font référence aux personnes qui se trouvent hors de leur pays ou territoire d’or...","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.OPIP.EO?locations=CI","methodology":"Methodology: Data collection on other people in need of international protection involves methodologies similar to those used for refugees and asylum-seekers. \n\n\n\nData is primarily collected through administrative records, which track the number of individuals identified as needing international protection but who do not fall under the traditional definitions of refugees or asylum-seekers. These records are often supplemented by data from humanitarian operations and targeted surveys conducted in areas experiencing large-scale displacement.\n\n\n\nSince 2018, the Office of the United Nations High Commissioner for Refugees (UNHCR) has expanded its statistical frameworks to include this category, reflecting the growing recognition of the diverse forms of displacement and protection needs that exist beyond the traditional categories. The methodology for collecting and reporting data on these populations ensures that they are accurately represented in global statistics, and are comprehensive and comparable across different regions and timeframes, supporting more targeted and effective protection responses.","theme":"demo","source_group":"wb"},{"code":"GC.TAX.OTHR.RV.ZS","name":"Autres impôts ( % du chiffre d'affaires)","description":"Les autres impôts comprennent les charges sociales des employeurs ou les taxes sur le travail, les impôts sur la propriété et les impôts non imputa...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.OTHR.RV.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.TAX.OTHR.CN","name":"Autres impôts (LCU courants)","description":"Les autres impôts comprennent les charges sociales des employeurs ou les taxes sur le travail, les impôts sur la propriété et les impôts non imputa...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.OTHR.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"SH.XPD.OOPC.CH.ZS","name":"Reste à charge ( % des dépenses courantes de santé)","description":"Part des paiements directs dans le total des dépenses courantes de santé.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.OOPC.CH.ZS?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making. Aggregations are weighted by total current health expenditure (not by population).\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.OOPC.PC.CD","name":"Dépenses directes par habitant (en dollars courants des États-Unis)","description":"Dépenses de santé au moyen de paiements directs par habitant en USD.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.OOPC.PC.CD?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SH.XPD.OOPC.PP.CD","name":"Dépenses directes par habitant, PPA (en dollars internationaux courants)","description":"Dépenses de santé au moyen de paiements directs par habitant en dollars internationaux à parité de pouvoir d'achat.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.XPD.OOPC.PP.CD?locations=CI","methodology":"Methodology: The Health SHA 2011 tracks all health spending in a given country over a defined period of time regardless of the entity or institution that financed and managed that spending. It generates consistent and comprehensive data on health spending in a country, which in turn can contribute to evidence-based policy-making. WHO converted the expenditure data using PPP time series extracted from WDI (based on ICP 2017) and OECD data. Where WDI/OECD data were not available, IMF or WHO estimates were utilized. Detailed metadata are available at <https://apps.who.int/nha/database/Select/Indicators/en>.\nStatistical concept(s): The health expenditure estimates have been prepared by the World Health Organization under the framework of the System of Health Accounts 2011 (SHA 2011).","theme":"sante","source_group":"wb"},{"code":"SE.PRM.OENR.ZS","name":"Élèves ayant dépassé l'âge limite dans le primaire ( % des inscriptions)","description":"Les élèves trop âgés représentent le pourcentage des inscrits qui sont plus âgés que la tranche d'âge scolaire officielle pour l'enseignement prima...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.OENR.ZS?locations=CI","methodology":"Methodology: The percentage of over-age students is calculated by dividing the number of students who are older than the official school-age range for primary education by primary school enrollment, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.PRM.OENR.FE.ZS","name":"Élèves ayant dépassé l'âge limite de l'enseignement primaire, de sexe féminin ( % des inscriptions féminines)","description":"Les élèves trop âgés représentent le pourcentage des inscrits qui sont plus âgés que la tranche d'âge scolaire officielle pour l'enseignement prima...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.OENR.FE.ZS?locations=CI","methodology":"Methodology: The percentage of over-age students is calculated by dividing the number of students who are older than the official school-age range for primary education by primary school enrollment, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.PRM.OENR.MA.ZS","name":"Élèves ayant dépassé l'âge limite dans l'enseignement primaire (en % des inscriptions masculines)","description":"Les élèves trop âgés représentent le pourcentage des inscrits qui sont plus âgés que la tranche d'âge scolaire officielle pour l'enseignement prima...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.OENR.MA.ZS?locations=CI","methodology":"Methodology: The percentage of over-age students is calculated by dividing the number of students who are older than the official school-age range for primary education by primary school enrollment, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SL.TLF.PART.FE.ZS","name":"Emploi à temps partiel, femmes ( % de l'emploi féminin total)","description":"Le taux d'emploi à temps partiel représente le pourcentage d'emploi à temps partiel.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.PART.FE.ZS?locations=CI","methodology":"Methodology: Labor force surveys are typically the preferred source of information on hours of work. Such surveys can be designed to cover virtually the entire non-institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders.\n\nOther types of household surveys could also be used as sources of data on hours of work, if they have an appropriate module on the topic.\n\nIn the absence of a labor force survey or other types of household surveys with a module on working time, an establishment survey can be used as a source of statistics on hours of work. However, the statistics derived from establishments surveys would typically not refer to the whole employed population but only to employees (and often only to formal sector employees or non-agricultural formal sector employees).\nStatistical concept(s): Employment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.PART.MA.ZS","name":"Emploi à temps partiel, hommes ( % de l'emploi masculin total)","description":"Le taux d'emploi à temps partiel représente le pourcentage d'emploi à temps partiel.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.PART.MA.ZS?locations=CI","methodology":"Methodology: Labor force surveys are typically the preferred source of information on hours of work. Such surveys can be designed to cover virtually the entire non-institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders.\n\nOther types of household surveys could also be used as sources of data on hours of work, if they have an appropriate module on the topic.\n\nIn the absence of a labor force survey or other types of household surveys with a module on working time, an establishment survey can be used as a source of statistics on hours of work. However, the statistics derived from establishments surveys would typically not refer to the whole employed population but only to employees (and often only to formal sector employees or non-agricultural formal sector employees).\nStatistical concept(s): Employment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.PART.ZS","name":"Emploi à temps partiel, total ( % de l'emploi total)","description":"Le taux d'emploi à temps partiel représente le pourcentage d'emploi à temps partiel.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.PART.ZS?locations=CI","methodology":"Methodology: Labor force surveys are typically the preferred source of information on hours of work. Such surveys can be designed to cover virtually the entire non-institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders.\n\nOther types of household surveys could also be used as sources of data on hours of work, if they have an appropriate module on the topic.\n\nIn the absence of a labor force survey or other types of household surveys with a module on working time, an establishment survey can be used as a source of statistics on hours of work. However, the statistics derived from establishments surveys would typically not refer to the whole employed population but only to employees (and often only to formal sector employees or non-agricultural formal sector employees).\nStatistical concept(s): Employment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).","theme":"emploi","source_group":"wb"},{"code":"IP.PAT.NRES","name":"Demandes de brevets, non-résidents","description":"Les demandes de brevet sont des demandes de brevet mondiales déposées via la procédure du Traité de coopération en matière de brevets ou auprès d'u...","source_link":"https://donnees.banquemondiale.org/indicateur/IP.PAT.NRES?locations=CI","methodology":"Methodology: Non-resident patent applications are from applicants outside the relevant State or region. Patent data cover applications and grants classified by field of technology. International applications series distinguish four subcategories: a) patents taken out by residents of a country in that country; b) patents taken out in a country by non-residents of that country; c) total patents registered in the country or naming it; d) patents taken out outside a country by its residents. Data on patents granted only distinguish between patents awarded to residents and to non-residents. A patent provides protection for the invention to the owner of the patent for a limited period, generally 20 years.\n\nPatent applications are worldwide patent applications filed through the Patent Cooperation Treaty procedure or with a national patent office for exclusive rights for an invention - a product or process that provides a new way of doing something or offers a new technical solution to a problem.","theme":"business","source_group":"wb"},{"code":"IP.PAT.RESD","name":"Demandes de brevets, résidents","description":"Les demandes de brevet sont des demandes de brevet mondiales déposées via la procédure du Traité de coopération en matière de brevets ou auprès d'u...","source_link":"https://donnees.banquemondiale.org/indicateur/IP.PAT.RESD?locations=CI","methodology":"Methodology: Resident patent applications are those for which the first-named applicant or assignee is a resident of the State or region concerned. In the case of regional offices such as the European Patent Office, a resident is an applicant from any of the member States of the regional patent convention.\n\nPatent data cover applications and grants classified by field of technology. International applications series distinguish four subcategories: a) patents taken out by residents of a country in that country; b) patents taken out in a country by non-residents of that country; c) total patents registered in the country or naming it; d) patents taken out outside a country by its residents. Data on patents granted only distinguish between patents awarded to residents and to non-residents. A patent provides protection for the invention to the owner of the patent for a limited period, generally 20 years.\n\nPatent applications are worldwide patent applications filed through the Patent Cooperation Treaty procedure or with a national patent office for exclusive rights for an invention - a product or process that provides a new way of doing something or offers a new technical solution to a problem.","theme":"business","source_group":"wb"},{"code":"SH.STA.ODFC.ZS","name":"Personnes pratiquant la défécation à l'air libre ( % de la population)","description":"Les personnes pratiquant la défécation à l'air libre font référence au pourcentage de la population déféquant à l'air libre, comme dans les champs,...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.ODFC.ZS?locations=CI","methodology":"Methodology: The data sources for sanitation services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and open defecation (Reference: https://washdata.org/monitoring/sanitation).","theme":"sante","source_group":"wb"},{"code":"SH.STA.ODFC.RU.ZS","name":"Pratiquants de la défécation à l'air libre, ruraux ( % de la population rurale)","description":"Les personnes pratiquant la défécation à l'air libre font référence au pourcentage de la population déféquant à l'air libre, comme dans les champs,...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.ODFC.RU.ZS?locations=CI","methodology":"Methodology: The data sources for sanitation services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and open defecation (Reference: https://washdata.org/monitoring/sanitation).","theme":"sante","source_group":"wb"},{"code":"SH.STA.ODFC.UR.ZS","name":"Personnes pratiquant la défécation à l'air libre, urbaines ( % de la population urbaine)","description":"Les personnes pratiquant la défécation à l'air libre font référence au pourcentage de la population déféquant à l'air libre, comme dans les champs,...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.ODFC.UR.ZS?locations=CI","methodology":"Methodology: The data sources for sanitation services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and open defecation (Reference: https://washdata.org/monitoring/sanitation).","theme":"sante","source_group":"wb"},{"code":"SH.H2O.BASW.ZS","name":"Personnes utilisant au moins les services d'eau potable de base ( % de la population)","description":"Le pourcentage de personnes utilisant au moins les services d’eau de base.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.H2O.BASW.ZS?locations=CI","methodology":"Methodology: The data sources for drinking water services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and surface water (Reference: https://washdata.org/monitoring/drinking-water). This indicator encompasses both people using basic water services as well as those using safely managed water services.","theme":"territory","source_group":"wb"},{"code":"SH.H2O.BASW.RU.ZS","name":"Personnes utilisant au moins les services d'eau potable de base, zones rurales ( % de la population rurale)","description":"Le pourcentage de personnes utilisant au moins les services d’eau de base.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.H2O.BASW.RU.ZS?locations=CI","methodology":"Methodology: The data sources for drinking water services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and surface water (Reference: https://washdata.org/monitoring/drinking-water). This indicator encompasses both people using basic water services as well as those using safely managed water services.","theme":"territory","source_group":"wb"},{"code":"SH.H2O.BASW.UR.ZS","name":"Personnes utilisant au moins des services d'eau potable de base, en milieu urbain ( % de la population urbaine)","description":"Le pourcentage de personnes utilisant au moins les services d’eau de base.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.H2O.BASW.UR.ZS?locations=CI","methodology":"Methodology: The data sources for drinking water services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and surface water (Reference: https://washdata.org/monitoring/drinking-water). This indicator encompasses both people using basic water services as well as those using safely managed water services.","theme":"territory","source_group":"wb"},{"code":"SH.STA.BASS.ZS","name":"Personnes utilisant au moins des services d'assainissement de base ( % de la population)","description":"Le pourcentage de personnes utilisant au moins les services d’assainissement de base, c’est-à-dire des installations sanitaires améliorées qui ne s...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.BASS.ZS?locations=CI","methodology":"Methodology: The data sources for sanitation services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and open defecation (Reference: https://washdata.org/monitoring/sanitation).  This indicator encompasses both people using basic sanitation services as well as those using safely managed sanitation services.","theme":"sante","source_group":"wb"},{"code":"SH.STA.BASS.RU.ZS","name":"Personnes utilisant au moins des services d'assainissement de base, zones rurales ( % de la population rurale)","description":"Le pourcentage de personnes utilisant au moins les services d’assainissement de base, c’est-à-dire des installations sanitaires améliorées qui ne s...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.BASS.RU.ZS?locations=CI","methodology":"Methodology: The data sources for sanitation services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and open defecation (Reference: https://washdata.org/monitoring/sanitation).  This indicator encompasses both people using basic sanitation services as well as those using safely managed sanitation services.","theme":"sante","source_group":"wb"},{"code":"SH.STA.BASS.UR.ZS","name":"Personnes utilisant au moins des services d'assainissement de base, urbaines ( % de la population urbaine)","description":"Le pourcentage de personnes utilisant au moins les services d’assainissement de base, c’est-à-dire des installations sanitaires améliorées qui ne s...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.BASS.UR.ZS?locations=CI","methodology":"Methodology: The data sources for sanitation services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and open defecation (Reference: https://washdata.org/monitoring/sanitation).  This indicator encompasses both people using basic sanitation services as well as those using safely managed sanitation services.","theme":"sante","source_group":"wb"},{"code":"SH.H2O.SMDW.ZS","name":"Personnes utilisant des services d'eau potable gérés en toute sécurité ( % de la population)","description":"Le pourcentage de personnes utilisant de l’eau potable provenant d’une source améliorée qui est accessible sur place, disponible en cas de besoin e...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.H2O.SMDW.ZS?locations=CI","methodology":"Methodology: The data sources for drinking water services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): Safely managed drinking water services are defined as the water from an improved source that is accessible on premises, available when needed and free from faecal and priority chemical contamination. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.  The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and surface water (Reference: https://washdata.org/monitoring/drinking-water).","theme":"territory","source_group":"wb"},{"code":"SH.H2O.SMDW.RU.ZS","name":"Personnes utilisant des services d'eau potable gérés en toute sécurité, zones rurales ( % de la population rurale)","description":"Le pourcentage de personnes utilisant de l’eau potable provenant d’une source améliorée qui est accessible sur place, disponible en cas de besoin e...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.H2O.SMDW.RU.ZS?locations=CI","methodology":"Methodology: The data sources for drinking water services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): Safely managed drinking water services are defined as the water from an improved source that is accessible on premises, available when needed and free from faecal and priority chemical contamination. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.  The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and surface water (Reference: https://washdata.org/monitoring/drinking-water).","theme":"territory","source_group":"wb"},{"code":"SH.H2O.SMDW.UR.ZS","name":"Personnes utilisant des services d'eau potable gérés en toute sécurité, urbaines ( % de la population urbaine)","description":"Le pourcentage de personnes utilisant de l’eau potable provenant d’une source améliorée qui est accessible sur place, disponible en cas de besoin e...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.H2O.SMDW.UR.ZS?locations=CI","methodology":"Methodology: The data sources for drinking water services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): Safely managed drinking water services are defined as the water from an improved source that is accessible on premises, available when needed and free from faecal and priority chemical contamination. Improved water sources include piped water, boreholes or tubewells, protected dug wells, protected springs, and packaged or delivered water.  The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and surface water (Reference: https://washdata.org/monitoring/drinking-water).","theme":"territory","source_group":"wb"},{"code":"SH.STA.SMSS.ZS","name":"Personnes utilisant des services d'assainissement gérés en toute sécurité ( % de la population)","description":"Le pourcentage de personnes utilisant des installations sanitaires améliorées qui ne sont pas partagées avec d’autres ménages et où les excréments ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.SMSS.ZS?locations=CI","methodology":"Methodology: The data sources for sanitation services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): Safely managed sanitation facilities are defined as improved sanitation facilities that are not shared with other households and where excreta are safely disposed of in situ or transported and treated offsite.  Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines: ventilated improved pit latrines, compositing toilets or pit latrines with slabs.  The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and open defecation (Reference: https://washdata.org/monitoring/sanitation).","theme":"sante","source_group":"wb"},{"code":"SH.STA.SMSS.RU.ZS","name":"Personnes utilisant des services d'assainissement gérés en toute sécurité, zones rurales ( % de la population rurale)","description":"Le pourcentage de personnes utilisant des installations sanitaires améliorées qui ne sont pas partagées avec d’autres ménages et où les excréments ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.SMSS.RU.ZS?locations=CI","methodology":"Methodology: The data sources for sanitation services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): Safely managed sanitation facilities are defined as improved sanitation facilities that are not shared with other households and where excreta are safely disposed of in situ or transported and treated offsite.  Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines: ventilated improved pit latrines, compositing toilets or pit latrines with slabs.  The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and open defecation (Reference: https://washdata.org/monitoring/sanitation).","theme":"sante","source_group":"wb"},{"code":"SH.STA.SMSS.UR.ZS","name":"Personnes utilisant des services d'assainissement gérés en toute sécurité, urbaines ( % de la population urbaine)","description":"Le pourcentage de personnes utilisant des installations sanitaires améliorées qui ne sont pas partagées avec d’autres ménages et où les excréments ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.SMSS.UR.ZS?locations=CI","methodology":"Methodology: The data sources for sanitation services are household surveys such as Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), administrative data, census, and other datasets such as compilations by international or regional initiatives (e.g., IB-NET) or studies conducted by research institutions. Based on these national datasets, JMP estimates the proportion of the people accessing different levels of services by using linear regression. You can find the details of estimates including the rules on interpolation, extrapolation and extension in the JMP’s methodology report (https://washdata.org/reports/jmp-2017-methodology).\nStatistical concept(s): Safely managed sanitation facilities are defined as improved sanitation facilities that are not shared with other households and where excreta are safely disposed of in situ or transported and treated offsite.  Improved sanitation facilities include flush/pour flush to piped sewer systems, septic tanks or pit latrines: ventilated improved pit latrines, compositing toilets or pit latrines with slabs.  The JMP classifies the sanitation service levels into five tiers, ranging from the most to the least favorable: safely managed, basic, limited, unimproved, and open defecation (Reference: https://washdata.org/monitoring/sanitation).","theme":"sante","source_group":"wb"},{"code":"SH.STA.HYGN.ZS","name":"Personnes disposant d'installations de base pour se laver les mains, y compris de l'eau et du savon ( % de la population)","description":"Le pourcentage de personnes vivant dans des ménages disposant d’une installation de lavage des mains avec de l’eau et du savon disponibles sur place.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.HYGN.ZS?locations=CI","methodology":"Methodology: Utilizing national-level data derived from household surveys, mainly the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), the JMP calculates the proportion of the population with access to basic handwashing facilities at home with soap and water for each country by using a simple linear regression.\nStatistical concept(s): This indicator is measured using a straightforward indicator that examines the presence of handwashing facilities with soap within homes mainly through national household surveys. \nCollecting accurate information on handwashing practices presents challenges. Self-reported handwashing is an unreliable measure due to the potential for inaccurate reporting. Direct observation of handwashing can lead to observer bias, as individuals may alter their behavior when they know they are being watched, and implementing such observations on a large scale is resource-intensive. A more effective method involves survey enumerators observing the designated handwashing areas in homes and verifying the availability of water and soap, or a local substitute. This approach provides a more dependable and practical measure of handwashing behavior than relying on self-reported data.","theme":"sante","source_group":"wb"},{"code":"SH.STA.HYGN.RU.ZS","name":"Personnes disposant d'installations de base pour se laver les mains, y compris de l'eau et du savon, zones rurales ( % de la population rurale)","description":"Le pourcentage de personnes vivant dans des ménages disposant d’une installation de lavage des mains avec de l’eau et du savon disponibles sur place.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.HYGN.RU.ZS?locations=CI","methodology":"Methodology: Utilizing national-level data derived from household surveys, mainly the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), the JMP calculates the proportion of the population with access to basic handwashing facilities at home with soap and water for each country by using a simple linear regression.\nStatistical concept(s): This indicator is measured using a straightforward indicator that examines the presence of handwashing facilities with soap within homes mainly through national household surveys. \nCollecting accurate information on handwashing practices presents challenges. Self-reported handwashing is an unreliable measure due to the potential for inaccurate reporting. Direct observation of handwashing can lead to observer bias, as individuals may alter their behavior when they know they are being watched, and implementing such observations on a large scale is resource-intensive. A more effective method involves survey enumerators observing the designated handwashing areas in homes and verifying the availability of water and soap, or a local substitute. This approach provides a more dependable and practical measure of handwashing behavior than relying on self-reported data.","theme":"sante","source_group":"wb"},{"code":"SH.STA.HYGN.UR.ZS","name":"Personnes disposant d'installations de base pour se laver les mains, y compris de l'eau et du savon, urbaines ( % de la population urbaine)","description":"Le pourcentage de personnes vivant dans des ménages disposant d’une installation de lavage des mains avec de l’eau et du savon disponibles sur place.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.HYGN.UR.ZS?locations=CI","methodology":"Methodology: Utilizing national-level data derived from household surveys, mainly the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), the JMP calculates the proportion of the population with access to basic handwashing facilities at home with soap and water for each country by using a simple linear regression.\nStatistical concept(s): This indicator is measured using a straightforward indicator that examines the presence of handwashing facilities with soap within homes mainly through national household surveys. \nCollecting accurate information on handwashing practices presents challenges. Self-reported handwashing is an unreliable measure due to the potential for inaccurate reporting. Direct observation of handwashing can lead to observer bias, as individuals may alter their behavior when they know they are being watched, and implementing such observations on a large scale is resource-intensive. A more effective method involves survey enumerators observing the designated handwashing areas in homes and verifying the availability of water and soap, or a local substitute. This approach provides a more dependable and practical measure of handwashing behavior than relying on self-reported data.","theme":"sante","source_group":"wb"},{"code":"AG.LND.CROP.ZS","name":"Terres cultivées permanentes ( % de la superficie)","description":"Les terres cultivées permanentes sont des terres cultivées avec des cultures qui occupent la terre pendant de longues périodes et qui n'ont pas bes...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.CROP.ZS?locations=CI","methodology":"Methodology: The data on Permanent cropland and land area are collected by the Food and Agriculture Organization (FAO) of the United Nations from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.","theme":"primary","source_group":"wb"},{"code":"SE.PRM.PRS5.FE.ZS","name":"Persistance jusqu'à la 5e année, filles ( % de la cohorte)","description":"La persévérance jusqu'en 5e année (pourcentage de la cohorte atteignant la 5e année) est la proportion d'enfants inscrits en première année de l'éc...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.PRS5.FE.ZS?locations=CI","methodology":"Methodology: Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years. Aggregate data are based on World Bank estimates.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The cohort survival rate measures an education system's holding power and internal efficiency. Rates approaching 100 percent indicate high retention and low dropout levels.","theme":"education","source_group":"wb"},{"code":"SE.PRM.PRS5.MA.ZS","name":"Persévérance jusqu'à la 5e année, hommes ( % de la cohorte)","description":"La persévérance jusqu'en 5e année (pourcentage de la cohorte atteignant la 5e année) est la proportion d'enfants inscrits en première année de l'éc...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.PRS5.MA.ZS?locations=CI","methodology":"Methodology: Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years. Aggregate data are based on World Bank estimates.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The cohort survival rate measures an education system's holding power and internal efficiency. Rates approaching 100 percent indicate high retention and low dropout levels.","theme":"education","source_group":"wb"},{"code":"SE.PRM.PRS5.ZS","name":"Persévérance jusqu'à la 5e année, total ( % de la cohorte)","description":"La persévérance jusqu'en 5e année (pourcentage de la cohorte atteignant la 5e année) est la proportion d'enfants inscrits en première année de l'éc...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.PRS5.ZS?locations=CI","methodology":"Methodology: Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years. Aggregate data are based on World Bank estimates.\n\n\n\n\n\n\n\n\n\n\n\n\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\n\n\n\n\n\n\n\n\n\n\n\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The cohort survival rate measures an education system's holding power and internal efficiency. Rates approaching 100 percent indicate high retention and low dropout levels.","theme":"education","source_group":"wb"},{"code":"SE.PRM.PRSL.FE.ZS","name":"Persistance jusqu'à la dernière année du primaire, filles ( % de la cohorte)","description":"La persévérance jusqu'à la dernière année du primaire est le pourcentage d'enfants inscrits en première année de l'école primaire qui atteignent fi...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.PRSL.FE.ZS?locations=CI","methodology":"Methodology: Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The cohort survival rate measures an education system's holding power and internal efficiency. Rates approaching 100 percent indicate high retention and low dropout levels. Survival rate to the last grade of primary education is of particular interest for monitoring universal primary education.","theme":"education","source_group":"wb"},{"code":"SE.PRM.PRSL.MA.ZS","name":"Persistance jusqu'à la dernière année du primaire, garçons ( % de la cohorte)","description":"La persévérance jusqu'à la dernière année du primaire est le pourcentage d'enfants inscrits en première année de l'école primaire qui atteignent fi...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.PRSL.MA.ZS?locations=CI","methodology":"Methodology: Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The cohort survival rate measures an education system's holding power and internal efficiency. Rates approaching 100 percent indicate high retention and low dropout levels. Survival rate to the last grade of primary education is of particular interest for monitoring universal primary education.","theme":"education","source_group":"wb"},{"code":"SE.PRM.PRSL.ZS","name":"Persistance jusqu'à la dernière année du primaire, total ( % de la cohorte)","description":"La persévérance jusqu'à la dernière année du primaire est le pourcentage d'enfants inscrits en première année de l'école primaire qui atteignent fi...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.PRSL.ZS?locations=CI","methodology":"Methodology: Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years. \n\n\n\n\n\n\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The cohort survival rate measures an education system's holding power and internal efficiency. Rates approaching 100 percent indicate high retention and low dropout levels. Survival rate to the last grade of primary education is of particular interest for monitoring universal primary education.","theme":"education","source_group":"wb"},{"code":"BM.TRF.PWKR.CD.DT","name":"Transferts de fonds personnels, payés ($ US courants)","description":"Les transferts de fonds personnels comprennent les transferts personnels et la rémunération des salariés.","source_link":"https://donnees.banquemondiale.org/indicateur/BM.TRF.PWKR.CD.DT?locations=CI","methodology":"Methodology: The two main components of personal remittances, \"personal transfers\" and \"compensation of employees\", are items in the balance of payments (BPM6) framework. Both of these standard components are recorded in the current account. \n\"Personal transfers,\" a new item in the Balance of Payments (BPM6) represents a broader definition of worker remittances. Personal transfers include all current transfers in cash or in kind between resident and nonresident individuals, independent of the source of income of the sender (irrespective of whether the sender receives income from labor, entrepreneurial or property income, social benefits, and any other types of transfers; or disposes assets) and the relationship between the households (irrespective of whether they are related or unrelated individuals).\n\nCompensation of employees refers to the income of border, seasonal, and other short-term workers who are employed in an economy where they are not resident and of residents employed by nonresident entities. Compensation of employees represents remuneration in return for the labor input to the production process contributed by an individual in an employer-employee relationship with the enterprise. Compensation of employees is recorded gross and includes amounts paid by the employee as taxes or for other purposes in the economy where the work is performed. Compensation of employees has three main components: wages and salaries in cash, wages and salaries in kind, and employers' social contributions.","theme":"inter","source_group":"wb"},{"code":"BX.TRF.PWKR.DT.GD.ZS","name":"Envois de fonds personnels, reçus ( % du PIB)","description":"Les transferts de fonds personnels comprennent les transferts personnels et la rémunération des salariés.","source_link":"https://donnees.banquemondiale.org/indicateur/BX.TRF.PWKR.DT.GD.ZS?locations=CI","methodology":"Methodology: The Balance of Payments (BOP) from the International Monetary Fund (IMF) serves as the primary source of information for personal transfers, which are categorized under secondary income, and for the compensation of employees, classified as primary income of the current account. Depending on data availability, references may be made to quarterly or annual figures.\n\nInformation from government agencies such as central banks and national statistical offices further complements the BOP data. When countries have missing data for certain years, this is addressed using methods like Last Observation Carried Forward (LOCF) and Next Observation Carried Backward (NOCB). If disaggregated data is unavailable, estimates are created based on historical ratios and trends.\n\nThe data is presented as a percentage of \"GDP (current US$)\" (NY.GDP.MKTP.CD), which is sourced from the World Bank's national accounts data and the OECD National Accounts data files.","theme":"inter","source_group":"wb"},{"code":"BX.TRF.PWKR.CD.DT","name":"Envois de fonds personnels reçus (en dollars américains courants)","description":"Les transferts de fonds personnels comprennent les transferts personnels et la rémunération des salariés.","source_link":"https://donnees.banquemondiale.org/indicateur/BX.TRF.PWKR.CD.DT?locations=CI","methodology":"Methodology: The two main components of personal remittances, \"personal transfers\" and \"compensation of employees\", are items in the balance of payments (BPM6) framework. Both of these standard components are recorded in the current account. \n\"Personal transfers\", a new item in the Balance of Payments (BPM6) represents a broader definition of worker remittances. Personal transfers include all current transfers in cash or in kind between resident and nonresident individuals, independent of the source of income of the sender (irrespective of whether the sender receives income from labor, entrepreneurial or property income, social benefits, and any other types of transfers; or disposes assets) and the relationship between the households (irrespective of whether they are related or unrelated individuals).\n\nCompensation of employees refers to the income of border, seasonal, and other short-term workers who are employed in an economy where they are not resident and of residents employed by nonresident entities. Compensation of employees represents remuneration in return for the labor input to the production process contributed by an individual in an employer-employee relationship with the enterprise. Compensation of employees is recorded gross and includes amounts paid by the employee as taxes or for other purposes in the economy where the work is performed. Compensation of employees has three main components: wages and salaries in cash, wages and salaries in kind, and employers' social contributions.","theme":"inter","source_group":"wb"},{"code":"BX.TRF.PWKR.CD","name":"Virements personnels, encaissements ($ US courants, BoP)","description":"Les transferts personnels sont des transferts courants, en espèces ou en nature, reçus par les ménages résidents de la part des ménages non-résidents.","source_link":"https://donnees.banquemondiale.org/indicateur/BX.TRF.PWKR.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"SH.MED.PHYS.ZS","name":"Médecins (pour 1 000 personnes)","description":"Les médecins comprennent les médecins généralistes et spécialistes.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.MED.PHYS.ZS?locations=CI","methodology":"Methodology: National focal points share the data with WHO through the online NHWA data platform. The platform hosted in WHO, is built to facilitate data reporting on the indicators listed in the NHWA Handbook and data sharing across all the 3 levels of WHO.\nStatistical concept(s): Health systems - the combined arrangements of institutions and actions whose primary purpose is to promote, restore, or maintain health (World Health Organization, World Health Report 2000) - are increasingly being recognized as key to combating disease and improving the health status of populations. The World Bank's Healthy Development: Strategy for Health, Nutrition, and Population Results emphasizes the need to strengthen health systems, which are weak in many countries, in order to increase the effectiveness of programs aimed at reducing specific diseases and further reduce morbidity and mortality. To evaluate health systems, the World Health Organization (WHO) has recommended that key components - such as financing, service delivery, workforce, governance, and information - be monitored using several key indicators. The data are a subset of the key indicators. Monitoring health systems allows the effectiveness, efficiency, and equity of different health system models to be compared. Health system data also help identify weaknesses and strengths and areas that need investment, such as additional health facilities, better health information systems, or better trained human resources.\nData on health worker (physicians, nurses and midwives, and community health workers) density show the availability of medical personnel.","theme":"sante","source_group":"wb"},{"code":"EN.HPT.THRD.NO","name":"Espèces végétales (supérieures), menacées","description":"Les plantes supérieures sont des espèces de plantes vasculaires indigènes.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.HPT.THRD.NO?locations=CI","methodology":"Methodology: Species assessed as Critically Endangered (CR), Endangered (EN) or Vulnerable (VU) are referred to as \"threatened\" species. The International Union for Conservation of Nature (IUCN) Red List of Threatened Species collects and disseminates information on the global threated species.\nProportion of threatened species is only reported for the more completely evaluated groups (i.e., >90% of species evaluated). Also, the reported percentage of threatened species for each group is presented as a best estimate within a range of possible values bounded by lower and upper estimates:\nLower estimate = % threatened extant species if all Data Deficient species are not threatened, i.e., (CR + EN + VU) / (total assessed - EX)\nBest estimate = % threatened extant species if Data Deficient species are equally threatened as data sufficient species, i.e., (CR + EN + VU) / (total assessed - EX - DD)\nUpper estimate = % threatened extant species if all Data Deficient species are threatened, i.e., (CR + EN + VU + DD) / (total assessed - EX)\nAdditional information on ecology and habitat preferences, threats, and conservation action are also collated and assessed as part of Red List process.","theme":"territory","source_group":"wb"},{"code":"EN.ATM.PM25.MC.M3","name":"Pollution atmosphérique PM2,5, exposition annuelle moyenne (microgrammes par mètre cube)","description":"L'exposition pondérée de la population à la pollution ambiante par les PM2,5 est définie comme le niveau moyen d'exposition de la population d'un p...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.ATM.PM25.MC.M3?locations=CI","methodology":"Methodology: A. van Donkelaar, R.V. Martin, M. Brauer, N.C. Hsu, R.A. Kahn, R.C. Levy, A. Lyapustin, A.M. Sayer, D.M. Winker, \"Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors,\" Environ. Sci. Technol 50, no. 7 (2016): 3762–3772; GBD 2017 Risk Factors Collaborators, \"Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 194 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017,\" Lancet 392 (2018): 1923-1994; Shaddick G, Thomas M, Amini H, Broday DM, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Prüss-Üstün A, Simpson D, van Donkelaar A, Brauer M. Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. Data provided by Institute for Health Metrics and Evaluation, University of Washington, Seattle. Data on exposure to ambient air pollution are derived from estimates of annual concentrations of very fine particulates produced by the Global Burden of Disease study, an international scientific effort led by the Institute for Health Metrics and Evaluation at the University of Washington. Estimates of annual concentrations are generated by combining data from atmospheric chemistry transport models, satellite observations of aerosols in the atmosphere, and ground-level monitoring of particulates. Exposure to concentrations of PM2.5 in both urban and rural areas is weighted by population and is aggregated at the national level.","theme":"territory","source_group":"wb"},{"code":"EN.ATM.PM25.MC.ZS","name":"Pollution atmosphérique par les PM2,5, population exposée à des niveaux supérieurs à la valeur recommandée par l'OMS ( % du total)","description":"Le pourcentage de la population exposée à des concentrations ambiantes de PM2,5 qui dépassent la valeur guide de l’OMS est défini comme la partie d...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.ATM.PM25.MC.ZS?locations=CI","methodology":"Methodology: A. van Donkelaar, R.V. Martin, M. Brauer, N.C. Hsu, R.A. Kahn, R.C. Levy, A. Lyapustin, A.M. Sayer, D.M. Winker, \"Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors,\" Environ. Sci. Technol 50, no. 7 (2016): 3762–3772; GBD 2017 Risk Factors Collaborators, \"Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 194 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017,\" Lancet 392 (2018): 1923-1994; Shaddick G, Thomas M, Amini H, Broday DM, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Prüss-Üstün A, Simpson D, van Donkelaar A, Brauer M. Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. Data provided by Institute for Health Metrics and Evaluation, University of Washington, Seattle. Data on exposure to ambient air pollution are derived from estimates of annual concentrations of very fine particulates produced by the Global Burden of Disease study, an international scientific effort led by the Institute for Health Metrics and Evaluation at the University of Washington. Estimates of annual concentrations are generated by combining data from atmospheric chemistry transport models, satellite observations of aerosols in the atmosphere, and ground-level monitoring of particulates. Overlaying PM2.5 estimates with gridded population data, the percent of a nation's people that lives in areas where PM2.5 concentrations exceed recommended levels is calculated by summing the population for grid cells where PM2.5 concentrations are beyond a threshold value, in this case 10 micrograms per cubic meter, and then dividing by total population.","theme":"territory","source_group":"wb"},{"code":"EN.ATM.PM25.MC.T1.ZS","name":"Pollution par les PM2,5, population exposée à des niveaux supérieurs à la valeur de l'objectif intermédiaire 1 de l'OMS ( % du total)","description":"Le pourcentage de la population exposée à des concentrations ambiantes de PM2,5 qui dépassent l’objectif intermédiaire 1 (IT-1) de l’Organisation m...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.ATM.PM25.MC.T1.ZS?locations=CI","methodology":"Methodology: A. van Donkelaar, R.V. Martin, M. Brauer, N.C. Hsu, R.A. Kahn, R.C. Levy, A. Lyapustin, A.M. Sayer, D.M. Winker, \"Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors,\" Environ. Sci. Technol 50, no. 7 (2016): 3762–3772;GBD 2017 Risk Factors Collaborators, \"Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 194 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017,\" Lancet 392 (2018): 1923-1994; Shaddick G, Thomas M, Amini H, Broday DM, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Prüss-Üstün A, Simpson D, van Donkelaar A, Brauer M. Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. Data provided by Institute for Health Metrics and Evaluation, University of Washington, Seattle. Data on exposure to ambient air pollution are derived from estimates of annual concentrations of very fine particulates produced by the Global Burden of Disease study, an international scientific effort led by the Institute for Health Metrics and Evaluation at the University of Washington. Estimates of annual concentrations are generated by combining data from atmospheric chemistry transport models, satellite observations of aerosols in the atmosphere, and ground-level monitoring of particulates. Overlaying PM2.5 estimates with gridded population data, the percent of a nation's people that lives in areas where PM2.5 concentrations exceed recommended levels is calculated by summing the population for grid cells where PM2.5 concentrations are beyond a threshold value, in this case 10 micrograms per cubic meter, and then dividing by total population.","theme":"territory","source_group":"wb"},{"code":"EN.ATM.PM25.MC.T2.ZS","name":"Pollution par les PM2,5, population exposée à des niveaux supérieurs à la valeur de l'objectif intermédiaire 2 de l'OMS ( % du total)","description":"Le pourcentage de la population exposée à des concentrations ambiantes de PM2,5 qui dépassent l’objectif intermédiaire 2 (IT-2) de l’Organisation m...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.ATM.PM25.MC.T2.ZS?locations=CI","methodology":"Methodology: A. van Donkelaar, R.V. Martin, M. Brauer, N.C. Hsu, R.A. Kahn, R.C. Levy, A. Lyapustin, A.M. Sayer, D.M. Winker, \"Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors,\" Environ. Sci. Technol 50, no. 7 (2016): 3762–3772; GBD 2017 Risk Factors Collaborators, \"Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 194 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017,\" Lancet 392 (2018): 1923-1994; Shaddick G, Thomas M, Amini H, Broday DM, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Prüss-Üstün A, Simpson D, van Donkelaar A, Brauer M. Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. Data provided by Institute for Health Metrics and Evaluation, University of Washington, Seattle. Data on exposure to ambient air pollution are derived from estimates of annual concentrations of very fine particulates produced by the Global Burden of Disease study, an international scientific effort led by the Institute for Health Metrics and Evaluation at the University of Washington. Estimates of annual concentrations are generated by combining data from atmospheric chemistry transport models, satellite observations of aerosols in the atmosphere, and ground-level monitoring of particulates. Overlaying PM2.5 estimates with gridded population data, the percent of a nation's people that lives in areas where PM2.5 concentrations exceed recommended levels is calculated by summing the population for grid cells where PM2.5 concentrations are beyond a threshold value, in this case 10 micrograms per cubic meter, and then dividing by total population.\nStatistical concept(s):","theme":"territory","source_group":"wb"},{"code":"EN.ATM.PM25.MC.T3.ZS","name":"Pollution par les PM2,5, population exposée à des niveaux supérieurs à la valeur de l'objectif intermédiaire 3 de l'OMS (en % du total)","description":"Le pourcentage de la population exposée à des concentrations ambiantes de PM2,5 qui dépassent l’objectif intermédiaire 3 (IT-3) de l’Organisation m...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.ATM.PM25.MC.T3.ZS?locations=CI","methodology":"Methodology: A. van Donkelaar, R.V. Martin, M. Brauer, N.C. Hsu, R.A. Kahn, R.C. Levy, A. Lyapustin, A.M. Sayer, D.M. Winker, \"Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors,\" Environ. Sci. Technol 50, no. 7 (2016): 3762–3772; GBD 2017 Risk Factors Collaborators, \"Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 194 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017,\" Lancet 392 (2018): 1923-1994; Shaddick G, Thomas M, Amini H, Broday DM, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Prüss-Üstün A, Simpson D, van Donkelaar A, Brauer M. Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. Data provided by Institute for Health Metrics and Evaluation, University of Washington, Seattle. Data on exposure to ambient air pollution are derived from estimates of annual concentrations of very fine particulates produced by the Global Burden of Disease study, an international scientific effort led by the Institute for Health Metrics and Evaluation at the University of Washington. Estimates of annual concentrations are generated by combining data from atmospheric chemistry transport models, satellite observations of aerosols in the atmosphere, and ground-level monitoring of particulates. Overlaying PM2.5 estimates with gridded population data, the percent of a nation's people that lives in areas where PM2.5 concentrations exceed recommended levels is calculated by summing the population for grid cells where PM2.5 concentrations are beyond a threshold value, in this case 10 micrograms per cubic meter, and then dividing by total population.","theme":"territory","source_group":"wb"},{"code":"DT.NFL.PNGB.CD","name":"PNG, obligations (NFL, $ US courants)","description":"Dette à long terme non garantie provenant d’obligations placées de manière privée.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.PNGB.CD?locations=CI","methodology":"Methodology: Countries that report to the World Bank’s Debtor Reporting System (DRS) submit their private nonguaranteed (PNG) on an aggregate basis. The World Bank Debt Data Team then compiles this information to produce this indicator.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.PNGC.CD","name":"PNG, banques commerciales et autres créanciers (NFL, dollars américains courants)","description":"Prêts bancaires commerciaux à long terme non garantis auprès de banques privées et d'autres institutions financières privées.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.PNGC.CD?locations=CI","methodology":"Methodology: Countries that report to the World Bank’s Debtor Reporting System (DRS) submit their private nonguaranteed (PNG) on an aggregate basis. The World Bank Debt Data Team then compiles this information to produce this indicator.","theme":"finance","source_group":"wb"},{"code":"PV.EST","name":"Stabilité politique et absence de violence/terrorisme : estimation","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/PV.EST?locations=CI","methodology":"","theme":"politique","source_group":"wb"},{"code":"PV.NO.SRC","name":"Stabilité politique et absence de violence/terrorisme : nombre de sources","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/PV.NO.SRC?locations=CI","methodology":"Methodology: The WGI compile and summarize information from over 30 existing data sources that report the views and experiences of citizens, entrepreneurs, and experts in the public, private and NGO sectors from around the world, on the quality of various aspects of governance.\n\n•\tThe data sources must provide subjective perceptions of relevant dimensions of governance, as the WGI are based exclusively on this type of data.\n•\tThe sources must provide original primary data produced using a well-defined methodology.\n•\tThe data sources must cover multiple countries, so that cross-country comparisons are possible.\n•\tThe data sources must be updated regularly, ideally every year, although some WGI data sources are updated once every two or three years.\n\nThe WGI draw on four different types of source data:\n\n•\tSurveys of households and firms, including the Afrobarometer surveys, Gallup World Poll, and Global Competitiveness Report survey,\n•\tCommercial business information providers, including the Economist Intelligence Unit, S&P Global, and Political Risk Services,\n•\tNon-governmental organizations, including Global Integrity, Freedom House, Reporters Without Borders, and\n•\tPublic sector organizations, including the Country Policy and Institutional Assessments (CPIA) assessments of World Bank and regional development banks.\n\nFor the detailed list of sources, please refer to: https://www.worldbank.org/en/publication/worldwide-governance-indicators/documentation#2  \nStatistical concept(s): Number of sources indicates the number of underlying data sources on which the aggregate estimate is based.\n\nVariables from the data sources are assigned to each of these six governance dimensions.  For example, an assessment of the quality of the bureaucracy would be assigned to Government Effectiveness, a question about confidence in the police or the courts would be assigned to Rule of Law, and a question about the perceived likelihood of having to pay a bribe would be assigned to Control of Corruption.  In some cases, a single data source will have multiple questions that can be assigned to the same dimension.  In this case, the WGI use the average across all relevant questions from that data source. In addition each question from each data source is assigned to only one of the six governance dimensions, selecting the dimension that best matches the content of the question.","theme":"politique","source_group":"wb"},{"code":"PV.PER.RNK","name":"Stabilité politique et absence de violence/terrorisme : rang centile","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/PV.PER.RNK?locations=CI","methodology":"","theme":"politique","source_group":"wb"},{"code":"PV.PER.RNK.LOWER","name":"Stabilité politique et absence de violence/terrorisme : rang centile, limite inférieure de l'intervalle de confiance à 90 %","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/PV.PER.RNK.LOWER?locations=CI","methodology":"Methodology: A key feature of the WGI is that all country scores are accompanied by standard errors. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether.\n\nThe standard deviations are essential to the interpretation of the WGI.  It often is more appropriate to think of the WGI methodology as identifying a statistically likely range of values for the unobserved “true” level of governance in a country.  For example, the assumption of normality tells us that there is a 90 percent probability that the true unobserved level of governance conditional on the available data for a country is in a range given by plus or minus 1.64 standard deviations around the estimate of governance. These confidence intervals are informally referred to as the “margin of error” around the estimates of governance.\n\nThese 90 percent confidence interval are also reported in percentile rank terms (the percentile rank among all country estimates of governance, of the upper and lower bounds of the 90 percent confidence interval for each country).\nStatistical concept(s): Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank.  Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.  \n\nPercentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.","theme":"politique","source_group":"wb"},{"code":"PV.PER.RNK.UPPER","name":"Stabilité politique et absence de violence/terrorisme : rang centile, limite supérieure de l'intervalle de confiance à 90 %","description":"La bonne gouvernance est essentielle au développement.","source_link":"https://donnees.banquemondiale.org/indicateur/PV.PER.RNK.UPPER?locations=CI","methodology":"Methodology: A key feature of the WGI is that all country scores are accompanied by standard errors. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether.\n\nThe standard deviations are essential to the interpretation of the WGI.  It often is more appropriate to think of the WGI methodology as identifying a statistically likely range of values for the unobserved “true” level of governance in a country.  For example, the assumption of normality tells us that there is a 90 percent probability that the true unobserved level of governance conditional on the available data for a country is in a range given by plus or minus 1.64 standard deviations around the estimate of governance. These confidence intervals are informally referred to as the “margin of error” around the estimates of governance.\n\nThese 90 percent confidence interval are also reported in percentile rank terms (the percentile rank among all country estimates of governance, of the upper and lower bounds of the 90 percent confidence interval for each country).\nStatistical concept(s): Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. \n\nPercentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.","theme":"politique","source_group":"wb"},{"code":"PV.STD.ERR","name":"Stabilité politique et absence de violence/terrorisme : l'erreur-type","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/PV.STD.ERR?locations=CI","methodology":"Methodology: The WGI are composite governance indicators based on over 30 underlying data sources. These data sources are rescaled and combined to create the six aggregate indicators using a statistical methodology known as an Unobserved Components Model (UCM). The six aggregate indicators are reported in two ways : (1) in their standard normal units, ranging from approximately -2.5 to 2.5, and (2) in percentile rank terms from 0 to 100, with higher values corresponding to better outcomes.\n\nA key feature of the WGI is that all country scores are accompanied by standard errors. These margins of error need to be taken into account when making comparisons across countries and over time. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether. \n\nPlease see more information at: https://www.worldbank.org/en/publication/worldwide-governance-indicators/documentation#1\nStatistical concept(s): Standard error indicates the precision of the estimate of governance. Larger values of the standard error indicate less precise estimates. A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.","theme":"politique","source_group":"wb"},{"code":"SP.POP.0004.FE.5Y","name":"Population âgée de 00 à 04 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 0 à 4 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.0004.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.0004.MA.5Y","name":"Population âgée de 00 à 04 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 0 à 4 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.0004.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.0014.TO.ZS","name":"Population âgée de 0 à 14 ans ( % de la population totale)","description":"Population âgée de 0 à 14 ans en pourcentage de la population totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.0014.TO.ZS?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.0014.FE.IN","name":"Population âgée de 0 à 14 ans, femmes","description":"Population féminine âgée de 0 à 14 ans.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.0014.FE.IN?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.0014.FE.ZS","name":"Population âgée de 0 à 14 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 0 à 14 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.0014.FE.ZS?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.0014.MA.IN","name":"Population âgée de 0 à 14 ans, hommes","description":"Population masculine âgée de 0 à 14 ans.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.0014.MA.IN?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.0014.MA.ZS","name":"Population âgée de 0 à 14 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 0 à 14 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.0014.MA.ZS?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.0014.TO","name":"Population âgée de 0 à 14 ans, total","description":"Population totale âgée de 0 à 14 ans.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.0014.TO?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.0509.FE.5Y","name":"Population âgée de 05 à 09 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 5 à 9 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.0509.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.0509.MA.5Y","name":"Population âgée de 05 à 09 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 5 à 9 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.0509.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.1014.FE.5Y","name":"Population âgée de 10 à 14 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 10 à 14 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.1014.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.1014.MA.5Y","name":"Population âgée de 10 à 14 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 10 à 14 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.1014.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.1519.FE.5Y","name":"Population âgée de 15 à 19 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 15 à 19 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.1519.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.1519.MA.5Y","name":"Population âgée de 15 à 19 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 15 à 19 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.1519.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.1564.TO.ZS","name":"Population âgée de 15 à 64 ans (en % de la population totale)","description":"Population totale âgée de 15 à 64 ans en pourcentage de la population totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.1564.TO.ZS?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.1564.FE.IN","name":"Population âgée de 15 à 64 ans, femmes","description":"Population féminine âgée de 15 à 64 ans.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.1564.FE.IN?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.1564.FE.ZS","name":"Population âgée de 15 à 64 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 15 à 64 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.1564.FE.ZS?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.1564.MA.IN","name":"Population âgée de 15 à 64 ans, hommes","description":"Population masculine âgée de 15 à 64 ans.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.1564.MA.IN?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.1564.MA.ZS","name":"Population âgée de 15 à 64 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 15 à 64 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.1564.MA.ZS?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.1564.TO","name":"Population âgée de 15 à 64 ans, total","description":"Population totale âgée de 15 à 64 ans.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.1564.TO?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.2024.FE.5Y","name":"Population âgée de 20 à 24 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 20 à 24 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.2024.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.2024.MA.5Y","name":"Population âgée de 20 à 24 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 20 à 24 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.2024.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.2529.FE.5Y","name":"Population âgée de 25 à 29 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 25 à 29 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.2529.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.2529.MA.5Y","name":"Population âgée de 25 à 29 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 25 à 29 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.2529.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.3034.FE.5Y","name":"Population âgée de 30 à 34 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 30 à 34 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.3034.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.3034.MA.5Y","name":"Population âgée de 30 à 34 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 30 à 34 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.3034.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.3539.FE.5Y","name":"Population âgée de 35 à 39 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 35 à 39 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.3539.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.3539.MA.5Y","name":"Population âgée de 35 à 39 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 35 à 39 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.3539.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.4044.FE.5Y","name":"Population âgée de 40 à 44 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 40 à 44 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.4044.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.4044.MA.5Y","name":"Population âgée de 40 à 44 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 40 à 44 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.4044.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.4549.FE.5Y","name":"Population âgée de 45 à 49 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 45 à 49 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.4549.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.4549.MA.5Y","name":"Population âgée de 45 à 49 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 45 à 49 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.4549.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.5054.FE.5Y","name":"Population âgée de 50 à 54 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 50 à 54 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.5054.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.5054.MA.5Y","name":"Population âgée de 50 à 54 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 50 à 54 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.5054.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.5559.FE.5Y","name":"Population âgée de 55 à 59 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 55 à 59 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.5559.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.5559.MA.5Y","name":"Population âgée de 55 à 59 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 55 à 59 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.5559.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.6064.FE.5Y","name":"Population âgée de 60 à 64 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 60 à 64 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.6064.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.6064.MA.5Y","name":"Population âgée de 60 à 64 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 60 à 64 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.6064.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.65UP.TO.ZS","name":"Population âgée de 65 ans et plus ( % de la population totale)","description":"Population âgée de 65 ans et plus en pourcentage de la population totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.65UP.TO.ZS?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.65UP.FE.IN","name":"Population âgée de 65 ans et plus, femmes","description":"Population féminine de 65 ans ou plus.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.65UP.FE.IN?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.65UP.FE.ZS","name":"Population âgée de 65 ans et plus, femmes ( % de la population féminine)","description":"Population féminine de 65 ans ou plus en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.65UP.FE.ZS?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.65UP.MA.IN","name":"Population âgée de 65 ans et plus, hommes","description":"Population masculine de 65 ans ou plus.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.65UP.MA.IN?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.65UP.MA.ZS","name":"Population âgée de 65 ans et plus, hommes ( % de la population masculine)","description":"Population masculine de 65 ans ou plus en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.65UP.MA.ZS?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.65UP.TO","name":"Population âgée de 65 ans et plus, total","description":"Population totale âgée de 65 ans ou plus.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.65UP.TO?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.6569.FE.5Y","name":"Population âgée de 65 à 69 ans, femmes (en % de la population féminine)","description":"Population féminine âgée de 65 à 69 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.6569.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.6569.MA.5Y","name":"Population âgée de 65 à 69 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 65 à 69 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.6569.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.7074.FE.5Y","name":"Population âgée de 70 à 74 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 70 à 74 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.7074.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.7074.MA.5Y","name":"Population âgée de 70 à 74 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 70 à 74 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.7074.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.7579.FE.5Y","name":"Population âgée de 75 à 79 ans, femmes ( % de la population féminine)","description":"Population féminine âgée de 75 à 79 ans en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.7579.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.7579.MA.5Y","name":"Population âgée de 75 à 79 ans, hommes ( % de la population masculine)","description":"Population masculine âgée de 75 à 79 ans en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.7579.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.80UP.FE.5Y","name":"Population âgée de 80 ans et plus, femmes ( % de la population féminine)","description":"Population féminine âgée de 80 ans et plus en pourcentage de la population féminine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.80UP.FE.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.80UP.MA.5Y","name":"Population âgée de 80 ans et plus, hommes ( % de la population masculine)","description":"Population masculine âgée de 80 ans et plus en pourcentage de la population masculine totale.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.80UP.MA.5Y?locations=CI","methodology":"Methodology: Population structure by age and sex in the World Bank's estimates is based on age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Proportion of population by age and/or sex describes the proportion of the population in the category out of total (or male total or female total). Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the age/sex distribution of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"EN.POP.DNST","name":"Densité de population (personnes par kilomètre carré de superficie)","description":"La densité de population correspond à la population en milieu d'année divisée par la superficie en kilomètres carrés.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.POP.DNST?locations=CI","methodology":"Methodology: Population density is midyear population divided by land area in square kilometers. This ratio can be calculated for any territorial unit for any point in time, depending on the source of the population data. Populationestimates are prepared by World Bank staff from variety of sources. They are based on the de facto definition of population and include all residents regardless of legal status or citizenship, within the physical boundaries of a country and under the jurisdiction of that country's political control. Refugees not permanently settled in the country of asylum are considered part of the population of their country of origin. Population numbers are either current census data or historical census data extrapolated through demographic methods. The count also excludes visitors from overseas.\nPopulation density is calculated by dividing midyear population by land area in a country. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship - except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.","theme":"demo","source_group":"wb"},{"code":"SP.POP.GROW","name":"Croissance démographique ( % annuel)","description":"Le taux de croissance démographique annuel pour l’année t est le taux exponentiel de croissance de la population en milieu d’année de l’année t-1 à...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.GROW?locations=CI","methodology":"Methodology: The growth rate is computed using the exponential growth formula:\nr = ln(pn/p0)/n, \nwhere r is the exponential rate of growth, ln() is the natural logarithm, pn is the end period population, p0 is the beginning period population, and n is the number of years in between. Note that this is not the geometric growth rate used to compute compound growth over discrete periods.\nFor information on total population from which the growth rates are calculated, see total population (SP.POP.TOTL).\nStatistical concept(s): Total population growth rates are calculated on the assumption that rate of growth is constant between two points in time.","theme":"demo","source_group":"wb"},{"code":"EN.URB.LCTY","name":"Population dans la plus grande ville","description":"La population de la plus grande ville est la population urbaine vivant dans la plus grande zone métropolitaine du pays.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.URB.LCTY?locations=CI","methodology":"Methodology: Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. The United Nations Population Division and other agencies provide current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data. The cohort component method - a standard method for estimating and projecting population - requires fertility, mortality, and net migration data, often collected from sample surveys, which can be small or limited in coverage. Population estimates are from demographic modeling and so are susceptible to biases and errors from shortcomings in the model and in the data. Because the five-year age group is the cohort unit and five-year period data are used, interpolations to obtain annual data or single age structure may not reflect actual events or age composition.\n\n\n\n\n\n\n\n\n\n\n\nCountries differ in the way they classify population as \"urban\" or \"rural.\" Typically, a community or settlement with a population of 2,000 or more is considered urban, but national definitions are most commonly based on size of locality. Eurostat defines urban areas as clusters of contiguous grid cells of 1 km2 with a density of at least 300 inhabitants per km2 and a minimum population of 5,000. Further it defines high-density cluster as contiguous grid cells of 1 km2 with a density of at least 1,500 inhabitants per km2 and a minimum population of 50,000.\n\n\n\n\n\n\n\n\n\n\n\nThe population of a city or metropolitan area depends on the boundaries chosen. For example, in 1990 Beijing, China, contained 2.3 million people in 87 square kilometers of \"inner city\" and 5.4 million in 158 square kilometers of \"core city.\" The population of \"inner city and inner suburban districts\" was 6.3 million and that of \"inner city, inner and outer suburban districts, and inner and outer counties\" was 10.8 million. (Most countries use the last definition.)","theme":"demo","source_group":"wb"},{"code":"EN.URB.LCTY.UR.ZS","name":"Population de la plus grande ville ( % de la population urbaine)","description":"La population de la plus grande ville est le pourcentage de la population urbaine d'un pays vivant dans la plus grande zone métropolitaine de ce pays.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.URB.LCTY.UR.ZS?locations=CI","methodology":"Methodology: Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. The United Nations Population Division and other agencies provide current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data. The cohort component method - a standard method for estimating and projecting population - requires fertility, mortality, and net migration data, often collected from sample surveys, which can be small or limited in coverage. Population estimates are from demographic modeling and so are susceptible to biases and errors from shortcomings in the model and in the data. Because the five-year age group is the cohort unit and five-year period data are used, interpolations to obtain annual data or single age structure may not reflect actual events or age composition.\n\n\n\n\n\n\n\n\n\n\n\nCountries differ in the way they classify population as \"urban\" or \"rural.\" Typically, a community or settlement with a population of 2,000 or more is considered urban, but national definitions are most commonly based on size of locality. Eurostat defines urban areas as clusters of contiguous grid cells of 1 km2 with a density of at least 300 inhabitants per km2 and a minimum population of 5,000. Further it defines high-density cluster as contiguous grid cells of 1 km2 with a density of at least 1,500 inhabitants per km2 and a minimum population of 50,000.\n\n\n\n\n\n\n\n\n\n\n\nThe population of a city or metropolitan area depends on the boundaries chosen. For example, in 1990 Beijing, China, contained 2.3 million people in 87 square kilometers of \"inner city\" and 5.4 million in 158 square kilometers of \"core city.\" The population of \"inner city and inner suburban districts\" was 6.3 million and that of \"inner city, inner and outer suburban districts, and inner and outer counties\" was 10.8 million. (Most countries use the last definition.)","theme":"demo","source_group":"wb"},{"code":"EN.URB.MCTY","name":"Population dans les agglomérations urbaines de plus de 1 million d'habitants","description":"La population des agglomérations urbaines de plus d'un million est la population du pays vivant dans les zones métropolitaines qui, en 2018, compta...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.URB.MCTY?locations=CI","methodology":"Methodology: Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. The United Nations Population Division and other agencies provide current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data. The cohort component method - a standard method for estimating and projecting population - requires fertility, mortality, and net migration data, often collected from sample surveys, which can be small or limited in coverage. Population estimates are from demographic modeling and so are susceptible to biases and errors from shortcomings in the model and in the data. Because the five-year age group is the cohort unit and five-year period data are used, interpolations to obtain annual data or single age structure may not reflect actual events or age composition.\n\n\n\n\n\n\n\n\n\n\n\nCountries differ in the way they classify population as \"urban\" or \"rural.\" Typically, a community or settlement with a population of 2,000 or more is considered urban, but national definitions are most commonly based on size of locality. Eurostat defines urban areas as clusters of contiguous grid cells of 1 km2 with a density of at least 300 inhabitants per km2 and a minimum population of 5,000. Further it defines high-density cluster as contiguous grid cells of 1 km2 with a density of at least 1,500 inhabitants per km2 and a minimum population of 50,000.\n\n\n\n\n\n\n\n\n\n\n\nThe population of a city or metropolitan area depends on the boundaries chosen. For example, in 1990 Beijing, China, contained 2.3 million people in 87 square kilometers of \"inner city\" and 5.4 million in 158 square kilometers of \"core city.\" The population of \"inner city and inner suburban districts\" was 6.3 million and that of \"inner city, inner and outer suburban districts, and inner and outer counties\" was 10.8 million. (Most countries use the last definition.)\nStatistical concept(s):","theme":"demo","source_group":"wb"},{"code":"EN.URB.MCTY.TL.ZS","name":"Population dans les agglomérations urbaines de plus de 1 million d'habitants (en % de la population totale)","description":"La population des agglomérations urbaines de plus d'un million est le pourcentage de la population d'un pays vivant dans des zones métropolitaines ...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.URB.MCTY.TL.ZS?locations=CI","methodology":"Methodology: Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. The United Nations Population Division and other agencies provide current population estimates for developing countries that lack recent census data and pre- and post-census estimates for countries with census data. The cohort component method - a standard method for estimating and projecting population - requires fertility, mortality, and net migration data, often collected from sample surveys, which can be small or limited in coverage. Population estimates are from demographic modeling and so are susceptible to biases and errors from shortcomings in the model and in the data. Because the five-year age group is the cohort unit and five-year period data are used, interpolations to obtain annual data or single age structure may not reflect actual events or age composition.\n\n\n\n\n\n\n\n\n\n\n\nCountries differ in the way they classify population as \"urban\" or \"rural.\" Typically, a community or settlement with a population of 2,000 or more is considered urban, but national definitions are most commonly based on size of locality. Eurostat defines urban areas as clusters of contiguous grid cells of 1 km2 with a density of at least 300 inhabitants per km2 and a minimum population of 5,000. Further it defines high-density cluster as contiguous grid cells of 1 km2 with a density of at least 1,500 inhabitants per km2 and a minimum population of 50,000.\n\n\n\n\n\n\n\n\n\n\n\nThe population of a city or metropolitan area depends on the boundaries chosen. For example, in 1990 Beijing, China, contained 2.3 million people in 87 square kilometers of \"inner city\" and 5.4 million in 158 square kilometers of \"core city.\" The population of \"inner city and inner suburban districts\" was 6.3 million and that of \"inner city, inner and outer suburban districts, and inner and outer counties\" was 10.8 million. (Most countries use the last definition.)","theme":"demo","source_group":"wb"},{"code":"EN.POP.EL5M.ZS","name":"Population vivant dans des zones où l'altitude est inférieure à 5 mètres ( % de la population totale)","description":"La population de moins de 5 m correspond au pourcentage de la population totale vivant dans des zones où l'altitude est de 5 mètres ou moins.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.POP.EL5M.ZS?locations=CI","methodology":"Methodology: Population counts in low elevation zones in the year 1990 as described by GRUMPv1 input estimates allocated into 3 arc second grid cells. Population counts in low elevation zones in the year 2000 as described by GRUMPv1 input estimates allocated into 3 arc second grid cells. Population counts in low elevation zones in the year 2010 derived from the application of United Nations 2000-2010 national growth rates to year 2000 population data from GRUMPv1 (see documentation for full description of methodologies).","theme":"demo","source_group":"wb"},{"code":"EN.POP.SLUM.UR.ZS","name":"Population vivant dans des bidonvilles (en % de la population urbaine)","description":"La population vivant dans des bidonvilles est la proportion de la population urbaine vivant dans des ménages de bidonvilles.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.POP.SLUM.UR.ZS?locations=CI","methodology":"Methodology: Population living in slums is the proportion of the urban population living in slum households. A slum household is defined as a group of individuals living under the same roof lacking one or more of the following conditions: access to improved water, access to improved sanitation, sufficient living area, housing durability, and security of tenure, as adopted in the Millennium Development Goal Target 7.D. The successor, the Sustainable Development Goal 11.1.1, considers inadequate housing (housing affordability) to complement the above definition of slums/informal settlements.","theme":"demo","source_group":"wb"},{"code":"SP.POP.TOTL.FE.IN","name":"Population, femmes","description":"La population féminine est basée sur la définition de facto de la population, qui compte toutes les résidentes féminines, quel que soit leur statut...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.TOTL.FE.IN?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.TOTL.FE.ZS","name":"Population, femmes ( % de la population totale)","description":"La population féminine est le pourcentage de la population qui est féminine.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.TOTL.FE.ZS?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.TOTL.MA.IN","name":"Population, hommes","description":"La population masculine est basée sur la définition de facto de la population, qui compte tous les résidents de sexe masculin, quel que soit leur s...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.TOTL.MA.IN?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.TOTL.MA.ZS","name":"Population, hommes ( % de la population totale)","description":"La population masculine est le pourcentage de la population qui est de sexe masculin.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.TOTL.MA.ZS?locations=CI","methodology":"Methodology: Estimates are calculated using the World Bank's total population and age/sex distributions of the population in United Nations Population Division's World Population Prospects.\nStatistical concept(s): Estimates of population by age and/or sex describe the size of the population in the category. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"SP.POP.TOTL","name":"Population, total","description":"La population totale est basée sur la définition de facto de la population, qui compte tous les résidents, quel que soit leur statut juridique ou l...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.TOTL?locations=CI","methodology":"Methodology: Population estimates are usually based on national population censuses, and estimates of fertility, mortality and migration.\nErrors and undercounting in census occur even in high-income countries.  In developing countries errors may be substantial because of limits in the transport, communications, and other resources required to conduct and analyze a full census.\nThe quality and reliability of official demographic data are also affected by public trust in the government, government commitment to full and accurate enumeration, confidentiality and protection against misuse of census data, and census agencies' independence from political influence. Moreover, comparability of population indicators is limited by differences in the concepts, definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that collect the data.\nThe currentness of a census and the availability of complementary data from surveys or registration systems are objective ways to judge demographic data quality. Some European countries' registration systems offer complete information on population in the absence of a census.\nThe United Nations Statistics Division monitors the completeness of vital registration systems. Some developing countries have made progress over the last 60 years, but others still have deficiencies in civil registration systems.\nInternational migration is the only other factor besides birth and death rates that directly determines a country's population change. Estimating migration is difficult. At any time many people are located outside their home country as tourists, workers, or refugees or for other reasons. Standards for the duration and purpose of international moves that qualify as migration vary, and estimates require information on flows into and out of countries that is difficult to collect.\nOne of the major data sources of this indicator is UN Population Division's World Population Prospects, which use the cohort component method to produce population estimates and projections.\nPopulation projections, starting from a base year are projected forward using assumptions of mortality, fertility, and migration by age and sex through 2050, based on the UN Population Division's World Population Prospects database medium variant.\nStatistical concept(s): Estimates of total population describe the size of total population. Population estimates are dependent on the demographic components of change that are fertility, mortality and migration. As the size of population continues to change throughout the time even within a year, a reference time in the year that the estimate refers to is needed, such as mid-year, end-year or beginning of year. The values shown are midyear estimates.","theme":"demo","source_group":"wb"},{"code":"BX.PEF.TOTL.CD.WD","name":"Actions de portefeuille, entrées nettes (BoP, $ US courants)","description":"Les capitaux propres du portefeuille comprennent les entrées nettes de titres de participation autres que ceux enregistrés comme investissement dir...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.PEF.TOTL.CD.WD?locations=CI","methodology":"Methodology: Data on equity flows are based on balance of payments data reported by the International Monetary Fund (IMF).\n\nPortfolio equity investment is defined as cross-border transactions and positions involving equity securities, other than those included in direct investment or reserve assets. Equity securities are equity instruments that are negotiable and designed to be traded, usually on organized exchanges or \"over the counter.\" The negotiability of securities facilitates trading, allowing securities to be held by different parties during their lives. Negotiability allows investors to diversify their portfolios and to withdraw their investment readily. Included in portfolio investment are investment fund shares or units (that is, those issued by investment funds) that are evidenced by securities and that are not reserve assets or direct investment. Although they are negotiable instruments, exchange-traded financial derivatives are not included in portfolio investment because they are in their own category.","theme":"inter","source_group":"wb"},{"code":"DT.NFL.BOND.CD","name":"Investissement de portefeuille, obligations (PPG + PNG) (NFL, $ US courants)","description":"Les obligations sont des titres émis avec un taux d'intérêt fixe pour une durée supérieure à un an.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.BOND.CD?locations=CI","methodology":"Methodology: Bonds are debt instruments issued by public and publicly guaranteed or private debtors with durations of one year or longer. Bonds usually give the holder the unconditional right to fixed money income or contractually determined, variable money income.\n\nData on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"BN.KLT.PTXL.CD","name":"Investissements de portefeuille, nets ($ US courants, BdP)","description":"Les investissements de portefeuille comprennent les flux transfrontaliers et les positions portant sur des titres de créance ou de capitaux propres...","source_link":"https://donnees.banquemondiale.org/indicateur/BN.KLT.PTXL.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"SI.POV.GAPS","name":"Écart de pauvreté à 3,00 $ par jour (PPA 2021) ( %)","description":"L'écart de pauvreté à 3,00 $ par jour (PPA 2021) est le déficit moyen de revenu ou de consommation par rapport au seuil de pauvreté de 3,00 $ par j...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.POV.GAPS?locations=CI","methodology":"Methodology: International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.Since World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in June 2025, when we adopted $3.00 as the international poverty line using the 2021 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $4.20 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $8.30 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.Early editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, 2011, 2021, and 2021 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $3.00 a day in 2021 PPP terms, which represents the median of the poverty lines found in 23 low-income countries. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.The statistics reported here are based on consumption data or, when unavailable, on income surveys.\nStatistical concept(s): The poverty gap measures the average shortfall in income or consumption of individuals living below the international poverty line of $3.00 per day, adjusted to 2021 purchasing power parity (PPP), expressed as a percentage of that poverty line. It essentially measures the depth of poverty—that is, how far the extreme poor are living below the poverty line.","theme":"social","source_group":"wb"},{"code":"SI.POV.LMIC.GP","name":"Écart de pauvreté à 4,20 dollars par jour (PPA 2021) ( %)","description":"L'écart de pauvreté à 4,20 dollars par jour (PPA 2021) est le déficit moyen de revenu ou de consommation par rapport au seuil de pauvreté de 4,20 d...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.POV.LMIC.GP?locations=CI","methodology":"Methodology: International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.\nSince World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when we adopted $3.00 as the international poverty line using the 2021 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $4.20 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $8.30 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.\nEarly editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2021 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $3.00 a day in 2021 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.\nThe statistics reported here are based on consumption data or, when unavailable, on income surveys.\nStatistical concept(s): The poverty gap at $4.20 measures the average shortfall in income or consumption of individuals living below the poverty line of $4.20 per day, adjusted to 2021 purchasing power parity (PPP), expressed as a percentage of that poverty line. It essentially measures the depth of poverty—that is, how far the poor are living below the lower-middle-income poverty line.","theme":"social","source_group":"wb"},{"code":"SI.POV.UMIC.GP","name":"Écart de pauvreté à 8,30 dollars par jour (PPA 2021) ( %)","description":"L'écart de pauvreté à 8,30 $ par jour (PPA 2021) est le déficit moyen de revenu ou de consommation par rapport au seuil de pauvreté de 8,30 $ par j...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.POV.UMIC.GP?locations=CI","methodology":"Methodology: International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.Since World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when we adopted $3.00 as the international poverty line using the 2021 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $4.20 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $8.30 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.Early editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2021 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $3.00 a day in 2021 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.The statistics reported here are based on consumption data or, when unavailable, on income surveys.\nStatistical concept(s): The poverty gap at $8.30 measures the average shortfall in income or consumption of individuals living below the poverty line of $8.30 per day, adjusted to 2021 purchasing power parity (PPP), expressed as a percentage of that poverty line. It essentially measures the depth of poverty—that is, how far the poor are living below the upper-middle-income poverty line.","theme":"social","source_group":"wb"},{"code":"SI.POV.DDAY","name":"Taux de pauvreté : 3,00 dollars par jour (PPA 2021) ( % de la population)","description":"Le taux de pauvreté à 3,00 dollars par jour est le pourcentage de la population vivant avec moins de 3,00 dollars par jour aux prix ajustés du pouv...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.POV.DDAY?locations=CI","methodology":"Methodology: International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.\nSince World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when we adopted $3.00 as the international poverty line using the 2021 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $4.20 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $8.30 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.\nEarly editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2021 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $3.00 a day in 2021 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.\nThe statistics reported here are based on consumption data or, when unavailable, on income surveys.\nStatistical concept(s): Poverty headcount ratio at $3.00 a day refers to the percentage of a population whose consumption or income per day falls short of the international poverty line of $3.00 a day (adjusted for purchasing power parity differences across countries), the poverty line typical of low-income countries.","theme":"social","source_group":"wb"},{"code":"SI.POV.LMIC","name":"Taux de pauvreté à 4,00 $ par jour (PPA 2021) ( % de la population)","description":"Le taux de pauvreté à 4,20 dollars par jour correspond au pourcentage de la population vivant avec moins de 4,20 dollars par jour aux prix internat...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.POV.LMIC?locations=CI","methodology":"Methodology: International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.\nSince World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when we adopted $3.00 as the international poverty line using the 2021 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $4.20 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $8.30 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.\nEarly editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2021 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $3.00 a day in 2021 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.\nThe statistics reported here are based on consumption data or, when unavailable, on income surveys.\nStatistical concept(s): Poverty headcount ratio at $4.20 a day refers to the percentage of a population whose consumption or income per day falls short of $4.20 a day (adjusted for purchasing power parity differences across countries). $4.20 is the typical poverty line of lower-middle-income countries.","theme":"social","source_group":"wb"},{"code":"SI.POV.UMIC","name":"Taux de pauvreté : 8,30 dollars par jour (PPA 2021) ( % de la population)","description":"Le taux de pauvreté à 8,30 dollars par jour correspond au pourcentage de la population vivant avec moins de 8,30 dollars par jour aux prix internat...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.POV.UMIC?locations=CI","methodology":"Methodology: International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.Since World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in September 2022, when we adopted $3.00 as the international poverty line using the 2021 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $4.20 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $8.30 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.Early editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2021 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $3.00 a day in 2021 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.The statistics reported here are based on consumption data or, when unavailable, on income surveys.\nStatistical concept(s): Poverty headcount ratio at $8.30 a day refers to the percentage of a population whose consumption or income per day falls short of $8.30 a day (adjusted for purchasing power parity differences across countries). $8.30 is the typical poverty line of upper-middle-income countries.","theme":"social","source_group":"wb"},{"code":"SI.POV.NAHC","name":"Taux de pauvreté aux seuils de pauvreté nationaux (en % de la population)","description":"Le taux de pauvreté national est le pourcentage de la population vivant en dessous du ou des seuils nationaux de pauvreté.","source_link":"https://donnees.banquemondiale.org/indicateur/SI.POV.NAHC?locations=CI","methodology":"Methodology: Poverty headcount ratio among the population is measured based on national (i.e. country-specific) poverty lines. A country may have a unique national poverty line or separate poverty lines for rural and urban areas, or for different geographic areas to reflect differences in the cost of living or sometimes to reflect differences in diets and consumption baskets.\nPoverty estimates at national poverty lines are computed from household survey data collected from nationally representative samples of households. These data must contain sufficiently detailed information to compute a comprehensive estimate of total household income or consumption (including consumption or income from own production), from which it is possible to construct a correctly weighted distribution of per capita consumption or income. \nNational poverty lines are the benchmark for estimating poverty indicators that are consistent with the country's specific economic and social circumstances. National poverty lines reflect local perceptions of the level and composition of consumption or income needed to be non-poor. The perceived boundary between poor and non-poor typically rises with the average income of a country and thus does not provide a uniform measure for comparing poverty rates across countries. While poverty rates at national poverty lines should not be used for comparing poverty rates across countries, they are appropriate for guiding and monitoring the results of country-specific national poverty reduction strategies. \nAlmost all national poverty lines in developing economies are anchored to the cost of a food bundle - based on the prevailing national diet of the poor - that provides adequate nutrition for good health and normal activity, plus an allowance for nonfood spending. National poverty lines must be adjusted for inflation between survey years to remain constant in real terms and thus allow for meaningful comparisons of poverty over time. Because diets and consumption baskets change over time, countries periodically recalculate the poverty line based on new survey data. In such cases the new poverty lines should be deflated to obtain comparable poverty estimates from earlier years. \nThis series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year. For all other economies, the year reported is the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which data collection started.\nStatistical concept(s): National poverty headcount ratio refers to the percentage of a population whose consumption or income per day falls short of the national poverty line. National poverty lines vary by country and over time. In low- and middle-income countries, national poverty lines tend to be absolute poverty lines, thus reflecting the estimated minimum amount of money needed to cover basic needs. In high-income countries, national poverty lines tend to be relative poverty lines, thus reflecting the typical amount of money needed for an individual to afford the typical standard of living and without any restraints to participating fully in the societies in which they live. National poverty lines tend to grow with economic growth, especially in high-income or upper-middle-income countries.","theme":"social","source_group":"wb"},{"code":"SI.POV.SOPO","name":"Taux de pauvreté au seuil de pauvreté sociétale ( % de la population)","description":"Le taux de pauvreté au seuil de pauvreté sociétale est le pourcentage d'une population vivant dans la pauvreté selon le seuil de pauvreté sociétale...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.POV.SOPO?locations=CI","methodology":"Methodology: The Societal Poverty Line (SPL) adopted by the World Bank is calculated in 2021 PPP U.S. dollars as follows: SPL = max (US$3.00, US$1.30 + 0.5 median consumption). By this definition, societal poverty represents a combination of extreme poverty, which is fixed in value for everyone, and a relative dimension of well-being that differs in every country depending on the median level of consumption in that country. In countries with low median consumption (less than US$2.00 per person per day), a rise in median consumption does not change the SPL. Indeed, the SPL has the same value as the IPL in all countries with median consumption up to $3.40. However, as countries with median consumption at more than US$3.40 become richer, and the median consumption increases, the value of the SPL also rises. The slope of one-half, the rate at which the SPL is rising as countries become richer, comes from the empirical association observed between national poverty lines and different measures of overall consumption in society. It indicates that, on average, the national poverty lines are increasing at a rate equal to half the median consumption in the countries. The slope of one-half and the intercept of US$1.30 are the values that most closely fit the data provided by the national poverty lines and overall consumption in each country. The SPL and the International Poverty Line (IPL) share the same empirical underpinning. Both are anchored in the distribution of national poverty lines, which represent countries’ own judgements of what poverty means for them. Whereas the IPL focuses narrowly—and deliberately—on the choices of some of the poorest countries, the SPL is built on information from across the whole range of levels of development. In addition to fitting the data well, the slope coefficient of half the median is widely used by many countries and organizations as a measure of relative poverty and inclusion.\nStatistical concept(s): Poverty headcount ratio at societal poverty line measures the share of the population living below the societal poverty line. The societal poverty line combines elements of both absolute and relative poverty. A minimum amount of money is required for subsistence (absolute poverty), while an additional amount of money is required to afford the typical lifestyle expected in the society in which people live (relative poverty). The societal poverty line is expressed as: max (US$3.00, US$1.30 + 0.5 median consumption) in 2021 PPP U.S. dollars. $1.30 represents the standard for absolute poverty, while 0.5 median consumption represents the standard for relative poverty. In very poor countries, typically with median consumption up to $3.40, it makes more sense to consider that poverty is entirely absolute, so that the effective societal poverty line becomes the international poverty line of $3.00.","theme":"social","source_group":"wb"},{"code":"DT.NFL.PBND.CD","name":"PPG, obligations (NFL, $ US courants)","description":"Dette publique et garantie par l'État provenant d'obligations émises publiquement ou placées par le secteur privé.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.PBND.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.PCBK.CD","name":"PPG, banques commerciales (NFL, $ US courants)","description":"Prêts bancaires commerciaux publics et garantis par l'État auprès de banques privées et d'autres institutions financières privées.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.PCBK.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.DOD.MIBR.CD","name":"PPG, BIRD (DoD, $ US courants)","description":"L’encours de la dette publique et garantie par l’État auprès de la Banque internationale pour la reconstruction et le développement (BIRD) est non ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.MIBR.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.DOD.MIDA.CD","name":"PPG, IDA (DoD, $ US courants)","description":"L’encours de la dette publique et garantie par l’État auprès de l’Association internationale de développement (IDA) est concessionnel.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.MIDA.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.OFFT.CD","name":"PPG, créanciers officiels (NFL, $ US courants)","description":"La dette publique et garantie par l'État auprès des créanciers officiels comprend les prêts des organisations internationales (prêts multilatéraux)...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.OFFT.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.PROP.CD","name":"PPG, autres créanciers privés (NFL, $ US courants)","description":"Autres crédits privés publics et garantis par l'État auprès de fabricants, d'exportateurs et d'autres fournisseurs de biens, ainsi que les crédits ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.PROP.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.NFL.PRVT.CD","name":"PPG, créanciers privés (NFL, $ US courants)","description":"La dette publique et garantie par l'État auprès de créanciers privés comprend les obligations qui sont soit émises publiquement, soit placées par l...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.NFL.PRVT.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"PA.NUS.PPP","name":"Facteur de conversion en PPA, PIB (UCL par dollar international)","description":"Le facteur de conversion en parité de pouvoir d'achat (PPA) est un facteur de conversion monétaire et un déflateur spatial des prix.","source_link":"https://donnees.banquemondiale.org/indicateur/PA.NUS.PPP?locations=CI","methodology":"Methodology: The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The recent 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model.\n\nICP estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years. Description of WDI extrapolation approach is available here: https://datahelpdesk.worldbank.org/knowledgebase/articles/665452-how-do-you-extrapolate-the-ppp-conversion-factors\n\nFor the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. For Eurostat-OECD PPP Programme, please refer to the following websites.\n(http://www.oecd.org/sdd/prices-ppp/)\n(https://ec.europa.eu/eurostat/web/purchasing-power-parities/overview)\n\nFor more information on the ICP and PPPs, please refer to the ICP website at https://www.worldbank.org/en/programs/icp.\nStatistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency.  In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. \n\nPPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures. See https://www.worldbank.org/en/programs/icp/methodology.","theme":"macro","source_group":"wb"},{"code":"PA.NUS.PRVT.PP","name":"Facteur de conversion PPA, consommation privée (UCL par dollar international)","description":"Le facteur de conversion en parité de pouvoir d'achat (PPA) est un facteur de conversion monétaire et un déflateur spatial des prix.","source_link":"https://donnees.banquemondiale.org/indicateur/PA.NUS.PRVT.PP?locations=CI","methodology":"Methodology: The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model.\n\nICP-estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years.    Description of WDI extrapolation approach is available here: https://datahelpdesk.worldbank.org/knowledgebase/articles/665452-how-do-you-extrapolate-the-ppp-conversion-factors\n\nFor the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. For Eurostat-OECD PPP Programme, please refer to the following websites.\n(http://www.oecd.org/sdd/prices-ppp/)\n(https://ec.europa.eu/eurostat/web/purchasing-power-parities/overview)\n\nFor more information on the ICP and PPPs, please refer to the ICP website at https://www.worldbank.org/en/programs/icp.\nStatistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency.  In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. \n\nPPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures. See https://www.worldbank.org/en/programs/icp/methodology.","theme":"macro","source_group":"wb"},{"code":"SH.STA.ANVC.ZS","name":"Femmes enceintes recevant des soins prénatals ( %)","description":"Les femmes enceintes bénéficiant de soins prénatals représentent le pourcentage de femmes suivies au moins une fois pendant leur grossesse par un p...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.ANVC.ZS?locations=CI","methodology":"Methodology: Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\nGood prenatal and postnatal care improves maternal health and reduces maternal and infant mortality. However, indicators on use of antenatal care services provide no information on the content or quality of the services. Data on antenatal care are obtained mostly from household surveys, which ask women who have had a live birth whether and from whom they received antenatal care.","theme":"sante","source_group":"wb"},{"code":"SE.PRE.DURS","name":"Enseignement préprimaire, durée (années)","description":"La durée de l'enseignement préscolaire fait référence au nombre de classes (années) de l'école préscolaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRE.DURS?locations=CI","methodology":"Methodology: Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Aggregate data are based on World Bank estimates.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator measures the number of years that a country's laws or regulations specify for the preprimary stage of education. The definition of pre-primary education as programs that introduce children, typically starting at the age of 3, to a structured school environment and serve as a transition from home to school aligns with UNESCO's description(https://learningportal.iiep.unesco.org/en/glossary/pre-primary-education).","theme":"education","source_group":"wb"},{"code":"DT.DOD.PVLX.EX.ZS","name":"Valeur actuelle de la dette extérieure (en % des exportations de biens, de services et de revenus)","description":"Valeur actuelle de la dette extérieure par rapport aux exportations de biens, de services et de revenus.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.PVLX.EX.ZS?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.DOD.PVLX.GN.ZS","name":"Valeur actuelle de la dette extérieure ( % du RNB)","description":"Valeur actuelle de la dette extérieure par rapport au revenu national brut.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.PVLX.GN.ZS?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.DOD.PVLX.CD","name":"Valeur actuelle de la dette extérieure (en dollars américains courants)","description":"La valeur actuelle de la dette est la somme de la dette extérieure à court terme plus la somme actualisée du total des paiements du service de la d...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.PVLX.CD?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"SH.ANM.CHLD.ZS","name":"Prévalence de l'anémie chez les enfants ( % des enfants âgés de 6 à 59 mois)","description":"La prévalence de l'anémie chez les enfants âgés de 6 à 59 mois correspond au pourcentage d'enfants âgés de 6 à 59 mois dont le taux d'hémoglobine e...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.ANM.CHLD.ZS?locations=CI","methodology":"Methodology: Data on anemia are compiled by the WHO, and a statistical model was used to estimate trends. WHO’s hemoglobin threshold concentration in blood was used.","theme":"sante","source_group":"wb"},{"code":"SH.ANM.NPRG.ZS","name":"Prévalence de l'anémie chez les femmes non enceintes ( % des femmes âgées de 15 à 49 ans)","description":"La prévalence de l'anémie chez les femmes non enceintes est le pourcentage de femmes non enceintes dont le taux d'hémoglobine est inférieur à 120 g...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.ANM.NPRG.ZS?locations=CI","methodology":"Methodology: Data on the prevalence of anaemia and/or mean haemoglobin levels in women of reproductive age, collected between 1995 and 2019, were obtained from 408 population-representative data sources across 124 countries worldwide. A Bayesian hierarchical mixture model was employed to estimate haemoglobin distributions, systematically addressing missing data, non-linear time trends, and the representativeness of data sources. Full details on data sources are available on the GHO Anaemia page. Detailed information on the statistical methods can be found in the following reference: Finucane MM, Paciorek CJ, Stevens GA EM. Semiparametric Bayesian density estimation with disparate data sources: a meta-analysis of global childhood undernutrition. J Am Stat Assoc. 2015;110(511):889–901.","theme":"sante","source_group":"wb"},{"code":"SH.PRG.ANEM","name":"Prévalence de l'anémie chez les femmes enceintes ( %)","description":"La prévalence de l'anémie chez les femmes enceintes est le pourcentage de femmes enceintes dont le taux d'hémoglobine est inférieur à 110 grammes p...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.PRG.ANEM?locations=CI","methodology":"Methodology: Anemia is a condition in which the number of red blood cells or their oxygen-carrying capacity is insufficient to meet physiologic needs, which vary by age, sex, altitude, smoking status, and pregnancy status. In its severe form it is associated with fatigue, weakness, dizziness, and drowsiness. Children under age 5 and pregnant women have the highest risk for anemia.","theme":"sante","source_group":"wb"},{"code":"SH.ANM.ALLW.ZS","name":"Prévalence de l'anémie chez les femmes en âge de procréer ( % des femmes âgées de 15 à 49 ans)","description":"La prévalence de l'anémie chez les femmes en âge de procréer fait référence à la prévalence combinée des femmes non enceintes ayant un taux d'hémog...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.ANM.ALLW.ZS?locations=CI","methodology":"Methodology: Data on the prevalence of anaemia and/or mean haemoglobin levels in women of reproductive age, collected between 1995 and 2019, were obtained from 408 population-representative data sources across 124 countries worldwide. A Bayesian hierarchical mixture model was employed to estimate haemoglobin distributions, systematically addressing missing data, non-linear time trends, and the representativeness of data sources. Full details on data sources are available on the GHO Anaemia page. Detailed information on the statistical methods can be found in the following reference: Finucane MM, Paciorek CJ, Stevens GA EM. Semiparametric Bayesian density estimation with disparate data sources: a meta-analysis of global childhood undernutrition. J Am Stat Assoc. 2015;110(511):889–901.","theme":"sante","source_group":"wb"},{"code":"SH.PRV.SMOK","name":"Prévalence de l'usage actuel du tabac ( % des adultes)","description":"Pourcentage de la population âgée de 15 ans et plus qui consomme actuellement un produit du tabac (tabac fumé et/ou sans fumée) de manière quotidie...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.PRV.SMOK?locations=CI","methodology":"Methodology: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information. To compensate for this and improve reliability and international comparability, the World Health Organization (WHO) prepares estimates in accordance with epidemiological models and statistical standards.\n\nA statistical model based on a Bayesian negative binomial meta-regression is used to model prevalence of current tobacco use for each country, separately for men and women. \n\nThe model has two main components: (a) adjusting for missing indicators and age groups, and (b) generating an estimate of trends over time as well as the 95% credible interval around the estimate. \n\nDepending on the completeness/comprehensiveness of survey data from a particular country, the model at times makes use of data from other countries to fill information gaps. When a country has fewer than two nationally representative population-based surveys in different years, no attempt is made to fill data gaps and no estimates are calculated. To fill data gaps, information is “borrowed” from countries in the same UN subregion. The resulting trend lines are used to derive estimates for single years, so that a number can be reported even if the country did not run a survey in that year. In order to make the results comparable between countries, the prevalence rates are age-standardized to the WHO Standard Population. A full description of the method is available as a peer-reviewed article in The Lancet, volume 385, No. 9972, p966–976 (2015).","theme":"sante","source_group":"wb"},{"code":"SH.PRV.SMOK.FE","name":"Prévalence de l'usage actuel du tabac, femmes ( % des femmes adultes)","description":"Pourcentage de la population féminine âgée de 15 ans et plus qui consomme actuellement un produit du tabac (tabac fumé et/ou sans fumée) de manière...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.PRV.SMOK.FE?locations=CI","methodology":"Methodology: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information. To compensate for this and improve reliability and international comparability, the World Health Organization (WHO) prepares estimates in accordance with epidemiological models and statistical standards.\n\nA statistical model based on a Bayesian negative binomial meta-regression is used to model prevalence of current tobacco use for each country, separately for men and women. \n\nThe model has two main components: (a) adjusting for missing indicators and age groups, and (b) generating an estimate of trends over time as well as the 95% credible interval around the estimate. \n\nDepending on the completeness/comprehensiveness of survey data from a particular country, the model at times makes use of data from other countries to fill information gaps. When a country has fewer than two nationally representative population-based surveys in different years, no attempt is made to fill data gaps and no estimates are calculated. To fill data gaps, information is “borrowed” from countries in the same UN subregion. The resulting trend lines are used to derive estimates for single years, so that a number can be reported even if the country did not run a survey in that year. In order to make the results comparable between countries, the prevalence rates are age-standardized to the WHO Standard Population. A full description of the method is available as a peer-reviewed article in The Lancet, volume 385, No. 9972, p966–976 (2015).","theme":"sante","source_group":"wb"},{"code":"SH.PRV.SMOK.MA","name":"Prévalence de l'usage actuel du tabac, hommes ( % des hommes adultes)","description":"Pourcentage de la population masculine âgée de 15 ans et plus qui consomme actuellement un produit du tabac (tabac fumé et/ou sans fumée) quotidien...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.PRV.SMOK.MA?locations=CI","methodology":"Methodology: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information. To compensate for this and improve reliability and international comparability, the World Health Organization (WHO) prepares estimates in accordance with epidemiological models and statistical standards.\n\n\n\nSmoking is the most common form of tobacco use and the prevalence of smoking is therefore a good measure of the tobacco epidemic. (Corrao MA, Guindon GE, Sharma N, Shokoohi  DF (eds). Tobacco Control Country Profiles, 2000, American Cancer Society, Atlanta.) Tobacco use causes heart and other vascular diseases and cancers of the lung and other organs. Given the long delay between starting to smoke and the onset of disease, the health impact of smoking will increase rapidly only in the next few decades. The data presented are age-standardized rates for adults ages 15 and older from the WHO.","theme":"sante","source_group":"wb"},{"code":"SH.HIV.1524.FE.ZS","name":"Prévalence du VIH, femmes ( % 15-24 ans)","description":"La prévalence du VIH chez les femmes est le pourcentage de femmes infectées par le VIH.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.HIV.1524.FE.ZS?locations=CI","methodology":"Methodology: HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable.\nData on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates.","theme":"sante","source_group":"wb"},{"code":"SH.HIV.1524.MA.ZS","name":"Prévalence du VIH, hommes ( % 15-24 ans)","description":"La prévalence du VIH chez les hommes est le pourcentage d'hommes infectés par le VIH.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.HIV.1524.MA.ZS?locations=CI","methodology":"Methodology: HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable.\nData on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates.","theme":"sante","source_group":"wb"},{"code":"SH.DYN.AIDS.ZS","name":"Prévalence du VIH, total ( % de la population âgée de 15 à 49 ans)","description":"La prévalence du VIH fait référence au pourcentage de personnes âgées de 15 à 49 ans infectées par le VIH.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.AIDS.ZS?locations=CI","methodology":"Methodology: Data on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates.\nStatistical concept(s): HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable.","theme":"sante","source_group":"wb"},{"code":"SN.ITK.MSFI.ZS","name":"Prévalence de l'insécurité alimentaire modérée ou grave dans la population ( %)","description":"Pourcentage de personnes dans la population vivant dans des ménages classés comme étant en insécurité alimentaire modérée ou grave.","source_link":"https://donnees.banquemondiale.org/indicateur/SN.ITK.MSFI.ZS?locations=CI","methodology":"Methodology: The assessment is conducted using data collected with the Food Insecurity Experience Scale or a compatible experience-based food security measurement questionnaire (such as the HFSSM). The probability to be food insecure is estimated using the one-parameter logistic Item Response Theory model (the Rasch model) and thresholds for classification are made cross country comparable by calibrating the metrics obtained in each country against the FIES global reference scale, maintained by FAO. The threshold to classify \"moderate or severe\" food insecurity corresponds to the severity associated with the item \"having to eat less\" on the global FIES scale. It is an indicator of lack of food access.The indicator is calculated as an average over 3 years (eg. data for 2015 is the average of 2014-2016 data).","theme":"sante","source_group":"wb"},{"code":"SH.STA.OWGH.ZS","name":"Prévalence du surpoids, rapport poids/taille ( % des enfants de moins de 5 ans)","description":"La prévalence des enfants en surpoids est le pourcentage d'enfants de moins de 5 ans dont le rapport poids/taille est supérieur de plus de deux éca...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.OWGH.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child overweight refers to a child who is too heavy for his or her height. This form of malnutrition results from expending too few calories for the amount of food consumed and increases the risk of noncommunicable diseases later in life.","theme":"sante","source_group":"wb"},{"code":"SH.STA.OWGH.ME.ZS","name":"Prévalence du surpoids (estimation modélisée, % des enfants de moins de 5 ans)","description":"La prévalence des enfants en surpoids est le pourcentage d'enfants de moins de 5 ans dont le rapport poids/taille est supérieur de plus de deux éca...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.OWGH.ME.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child overweight refers to a child who is too heavy for his or her height. This form of malnutrition results from expending too few calories for the amount of food consumed and increases the risk of noncommunicable diseases later in life.","theme":"sante","source_group":"wb"},{"code":"SH.STA.OWGH.FE.ZS","name":"Prévalence du surpoids, poids par rapport à la taille, femmes ( % des enfants de moins de 5 ans)","description":"La prévalence du surpoids chez les femmes est le pourcentage de filles de moins de 5 ans dont le rapport poids/taille est supérieur de plus de deux...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.OWGH.FE.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child overweight refers to a child who is too heavy for his or her height. This form of malnutrition results from expending too few calories for the amount of food consumed and increases the risk of noncommunicable diseases later in life.","theme":"sante","source_group":"wb"},{"code":"SH.STA.OWGH.ME.FE.ZS","name":"Prévalence du surpoids chez les femmes (estimation modélisée, % d'enfants de moins de 5 ans)","description":"La prévalence du surpoids chez les femmes est le pourcentage de filles de moins de 5 ans dont le rapport poids/taille est supérieur de plus de deux...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.OWGH.ME.FE.ZS?locations=CI","methodology":"","theme":"sante","source_group":"wb"},{"code":"SH.STA.OWGH.MA.ZS","name":"Prévalence du surpoids, rapport poids/taille, hommes ( % d'enfants de moins de 5 ans)","description":"La prévalence du surpoids chez les hommes est le pourcentage de garçons de moins de 5 ans dont le rapport poids/taille est supérieur de plus de deu...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.OWGH.MA.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child overweight refers to a child who is too heavy for his or her height. This form of malnutrition results from expending too few calories for the amount of food consumed and increases the risk of noncommunicable diseases later in life.","theme":"sante","source_group":"wb"},{"code":"SH.STA.OWGH.ME.MA.ZS","name":"Prévalence du surpoids chez les hommes (estimation modélisée, % d'enfants de moins de 5 ans)","description":"La prévalence du surpoids chez les hommes est le pourcentage de garçons de moins de 5 ans dont le rapport poids/taille est supérieur de plus de deu...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.OWGH.ME.MA.ZS?locations=CI","methodology":"","theme":"sante","source_group":"wb"},{"code":"SN.ITK.SVFI.ZS","name":"Prévalence de l'insécurité alimentaire sévère dans la population ( %)","description":"Le pourcentage de personnes dans la population qui vivent dans des ménages classés comme étant en situation d’insécurité alimentaire grave.","source_link":"https://donnees.banquemondiale.org/indicateur/SN.ITK.SVFI.ZS?locations=CI","methodology":"Methodology: The assessment is conducted using data collected with the Food Insecurity Experience Scale or a compatible experience-based food security measurement questionnaire (such as the HFSSM). The probability to be food insecure is estimated using the one-parameter logistic Item Response Theory model (the Rasch model) and thresholds for classification are made cross country comparable by calibrating the metrics obtained in each country against the FIES global reference scale, maintained by FAO. The threshold to classify \"severe\" food insecurity corresponds to the severity associated with the item \"having not eaten for an entire day\" on the global FIES scale. It is an indicator of lack of food access.The indicator is calculated as an average over 3 years (eg. data for 2015 is the average of 2014-2016 data).","theme":"sante","source_group":"wb"},{"code":"SH.SVR.WAST.ZS","name":"Prévalence de l'émaciation sévère, rapport poids/taille ( % des enfants de moins de 5 ans)","description":"La prévalence de l’émaciation sévère est la proportion d’enfants de moins de 5 ans dont le rapport poids/taille est inférieur de plus de trois écar...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.SVR.WAST.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child wasting refers to a child who is too thin for his or her height and is the result of recent rapid weight loss or the failure to gain weight. A child who is moderately or severely wasted has an increased risk of death, but treatment is possible.","theme":"sante","source_group":"wb"},{"code":"SH.SVR.WAST.FE.ZS","name":"Prévalence de l'émaciation sévère, poids par rapport à la taille, femmes ( % d'enfants de moins de 5 ans)","description":"La prévalence de l'émaciation sévère chez les femmes est la proportion de filles de moins de 5 ans dont le rapport poids/taille est inférieur de pl...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.SVR.WAST.FE.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child wasting refers to a child who is too thin for his or her height and is the result of recent rapid weight loss or the failure to gain weight. A child who is moderately or severely wasted has an increased risk of death, but treatment is possible.","theme":"sante","source_group":"wb"},{"code":"SH.SVR.WAST.MA.ZS","name":"Prévalence de l'émaciation sévère, rapport poids/taille, hommes ( % des enfants de moins de 5 ans)","description":"La prévalence de l'émaciation sévère chez les hommes correspond à la proportion de garçons de moins de 5 ans dont le rapport poids/taille est infér...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.SVR.WAST.MA.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child wasting refers to a child who is too thin for his or her height and is the result of recent rapid weight loss or the failure to gain weight. A child who is moderately or severely wasted has an increased risk of death, but treatment is possible.","theme":"sante","source_group":"wb"},{"code":"SH.STA.STNT.ZS","name":"Prévalence du retard de croissance, taille par rapport à l'âge ( % d'enfants de moins de 5 ans)","description":"La prévalence du retard de croissance est le pourcentage d'enfants de moins de 5 ans dont la taille par rapport à l'âge est inférieure de plus de d...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.STNT.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child stunting refers to a child who is too short for his or her age and is the result of chronic or recurrent malnutrition. Stunting is a contributing risk factor to child mortality and is also a marker of inequalities in human development. Stunted children fail to reach their physical and cognitive potential. Child stunting is one of the World Health Assembly nutrition target indicators.","theme":"sante","source_group":"wb"},{"code":"SH.STA.STNT.ME.ZS","name":"Prévalence du retard de croissance, taille par rapport à l'âge (estimation modélisée, % d'enfants de moins de 5 ans)","description":"La prévalence du retard de croissance est le pourcentage d'enfants de moins de 5 ans dont la taille par rapport à l'âge est inférieure de plus de d...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.STNT.ME.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child stunting refers to a child who is too short for his or her age and is the result of chronic or recurrent malnutrition. Stunting is a contributing risk factor to child mortality and is also a marker of inequalities in human development. Stunted children fail to reach their physical and cognitive potential. Child stunting is one of the World Health Assembly nutrition target indicators.","theme":"sante","source_group":"wb"},{"code":"SH.STA.STNT.FE.ZS","name":"Prévalence du retard de croissance, taille par rapport à l'âge, sexe féminin ( % d'enfants de moins de 5 ans)","description":"La prévalence du retard de croissance chez les femmes est le pourcentage de filles de moins de 5 ans dont la taille par rapport à l'âge est inférie...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.STNT.FE.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child stunting refers to a child who is too short for his or her age and is the result of chronic or recurrent malnutrition. Stunting is a contributing risk factor to child mortality and is also a marker of inequalities in human development. Stunted children fail to reach their physical and cognitive potential. Child stunting is one of the World Health Assembly nutrition target indicators.","theme":"sante","source_group":"wb"},{"code":"SH.STA.STNT.ME.FE.ZS","name":"Prévalence du retard de croissance, taille par rapport à l'âge, sexe féminin (estimation modélisée, % d'enfants de moins de 5 ans)","description":"La prévalence du retard de croissance chez les femmes est le pourcentage de filles de moins de 5 ans dont la taille par rapport à l'âge est inférie...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.STNT.ME.FE.ZS?locations=CI","methodology":"","theme":"sante","source_group":"wb"},{"code":"SH.STA.STNT.MA.ZS","name":"Prévalence du retard de croissance, taille par rapport à l'âge, hommes ( % d'enfants de moins de 5 ans)","description":"La prévalence du retard de croissance chez les hommes correspond au pourcentage de garçons de moins de 5 ans dont la taille par rapport à l'âge est...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.STNT.MA.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child stunting refers to a child who is too short for his or her age and is the result of chronic or recurrent malnutrition. Stunting is a contributing risk factor to child mortality and is also a marker of inequalities in human development. Stunted children fail to reach their physical and cognitive potential. Child stunting is one of the World Health Assembly nutrition target indicators.","theme":"sante","source_group":"wb"},{"code":"SH.STA.STNT.ME.MA.ZS","name":"Prévalence du retard de croissance, taille par rapport à l'âge, hommes (estimation modélisée, % d'enfants de moins de 5 ans)","description":"La prévalence du retard de croissance chez les hommes correspond au pourcentage de garçons de moins de 5 ans dont la taille par rapport à l'âge est...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.STNT.ME.MA.ZS?locations=CI","methodology":"","theme":"sante","source_group":"wb"},{"code":"SN.ITK.DEFC.ZS","name":"Prévalence de la sous-alimentation ( % de la population)","description":"La prévalence de la sous-alimentation est le pourcentage de la population dont la consommation alimentaire habituelle est insuffisante pour fournir...","source_link":"https://donnees.banquemondiale.org/indicateur/SN.ITK.DEFC.ZS?locations=CI","methodology":"Methodology: Data on undernourishment are from the Food and Agriculture Organization (FAO) of the United Nations and measure food deprivation based on average food available for human consumption per person, the level of inequality in access to food, and the minimum calories required for an average person.\nStatistical concept(s): Data on undernourishment are from the Food and Agriculture Organization (FAO) of the United Nations and measure food deprivation based on average food available for human consumption per person, the level of inequality in access to food, and the minimum calories required for an average person.","theme":"sante","source_group":"wb"},{"code":"SH.STA.MALN.ZS","name":"Prévalence de l'insuffisance pondérale, poids par rapport à l'âge ( % des enfants de moins de 5 ans)","description":"La prévalence des enfants présentant une insuffisance pondérale est le pourcentage d'enfants de moins de 5 ans dont le poids par rapport à l'âge es...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.MALN.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child underweight belongs to a set of indicators whose purpose is to measure nutritional imbalance and malnutrition resulting in undernutrition (assessed by underweight, stunting and wasting) and overweight.","theme":"sante","source_group":"wb"},{"code":"SH.STA.MALN.FE.ZS","name":"Prévalence de l'insuffisance pondérale, poids par rapport à l'âge, femmes ( % d'enfants de moins de 5 ans)","description":"La prévalence de l'insuffisance pondérale chez les femmes est le pourcentage de filles de moins de 5 ans dont le poids par rapport à l'âge est infé...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.MALN.FE.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child underweight belongs to a set of indicators whose purpose is to measure nutritional imbalance and malnutrition resulting in undernutrition (assessed by underweight, stunting and wasting) and overweight.","theme":"sante","source_group":"wb"},{"code":"SH.STA.MALN.MA.ZS","name":"Prévalence de l'insuffisance pondérale, poids par rapport à l'âge, hommes ( % des enfants de moins de 5 ans)","description":"La prévalence de l'insuffisance pondérale chez les hommes est le pourcentage de garçons de moins de 5 ans dont le poids par rapport à l'âge est inf...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.MALN.MA.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child underweight belongs to a set of indicators whose purpose is to measure nutritional imbalance and malnutrition resulting in undernutrition (assessed by underweight, stunting and wasting) and overweight.","theme":"sante","source_group":"wb"},{"code":"SH.STA.WAST.ZS","name":"Prévalence de l'émaciation, rapport poids/taille ( % des enfants de moins de 5 ans)","description":"La prévalence de l'émaciation est la proportion d'enfants de moins de 5 ans dont le rapport poids/taille est inférieur de plus de deux écarts types...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.WAST.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child wasting refers to a child who is too thin for his or her height and is the result of recent rapid weight loss or the failure to gain weight. A child who is moderately or severely wasted has an increased risk of death, but treatment is possible.","theme":"sante","source_group":"wb"},{"code":"SH.STA.WAST.FE.ZS","name":"Prévalence de l'émaciation, poids par rapport à la taille, femmes ( % d'enfants de moins de 5 ans)","description":"La prévalence de l'émaciation chez les femmes est la proportion de filles de moins de 5 ans dont le rapport poids/taille est inférieur de plus de d...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.WAST.FE.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child wasting refers to a child who is too thin for his or her height and is the result of recent rapid weight loss or the failure to gain weight. A child who is moderately or severely wasted has an increased risk of death, but treatment is possible.","theme":"sante","source_group":"wb"},{"code":"SH.STA.WAST.MA.ZS","name":"Prévalence de l'émaciation, poids par rapport à la taille, hommes ( % des enfants de moins de 5 ans)","description":"La prévalence de l'émaciation chez les hommes est la proportion de garçons de moins de 5 ans dont le rapport poids/taille est inférieur de plus de ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.WAST.MA.ZS?locations=CI","methodology":"Methodology: Survey estimates are based on standardized methodology using the WHO Child Growth Standards as described elsewhere.\nStatistical concept(s): Child wasting refers to a child who is too thin for his or her height and is the result of recent rapid weight loss or the failure to gain weight. A child who is moderately or severely wasted has an increased risk of death, but treatment is possible.","theme":"sante","source_group":"wb"},{"code":"PA.NUS.PPPC.RF","name":"Rapport du taux de conversion (PIB) de la PPA au taux de change du marché","description":"Le rapport du niveau des prix, ou indice du niveau des prix, est le rapport entre un facteur de conversion de parité de pouvoir d'achat (PPA) et le...","source_link":"https://donnees.banquemondiale.org/indicateur/PA.NUS.PPPC.RF?locations=CI","methodology":"Methodology: For more information on market exchange rate, please refer to the metadata for \"DEC alternative conversion factor (LCU per US$)\" [PA.NUS.ATLS].\nFor the concept and methodology of PPP, please refer to the International Comparison Program (ICP)’s website (https://www.worldbank.org/en/programs/icp).\nStatistical concept(s): 1. The ratio of the GDPs of two economies when both are valued at national price levels and\nexpressed in local currency units has three component ratios:\nGDP ratio = price level ratio × volume ratio × currency ratio. (B3.1.1)\n2. When converting the GDP ratio in equation (B3.1.1) to a common currency using the\nmarket exchange rate, the resulting GDPXR ratio has two component ratios:\nGDPXR ratio = price level ratio × volume ratio. (B3.1.2)\n The GDP ratio in equation (B3.1.2) is expressed in a common currency, but it reflects both\nthe price level differences and the volume differences between the two economies.\n3. A PPP is defined as a spatial price deflator and currency converter. It is composed of two\ncomponent ratios:\nPPP = price level ratio × currency ratio. (B3.1.3)\n4. When a PPP is used, the GDP ratio in equation (B3.1.1) is divided by equation (B3.1.3),\nand the resulting GDPPPP ratio has only one component ratio:\nGDPPPP ratio = volume ratio. (B3.1.4)\n The GDP ratio in equation (B3.1.4) is expressed in a common currency, is valued at a common price level, and reflects only differences in volume between the two economies.","theme":"macro","source_group":"wb"},{"code":"SE.PRM.CMPT.FE.ZS","name":"Taux d'achèvement de l'enseignement primaire, femmes ( % de la tranche d'âge concernée)","description":"Le taux d'achèvement du primaire, ou taux brut d'admission à la dernière année de l'enseignement primaire, est le nombre de nouveaux inscrits (insc...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.CMPT.FE.ZS?locations=CI","methodology":"Methodology: Primary completion rate is calculated by dividing the number of new entrants (enrollment minus repeaters) in the last grade of primary education, regardless of age, by the population at the entrance age for the last grade of primary education and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The indicator represents the influence of policies regarding entry and progress through the initial stages of primary or lower secondary education on the completion of the terminal grade at the respective level. The presumption is that students who enroll in the final grade for the first time will successfully finish that grade, thereby completing the designated level of education.","theme":"education","source_group":"wb"},{"code":"SE.PRM.CMPT.MA.ZS","name":"Taux d'achèvement de l'enseignement primaire, hommes ( % de la tranche d'âge concernée)","description":"Le taux d'achèvement du primaire, ou taux brut d'admission à la dernière année de l'enseignement primaire, est le nombre de nouveaux inscrits (insc...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.CMPT.MA.ZS?locations=CI","methodology":"Methodology: Primary completion rate is calculated by dividing the number of new entrants (enrollment minus repeaters) in the last grade of primary education, regardless of age, by the population at the entrance age for the last grade of primary education and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuse\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The indicator represents the influence of policies regarding entry and progress through the initial stages of primary or lower secondary education on the completion of the terminal grade at the respective level. The presumption is that students who enroll in the final grade for the first time will successfully finish that grade, thereby completing the designated level of education.","theme":"education","source_group":"wb"},{"code":"SE.PRM.CMPT.ZS","name":"Taux d'achèvement du primaire, total ( % de la tranche d'âge concernée)","description":"Le taux d'achèvement du primaire, ou taux brut d'admission à la dernière année de l'enseignement primaire, est le nombre de nouveaux inscrits (insc...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.CMPT.ZS?locations=CI","methodology":"Methodology: Primary completion rate is calculated by dividing the number of new entrants (enrollment minus repeaters) in the last grade of primary education, regardless of age, by the population at the entrance age for the last grade of primary education and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The indicator represents the influence of policies regarding entry and progress through the initial stages of primary or lower secondary education on the completion of the terminal grade at the respective level. The presumption is that students who enroll in the final grade for the first time will successfully finish that grade, thereby completing the designated level of education.","theme":"education","source_group":"wb"},{"code":"SE.PRM.DURS","name":"Enseignement primaire, durée (années)","description":"La durée du primaire fait référence au nombre de classes (années) à l'école primaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.DURS?locations=CI","methodology":"Methodology: Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Aggregate data are based on World Bank estimates.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator measures the number of years that a country's laws or regulations specify for primary education.  It aids in identifying the population of school-aged children at different educational levels. Additionally, this metric serves as crucial input data necessary for generating various indicators and evaluating a country's capacity to meet educational demand.","theme":"education","source_group":"wb"},{"code":"SE.PRM.ENRL","name":"Enseignement primaire, élèves","description":"Les élèves de l'enseignement primaire correspondent au nombre total d'élèves inscrits au niveau primaire dans les écoles publiques et privées.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.ENRL?locations=CI","methodology":"Methodology: Enrollment includes Individuals officially registered in a given educational programme, or stage or module thereof, regardless of age.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): Educational programs at the International Standard Classification of Education (ISCED) level 1, commonly referred to as primary education, are fundamentally structured to equip students with essential literacy and numeracy skills. These programs aim to lay a robust groundwork for learning, fostering an understanding of key knowledge domains, and promoting personal and social growth, thereby readying students for the subsequent stage of lower secondary education.\n\n\n\n\n\n\n\n\n\n\n\n\n\nEntry into this level is predominantly based on age, with the typical or legally mandated age of enrollment ranging from 5 to 7 years old. The duration of primary education is generally six years, though it can vary from four to seven years, concluding when students are between 10 to 12 years old (refer to Paragraphs 132 to 134 for further details). Upon successful completion of primary education, students are eligible to progress to ISCED level 2, which corresponds to lower secondary education.","theme":"education","source_group":"wb"},{"code":"SE.PRM.ENRL.FE.ZS","name":"Enseignement primaire, élèves ( % de filles)","description":"Les filles en pourcentage du total des élèves du primaire comprennent les inscriptions dans les écoles publiques et privées.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.ENRL.FE.ZS?locations=CI","methodology":"Methodology: Percentage of female enrollment is calculated by dividing the total number of female students at a given level of education by the total enrollment at the same level, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.PRM.TCHR","name":"Enseignement primaire, enseignants","description":"Dans l'enseignement primaire, les enseignants font référence au nombre total d'enseignants au niveau primaire, y compris les enseignants à temps pl...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.TCHR?locations=CI","methodology":"Methodology: Teachers refer to persons employed full-time or part-time in an official capacity to guide and direct the learning experience of pupils and students, irrespective of their qualifications or the delivery mechanism, i.e. face-to-face and/or at a distance. This definition excludes educational personnel who have no active teaching duties (e.g. headmasters, headmistresses or principals who do not teach) or who work occasionally or in a voluntary capacity in educational institutions.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The metric of personnel count primarily engaged in teaching and/or research reflects the scale, diversity, and distribution of educational staff within a nation's academic institutions. An increased count is anticipated to enrich the educational setting by means of dedicated teaching, practical research, academic pursuits, and contributions to the service of national educational policies.","theme":"education","source_group":"wb"},{"code":"SE.PRM.TCHR.FE.ZS","name":"Enseignement primaire, enseignants ( % de femmes)","description":"Les enseignantes, en pourcentage du total des enseignants du primaire, comprennent les enseignantes à temps plein et à temps partiel.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.TCHR.FE.ZS?locations=CI","methodology":"Methodology: The share of female teachers in primary education is calculated by dividing the total number of female teachers at primary level of education by the total number of teachers at the same level, and multiplying by 100.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The share of female teachers shows the level of gender representation in the teaching force. A value of greater than 50% indicates more opportunities or preference for women to participate in teaching activities.","theme":"education","source_group":"wb"},{"code":"GF.XPD.BUDG.ZS","name":"Dépenses publiques primaires en proportion du budget initial approuvé ( %)","description":"Dépenses publiques primaires en proportion des mesures budgétaires initialement approuvées : mesure dans laquelle les dépenses budgétaires globales...","source_link":"https://donnees.banquemondiale.org/indicateur/GF.XPD.BUDG.ZS?locations=CI","methodology":"","theme":"finance","source_group":"wb"},{"code":"BM.GSR.FCTY.CD","name":"Paiements de revenus primaires (BoP, $ US courants)","description":"Les paiements de revenus primaires font référence aux rémunérations versées aux travailleurs non-résidents et aux revenus d'investissement (paiemen...","source_link":"https://donnees.banquemondiale.org/indicateur/BM.GSR.FCTY.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BX.GSR.FCTY.CD","name":"Recettes des revenus primaires (BdP, $ US courants)","description":"Les recettes de revenus primaires font référence à la rémunération versée aux travailleurs résidents travaillant à l’étranger et aux revenus d’inve...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GSR.FCTY.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"SE.LPV.PRIM.SD","name":"Enfants en âge de fréquenter l'école primaire non scolarisés ( %)","description":"La proportion d’enfants en âge d’aller à l’école primaire qui ne sont pas scolarisés ou qui sont privés de scolarité.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.LPV.PRIM.SD?locations=CI","methodology":"Methodology: Schooling Deprivation is derived using enrollment rates computed by UIS using administrative records and follows the SDG 4.1.4 indicator. To ensure country coverage of data, we consider other enrollment definitions to use for learning poverty, if the first-best option is not available. \nWe construct an enrollment dataset from 1990 to the year of the current release, relying on multiple enrollment definitions. Our dataset is constructed from UIS (UNESCO Institute of Statistics), and other sources suggested by World Bank regional or country education specialists. Data sources are typically from administrative records (school registers or school censuses) for data on enrolment by age, and UNPD population estimates for school-age population (UIS). Enrolment by single years of age in all levels of education and the total primary-school-age population are used to compute enrollment rates.\nWe follow this hierarchy of enrollment definitions: Country specialist validated data > Adjusted Net Enrollment Rate (ANER) > Total Net Enrollment Rate (TNER) > Net enrollment rate (NER) > Gross Enrollment Rate (GER; if the gross enrollment rate is higher than 100%, it is adjusted to be 100%).\nOur preferred measure of school participation is ANER, because it accounts for some primary school aged children who might enter primary school early and advance to secondary school before they reach the official upper age limit of primary education. Adjusted net enrollment is a measure of both “stock” and “flow” and accounts for both age- and grade-based distortions, as it is the percent of primary school age children enrolled either in primary or secondary education, as opposed to gross enrollment which is the share of children of any age that are enrolled in primary school, or net enrollment which is the share of primary school age children that are enrolled in primary school. The next-best indicator is used if ANER is unavailable. In some cases, country specialists will provide a data point that reflects enrollment in the country better than UIS statistics which is used. In future Learning Poverty releases, the enrollment hierarchy may be adjusted as availability of indicator definitions change. \nThe enrollment year used is the one that best pairs with the assessment year used to compute Learning Deprivation. The year of the preferred assessment is the base. If the same enrollment year is not available, we use a step function to fill the data in with the value of the closest year. If there is data available for two years equally close to the year to fill, the older value is used. This procedure to extrapolate enrollment for missing values is required for us to pair the proficiency measure with enrollment measures from the same year, or its best proxy when enrollment is not available for the same year of the assessment.\nStatistical concept(s): Minimum Proficiency Level (MPL) in Reading","theme":"education","source_group":"wb"},{"code":"SE.PRM.AGES","name":"Âge d'entrée à l'école primaire (années)","description":"L’âge d’entrée à l’école primaire est l’âge auquel les élèves entreraient dans l’enseignement primaire, en supposant qu’ils aient commencé à l’âge ...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.AGES?locations=CI","methodology":"Methodology: Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator provides insights into the demand for educational services across various educational levels. Additionally, it serves as a crucial data point necessary for the generation of numerous educational indicators.","theme":"education","source_group":"wb"},{"code":"SH.DYN.1014","name":"Probabilité de décès chez les adolescents âgés de 10 à 14 ans (pour 1 000)","description":"Probabilité de mourir entre 10 et 14 ans, exprimée pour 1 000 adolescents de 10 ans, si elle est soumise aux taux de mortalité par âge de l'année s...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.1014?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.DYN.1519","name":"Probabilité de décès chez les adolescents âgés de 15 à 19 ans (pour 1 000)","description":"Probabilité de mourir entre 15 et 19 ans, exprimée pour 1 000 adolescents de 15 ans, si elle est soumise aux taux de mortalité par âge de l'année s...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.1519?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.DYN.0509","name":"Probabilité de décès chez les enfants âgés de 5 à 9 ans (pour 1 000)","description":"Probabilité de mourir entre 5 et 9 ans, exprimée pour 1 000 enfants âgés de 5 ans, si elle est soumise aux taux de mortalité par âge de l'année spé...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.0509?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SH.DYN.2024","name":"Probabilité de décès chez les jeunes de 20 à 24 ans (pour 1 000)","description":"Probabilité de mourir entre 20 et 24 ans, exprimée pour 1 000 jeunes de 20 ans, si elle est soumise aux taux de mortalité par âge de l'année spécif...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.2024?locations=CI","methodology":"Methodology: Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.\nStatistical concept(s): The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A \"complete\" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data.","theme":"sante","source_group":"wb"},{"code":"SE.SEC.PROG.ZS","name":"Progression vers l'enseignement secondaire ( %)","description":"La progression vers l'école secondaire fait référence au nombre de nouveaux inscrits en première année du secondaire au cours d'une année donnée, e...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.PROG.ZS?locations=CI","methodology":"Methodology: Effective transition rate is calculated by dividing the number of new entrants in the first grade of secondary education in a given year (t) by the number of students who enrolled in the final grade of primary education in the previous school year (t-1) minus the number of repeaters from the last grade of primary education in the given year (t), and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.SEC.PROG.FE.ZS","name":"Progression vers l'enseignement secondaire, filles ( %)","description":"La progression vers l'école secondaire fait référence au nombre de nouveaux inscrits en première année du secondaire au cours d'une année donnée, e...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.PROG.FE.ZS?locations=CI","methodology":"Methodology: Effective transition rate is calculated by dividing the number of new entrants in the first grade of secondary education in a given year (t) by the number of students who enrolled in the final grade of primary education in the previous school year (t-1) minus the number of repeaters from the last grade of primary education in the given year (t), and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.SEC.PROG.MA.ZS","name":"Progression vers l'enseignement secondaire, garçons ( %)","description":"La progression vers l'école secondaire fait référence au nombre de nouveaux inscrits en première année du secondaire au cours d'une année donnée, e...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.PROG.MA.ZS?locations=CI","methodology":"Methodology: Effective transition rate is calculated by dividing the number of new entrants in the first grade of secondary education in a given year (t) by the number of students who enrolled in the final grade of primary education in the previous school year (t-1) minus the number of repeaters from the last grade of primary education in the given year (t), and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SI.DST.50MD","name":"Proportion de personnes vivant en dessous de 50 % du revenu médian ( %)","description":"Pourcentage de personnes dans la population qui vivent dans des ménages dont le revenu ou la consommation par habitant est inférieur à la moitié du...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.DST.50MD?locations=CI","methodology":"Methodology: Inequality in the distribution of income is reflected in the share of income or consumption accruing to a portion of the population ranked by income or consumption levels. The portions ranked lowest by personal income receive the smallest shares of total income.\nData on the distribution of income or consumption come from nationally representative household surveys. Where the original data from the household survey were available, they have been used to directly calculate the income or consumption shares by quintile. Otherwise, shares have been estimated from the best available grouped data.\nThe distribution data have been adjusted for household size, providing a more consistent measure of per capita income or consumption. \nThe year reflects the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year data collection started.\nPercentage shares by quintile may not sum to 100 because of rounding.\nStatistical concept(s): The percentage of total income in a population that is held by the tenth or top decile, meaning the top 10% of people when ranked from lowest to highest income.","theme":"social","source_group":"wb"},{"code":"SH.UHC.NOP1.ZS","name":"Proportion de la population poussée en dessous du seuil de pauvreté de 2,15 $ (PPA de 2017) par les dépenses de santé à la charge directe ( %)","description":"Cet indicateur montre la fraction de la population d’un pays confrontée à des dépenses directes d’appauvrissement en matière de santé, définies com...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.UHC.NOP1.ZS?locations=CI","methodology":"Methodology: The proportion of the population facing catastrophic expenditures is measured as the population-weighted average of the number of households with “large household expenditures on health” as a share of total household expenditure or income (household’s budget).\nStatistical concept(s): Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.","theme":"sante","source_group":"wb"},{"code":"SH.UHC.NOP2.ZS","name":"Proportion de la population poussée sous le seuil de pauvreté de 3,65 $ ($ PPA de 2017) par les dépenses de santé à la charge directe ( %)","description":"Cet indicateur montre la fraction de la population d’un pays confrontée à des dépenses directes d’appauvrissement en matière de santé, définies com...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.UHC.NOP2.ZS?locations=CI","methodology":"Methodology: The proportion of the population facing catastrophic expenditures is measured as the population-weighted average of the number of households with “large household expenditures on health” as a share of total household expenditure or income (household’s budget).\nStatistical concept(s): Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.","theme":"sante","source_group":"wb"},{"code":"SH.UHC.NOPR.ZS","name":"Proportion de la population poussée en dessous du seuil de pauvreté médian de consommation de 60 % par les dépenses de santé à la charge des patients ( %)","description":"Cet indicateur montre la fraction de la population d’un pays confrontée à des dépenses de santé qui s’appauvrissent, définies comme des dépenses sa...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.UHC.NOPR.ZS?locations=CI","methodology":"Methodology: The proportion of the population facing catastrophic expenditures is measured as the population-weighted average of the number of households with “large household expenditures on health” as a share of total household expenditure or income (household’s budget).\nStatistical concept(s): Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.","theme":"sante","source_group":"wb"},{"code":"SH.UHC.FBP1.ZS","name":"Proportion de la population poussée encore plus en dessous du seuil de pauvreté de 2,15 $ (PPA de 2017 $) par les dépenses de santé à la charge directe ( %)","description":"Cet indicateur montre la fraction de la population d’un pays vivant dans des ménages dont les dépenses non liées à la santé sont déjà inférieures a...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.UHC.FBP1.ZS?locations=CI","methodology":"Methodology: The proportion of the population facing catastrophic expenditures is measured as the population-weighted average of the number of households with “large household expenditures on health” as a share of total household expenditure or income (household’s budget).\nStatistical concept(s): Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.","theme":"sante","source_group":"wb"},{"code":"SH.UHC.FBP2.ZS","name":"Proportion de la population poussée plus loin sous le seuil de pauvreté de 3,65 $ ($ PPA 2017) par les dépenses de santé à la charge directe ( %)","description":"Cet indicateur montre la fraction de la population d’un pays vivant dans des ménages dont les dépenses non liées à la santé sont déjà inférieures a...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.UHC.FBP2.ZS?locations=CI","methodology":"Methodology: The proportion of the population facing catastrophic expenditures is measured as the population-weighted average of the number of households with “large household expenditures on health” as a share of total household expenditure or income (household’s budget).\nStatistical concept(s): Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.","theme":"sante","source_group":"wb"},{"code":"SH.UHC.FBPR.ZS","name":"Proportion de la population poussée encore plus en dessous du seuil de pauvreté médian de 60 % de consommation par les dépenses de santé à la charge des patients ( %)","description":"Cet indicateur montre la fraction de la population d’un pays vivant dans des ménages dont les dépenses non liées à la santé sont déjà inférieures a...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.UHC.FBPR.ZS?locations=CI","methodology":"Methodology: The proportion of the population facing catastrophic expenditures is measured as the population-weighted average of the number of households with “large household expenditures on health” as a share of total household expenditure or income (household’s budget).\nStatistical concept(s): Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.","theme":"sante","source_group":"wb"},{"code":"SH.UHC.TOT1.ZS","name":"Proportion de la population poussée ou poussée en dessous du seuil de pauvreté de 2,15 $ (PPA de 2017) par les dépenses de santé à la charge des patients ( %)","description":"Cet indicateur montre la fraction de la population d'un pays qui soit (1) vit dans des ménages dont les dépenses non liées à la santé sont déjà inf...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.UHC.TOT1.ZS?locations=CI","methodology":"Methodology: The proportion of the population facing catastrophic expenditures is measured as the population-weighted average of the number of households with “large household expenditures on health” as a share of total household expenditure or income (household’s budget).\nStatistical concept(s): Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.","theme":"sante","source_group":"wb"},{"code":"SH.UHC.TOT2.ZS","name":"Proportion de la population poussée ou poussée en dessous du seuil de pauvreté de 3,65 $ (PPA de 2017) par les dépenses de santé à la charge directe ( %)","description":"Cet indicateur montre la fraction de la population d'un pays qui soit (1) vit dans des ménages dont les dépenses non liées à la santé sont déjà inf...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.UHC.TOT2.ZS?locations=CI","methodology":"Methodology: The proportion of the population facing catastrophic expenditures is measured as the population-weighted average of the number of households with “large household expenditures on health” as a share of total household expenditure or income (household’s budget).\nStatistical concept(s): Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.","theme":"sante","source_group":"wb"},{"code":"SH.UHC.TOTR.ZS","name":"Proportion de la population poussée ou poussée plus loin en dessous du seuil médian de pauvreté de consommation de 60 % par les dépenses de santé à la charge des patients ( %)","description":"Cet indicateur montre la fraction de la population d'un pays qui soit (1) vit dans des ménages dont les dépenses non liées à la santé sont déjà inf...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.UHC.TOTR.ZS?locations=CI","methodology":"Methodology: The proportion of the population facing catastrophic expenditures is measured as the population-weighted average of the number of households with “large household expenditures on health” as a share of total household expenditure or income (household’s budget).\nStatistical concept(s): Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.","theme":"sante","source_group":"wb"},{"code":"SH.UHC.OOPC.10.ZS","name":"Proportion de la population consacrant plus de 10 % de la consommation ou du revenu du ménage aux dépenses de santé à la charge des patients ( %)","description":"Proportion de la population consacrant plus de 10 % de la consommation ou du revenu du ménage aux dépenses de santé directes.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.UHC.OOPC.10.ZS?locations=CI","methodology":"Methodology: The proportion of the population facing catastrophic expenditures is measured as the population-weighted average of the number of households with “large household expenditures on health” as a share of total household expenditure or income (household’s budget).\nStatistical concept(s): Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.","theme":"sante","source_group":"wb"},{"code":"SH.UHC.OOPC.25.ZS","name":"Proportion de la population consacrant plus de 25 % de la consommation ou du revenu du ménage aux dépenses de santé directes ( %)","description":"Proportion de la population consacrant plus de 25 % de la consommation ou du revenu du ménage aux dépenses de santé directes.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.UHC.OOPC.25.ZS?locations=CI","methodology":"Methodology: The proportion of the population facing catastrophic expenditures is measured as the population-weighted average of the number of households with “large household expenditures on health” as a share of total household expenditure or income (household’s budget).\nStatistical concept(s): Out-of-pocket payments are those made by people at the time of getting any type of service (preventive, curative, rehabilitative, palliative or long-term care) provided by any type of provider. They include cost-sharing (the part not covered by a third party like an insurer) and informal payments, but they exclude insurance premiums. Out-of-pocket payments exclude any reimbursement by a third party, such as the government, a health insurance fund or a private insurance company. Out-of-pocket payments are defined as catastrophic at the 10% (25%) threshold when they represent 10% (25%) or more of household total consumption or income. They are defined as impoverishing if they push household consumption or income below the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption, or if they are incurred by households already living under the $2.15 or $3.65 ($ 2017 PPP) per day poverty lines or the relative poverty line of 60% of median consumption.","theme":"sante","source_group":"wb"},{"code":"SG.GEN.PARL.ZS","name":"Proportion de sièges occupés par des femmes dans les parlements nationaux ( %)","description":"Les femmes dans les parlements représentent le pourcentage de sièges parlementaires dans une chambre unique ou basse occupés par des femmes.","source_link":"https://donnees.banquemondiale.org/indicateur/SG.GEN.PARL.ZS?locations=CI","methodology":"Methodology: The proportion of seats held by women in national parliaments is the number of seats held by women members in single or lower chambers of national parliaments, expressed as a percentage of all occupied seats; it is derived by dividing the total number of seats occupied by women by the total number of seats in parliament.\nStatistical concept(s): This indicator assesses the extent to which women are provided with equal opportunities to participate in parliamentary decision-making processes. It applies to the sole chamber of unicameral national parliaments and the lower chamber in the case of bicameral systems. The upper chamber in bicameral parliaments is not included in this measure. Parliamentary seats are typically occupied by individuals who are victorious in general elections, though they can also be acquired through nomination, appointment, indirect election, member rotation, or by-elections. The term 'seats' refers to the total count of parliamentary mandates or the total number of parliament members.","theme":"politique","source_group":"wb"},{"code":"SG.TIM.UWRK.FE","name":"Proportion de temps consacré au travail domestique et aux soins non rémunérés, femmes ( % de la journée de 24 heures)","description":"Le temps moyen que les femmes consacrent à la fourniture de services au ménage pour leur propre consommation.","source_link":"https://donnees.banquemondiale.org/indicateur/SG.TIM.UWRK.FE?locations=CI","methodology":"Methodology: The proportion of time allocated to unpaid domestic and caregiving tasks is determined by dividing the daily average time spent on such activities by the total number of hours in a day (24 hours). The data for this indicator are presented as a daily time proportion. For instance, if women ages 15+ dedicate 10% of their day to unpaid domestic and caregiving work, while men of the same age bracket allocate 1%, this translates to women spending an average of 2.4 hours (or 2 hours and 24 minutes) and men spending 14.4 minutes per day on these tasks.\nTo ascertain the daily average, weekly data are averaged across all seven days.\nStatistical concept(s): This indicator measures the average amount of on unpaid domestic and care work as a proportion in a day.  The objective of this indicator is to quantify the time allocation of both women and men to unpaid tasks, thereby recognizing the value of all forms of work, irrespective of monetary compensation. Furthermore, it serves as a gauge for gender equality by revealing the disparity in time spent by women and men on unpaid activities, such as household chores, caregiving, and childcare.\n\n\n\n\n\n\n\n\n\n\n\nThe daily average is derived from a mean calculated over the data collection reference period, which does not imply that individuals allocate the specified amounts of time to these activities every day.","theme":"social","source_group":"wb"},{"code":"SG.TIM.UWRK.MA","name":"Proportion du temps consacré aux travaux domestiques et aux soins non rémunérés, hommes ( % de la journée de 24 heures)","description":"Temps moyen que les hommes consacrent à la fourniture de services pour leur propre consommation.","source_link":"https://donnees.banquemondiale.org/indicateur/SG.TIM.UWRK.MA?locations=CI","methodology":"Methodology: The proportion of time allocated to unpaid domestic and caregiving tasks is determined by dividing the daily average time spent on such activities by the total number of hours in a day (24 hours). The data for this indicator are presented as a daily time proportion. For instance, if women ages 15+ dedicate 10% of their day to unpaid domestic and caregiving work, while men of the same age bracket allocate 1%, this translates to women spending an average of 2.4 hours (or 2 hours and 24 minutes) and men spending 14.4 minutes per day on these tasks.\nTo ascertain the daily average, weekly data are averaged across all seven days.\nStatistical concept(s): This indicator measures the average amount of on unpaid domestic and care work as a proportion in a day.  The objective of this indicator is to quantify the time allocation of both women and men to unpaid tasks, thereby recognizing the value of all forms of work, irrespective of monetary compensation. Furthermore, it serves as a gauge for gender equality by revealing the disparity in time spent by women and men on unpaid activities, such as household chores, caregiving, and childcare.\n\n\n\n\n\n\n\n\n\n\n\nThe daily average is derived from a mean calculated over the data collection reference period, which does not imply that individuals allocate the specified amounts of time to these activities every day.","theme":"social","source_group":"wb"},{"code":"SG.VAW.1549.ZS","name":"Proportion de femmes ayant subi des violences physiques et/ou sexuelles au cours des 12 derniers mois ( % de femmes âgées de 15 à 49 ans ayant déjà été en couple)","description":"La proportion de femmes soumises à des violences physiques et/ou sexuelles au cours des 12 derniers mois est le pourcentage de femmes âgées de 15 à...","source_link":"https://donnees.banquemondiale.org/indicateur/SG.VAW.1549.ZS?locations=CI","methodology":"Methodology: The indicator is calculated by the number of ever-partnered women (ages 15 and above) subjected to any act of physical violece, sexual violence or both divided by a current or former intimate partner in the previous 12 months divided by the number of ever-partnered women (aged 15 years and above) in the population multiplied by 100.  The main source of data are from the Demographic and Health Surveys (DHS), specialized surveys on violence against women and crime victimasation surveys.\nStatistical concept(s): Physical violence is defined as acts that can physically hurt the victim, including, but not limited to: being slapped or having something thrown at you that could hurt you; being pushed or shoved; being hit with a fist or something else that could hurt; being kicked, dragged or beaten up; being choked or burnt on purpose; and/or being threatened with or actually having a gun, knife or other weapon used on you. Sexual violence is operationalized as: being physically forced to have sexual intercourse when you do not want to; having sexual intercourse out of fear for what your partner might do or through coercion; and/or being forced to do something sexual that you consider humiliating or degrading (Reference: WHO, Violence Against Women Prevalence Estimates, 2018. https://www.who.int/publications/i/item/9789240022256).  \n\n\n\n\n\n\n\n\n\n\n\nCurrent intimate partner includes current or most recent husbands of ever-married women (and men they live with as if married) and the current intimate partner of never-married women. Former husband/intimate partner is a husband (or partner she is living with as if married) other than the current husband (or man she is living with as if married) for currently married women, any intimate partner for never-married women who do not currently have an intimate partner, and a husband/partner other than the most recent husband/partner for divorced, separated, or widowed women.","theme":"social","source_group":"wb"},{"code":"SI.SPR.PGAP","name":"Écart de prospérité (écart moyen par rapport à une norme de prospérité de 28 $ par jour)","description":"Le déficit moyen par rapport à une norme de prospérité de 25 dollars par jour (ajusté pour tenir compte des différences de parité de pouvoir d’acha...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.SPR.PGAP?locations=CI","methodology":"Methodology: The Prosperity Gap is a measure of shared prosperity. As a distribution-sensitive measure, the gap narrows when incomes increase anywhere and falls fastest when incomes of the very poorest increase: growth in income of a person earning $2.50 per day gets ten times more weight than growth in income of a person earning $25/day. Improvements (i.e., reductions) in the Prosperity Gap reflect increases in average income, reductions in inequality within countries, and (for global/regional aggregates) reductions in inequality between countries. It is estimated from nationally representative household surveys. When survey data are missing, in order to create global and regional aggregates, data are interpolated and extrapolated following the same methods that are used for global poverty estimates:  https://datanalytics.worldbank.org/PIP-Methodology/lineupestimates.html\nStatistical concept(s): The Prosperity Gap measures the average factor by which everyone’s incomes in a society needs to vary to reach a prosperity standard of $28 per day (expressed in 2021 PPP dollars). Consider the following example of five individuals earning $2, $7, $14, $28, and $56. Their incomes will have to vary by a factor of 14, 4, 2, 1, and 0.5, respectively, to achieve a prosperity standard of $28. If the world consisted of only these five individuals, the Global Prosperity Gap would be the average of these factors (4.3). As shown in this example, poorer individuals contribute more to the Global Prosperity Gap. $28 is roughly the per capita household income at which countries transition from upper-middle-income to high-income status.","theme":"social","source_group":"wb"},{"code":"DT.TDS.DPPG.XP.ZS","name":"Service de la dette publique et garantie par l'État ( % des exportations de biens, de services et de revenus primaires)","description":"Service de la dette publique et garanti par l’État pour les exportations de biens, de services et de revenus.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.TDS.DPPG.XP.ZS?locations=CI","methodology":"Methodology: Countries that report to the World Bank’s Debtor Reporting System (DRS) submit their public and publicly guaranteed debt (PPG) and private debt with a public guarantee on a loan-by-loan basis. The World Bank Debt Data Team then compiles this information to produce this indicator.","theme":"finance","source_group":"wb"},{"code":"DT.TDS.DPPG.GN.ZS","name":"Service de la dette publique et garantie par l'État ( % du RNB)","description":"Service de la dette publique et garantie par l’État par rapport au revenu national brut.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.TDS.DPPG.GN.ZS?locations=CI","methodology":"Methodology: Countries that report to the World Bank’s Debtor Reporting System (DRS) submit their public and publicly guaranteed debt (PPG) and private debt with a public guarantee on a loan-by-loan basis. The World Bank Debt Data Team then compiles this information to produce this indicator.","theme":"finance","source_group":"wb"},{"code":"IE.PPN.ENGY.CD","name":"Partenariats public-privé : investissement dans l'énergie (en dollars américains courants)","description":"La base de données sur la participation privée aux infrastructures (PPI) enregistre les accords contractuels pour les projets d'infrastructures pub...","source_link":"https://donnees.banquemondiale.org/indicateur/IE.PPN.ENGY.CD?locations=CI","methodology":"Methodology: A team of researchers gather data using public sources (from government and MDBs websites); commercial news databases (such as Factiva, Business News America, ISI Emerging markets, and the Economist Intelligence Unit’s databases) as well as from commercial specialized and industry publications/subscriptions (Thomson Financial’s Project Finance International, Euromoney’s Project Finance, Media Analytics’ Global Water Intelligence, Pisent Masons’ Water Yearbooks, and Platt’s Power in Asia, etc.), specialist portals (such as Privatization, IPAnet, and Privatization Barometer), online resources (such as websites of project companies, privatization or Public-Private Partnership (PPP) agencies, and regulatory agencies) sponsor information (primarily through their websites, annual reports, press releases, and financial reports such as 10K and 20F forms submitted to the NYSE) and multilateral development agencies primarily through information on their websites, annual reports, and other studies.\n\nData is uploaded to an administrative website through a template ensure that the data is standardized. Data is validated by a group of experts in Singapore first (PPI team), then by the World Bank focal points colleagues.\n\nData is later uploaded to the public website (www.ppi.worldbank.org) and made available free of charge. The website has a mechanism for challenges to the data and welcomes all PPP units to give feedback about any project.\n\nStatistical concept(s): PPPs is defined as “any contractual arrangement between a public entity or authority and a private entity, for providing a public asset or service, in which the private party bears significant risk and management responsibility.”\nThe term infrastructure refers to:\n• Energy: electricity generation, transmission, and distribution, and natural gas transmission and\ndistribution pipelines\n• Information and communications technology (ICT): ICT backbone infrastructure\n• Transport: Airports, railways, ports, and roads.\n• Water: potable water treatment and distribution, and sewerage collection and treatment.","theme":"territory","source_group":"wb"},{"code":"IE.PPN.ICTI.CD","name":"Investissements dans les TIC en partenariat public-privé (en dollars courants des États-Unis)","description":"La base de données sur la participation privée aux infrastructures (PPI) enregistre les accords contractuels pour les projets d'infrastructures pub...","source_link":"https://donnees.banquemondiale.org/indicateur/IE.PPN.ICTI.CD?locations=CI","methodology":"Methodology: A team of researchers gather data using public sources (from government and MDBs websites); commercial news databases (such as Factiva, Business News America, ISI Emerging markets, and the Economist Intelligence Unit’s databases) as well as from commercial specialized and industry publications/subscriptions (Thomson Financial’s Project Finance International, Euromoney’s Project Finance, Media Analytics’ Global Water Intelligence, Pisent Masons’ Water Yearbooks, and Platt’s Power in Asia, etc.), specialist portals (such as Privatization, IPAnet, and Privatization Barometer), online resources (such as websites of project companies, privatization or Public-Private Partnership (PPP) agencies, and regulatory agencies) sponsor information (primarily through their websites, annual reports, press releases, and financial reports such as 10K and 20F forms submitted to the NYSE) and multilateral development agencies primarily through information on their websites, annual reports, and other studies.\n\nData is uploaded to an administrative website through a template ensure that the data is standardized. Data is validated by a group of experts in Singapore first (PPI team), then by the World Bank focal points colleagues.\n\nData is later uploaded to the public website (www.ppi.worldbank.org) and made available free of charge. The website has a mechanism for challenges to the data and welcomes all PPP units to give feedback about any project.\nStatistical concept(s): PPPs is defined as “any contractual arrangement between a public entity or authority and a private entity, for providing a public asset or service, in which the private party bears significant risk and management responsibility.”\nThe term infrastructure refers to:\n• Energy: electricity generation, transmission, and distribution, and natural gas transmission and\ndistribution pipelines\n• Information and communications technology (ICT): ICT backbone infrastructure\n• Transport: Airports, railways, ports, and roads.\n• Water: potable water treatment and distribution, and sewerage collection and treatment.","theme":"territory","source_group":"wb"},{"code":"IE.PPN.TRAN.CD","name":"Investissements dans les transports en dollars courants (dollars courants)","description":"La base de données sur la participation privée aux infrastructures (PPI) enregistre les accords contractuels pour les projets d'infrastructures pub...","source_link":"https://donnees.banquemondiale.org/indicateur/IE.PPN.TRAN.CD?locations=CI","methodology":"Methodology: A team of researchers gather data using public sources (from government and MDBs websites); commercial news databases (such as Factiva, Business News America, ISI Emerging markets, and the Economist Intelligence Unit’s databases) as well as from commercial specialized and industry publications/subscriptions (Thomson Financial’s Project Finance International, Euromoney’s Project Finance, Media Analytics’ Global Water Intelligence, Pisent Masons’ Water Yearbooks, and Platt’s Power in Asia, etc.), specialist portals (such as Privatization, IPAnet, and Privatization Barometer), online resources (such as websites of project companies, privatization or Public-Private Partnership (PPP) agencies, and regulatory agencies) sponsor information (primarily through their websites, annual reports, press releases, and financial reports such as 10K and 20F forms submitted to the NYSE) and multilateral development agencies primarily through information on their websites, annual reports, and other studies.\n\nData is uploaded to an administrative website through a template ensure that the data is standardized. Data is validated by a group of experts in Singapore first (PPI team), then by the World Bank focal points colleagues.\n\nData is later uploaded to the public website (www.ppi.worldbank.org) and made available free of charge. The website has a mechanism for challenges to the data and welcomes all PPP units to give feedback about any project.\n\nStatistical concept(s): PPPs is defined as “any contractual arrangement between a public entity or authority and a private entity, for providing a public asset or service, in which the private party bears significant risk and management responsibility.”\nThe term infrastructure refers to:\n• Energy: electricity generation, transmission, and distribution, and natural gas transmission and\ndistribution pipelines\n• Information and communications technology (ICT): ICT backbone infrastructure\n• Transport: Airports, railways, ports, and roads.\n• Water: potable water treatment and distribution, and sewerage collection and treatment.","theme":"territory","source_group":"wb"},{"code":"IE.PPN.WATR.CD","name":"Partenariats public-privé : investissement dans l'eau et l'assainissement (en dollars courants)","description":"La base de données sur la participation privée aux infrastructures (PPI) enregistre les accords contractuels pour les projets d'infrastructures pub...","source_link":"https://donnees.banquemondiale.org/indicateur/IE.PPN.WATR.CD?locations=CI","methodology":"Methodology: A team of researchers gather data using public sources (from government and MDBs websites); commercial news databases (such as Factiva, Business News America, ISI Emerging markets, and the Economist Intelligence Unit’s databases) as well as from commercial specialized and industry publications/subscriptions (Thomson Financial’s Project Finance International, Euromoney’s Project Finance, Media Analytics’ Global Water Intelligence, Pisent Masons’ Water Yearbooks, and Platt’s Power in Asia, etc.), specialist portals (such as Privatization, IPAnet, and Privatization Barometer), online resources (such as websites of project companies, privatization or Public-Private Partnership (PPP) agencies, and regulatory agencies) sponsor information (primarily through their websites, annual reports, press releases, and financial reports such as 10K and 20F forms submitted to the NYSE) and multilateral development agencies primarily through information on their websites, annual reports, and other studies.\n\nData is uploaded to an administrative website through a template ensure that the data is standardized. Data is validated by a group of experts in Singapore first (PPI team), then by the World Bank focal points colleagues.\n\nData is later uploaded to the public website (www.ppi.worldbank.org) and made available free of charge. The website has a mechanism for challenges to the data and welcomes all PPP units to give feedback about any project.\n\nStatistical concept(s): PPPs is defined as “any contractual arrangement between a public entity or authority and a private entity, for providing a public asset or service, in which the private party bears significant risk and management responsibility.”\nThe term infrastructure refers to:\n• Energy: electricity generation, transmission, and distribution, and natural gas transmission and\ndistribution pipelines\n• Information and communications technology (ICT): ICT backbone infrastructure\n• Transport: Airports, railways, ports, and roads.\n• Water: potable water treatment and distribution, and sewerage collection and treatment.","theme":"territory","source_group":"wb"},{"code":"SE.LPV.PRIM.LD","name":"Élèves ayant des compétences minimales en lecture à la fin du primaire ( %). Seuil GAML bas","description":"La proportion d'élèves à la fin de l'école primaire qui sont en dessous du niveau minimum de compétence (MPL) pour la lecture ou l'apprentissage so...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.LPV.PRIM.LD?locations=CI","methodology":"Methodology: Learning assessments used to calculate Learning Poverty have a minimum proficiency level (MPL) benchmarked by Global Alliance to Monitor Learning (GAML) under the leadership of the UNESCO Institute of Statistics (UIS), which occurred within the reporting window. To operationalize this concept, the current SDG monitoring process is followed by defining “proficiency” as reaching at least the Low International Benchmark on the international PIRLS literacy assessment. \nPIRLS is the major global primary-age assessment focused on reading, and if all countries participated in it, the task of constructing global estimates of minimum proficiency would be trivial, as it would require aggregating results from a single cross-national assessment. However, most countries participating in PIRLS are high-income, and only a small minority of low- and middle-income countries participate in the assessment. One of the main contributions of the GAML process is that it has overcome this data gap by benchmarking several major cross-national assessments—and increasingly national learning assessments as well—against the standard. \nThe MPL for each learning assessment is used to calculate the reading proficiency rate for that country, which is the share of students scoring at or above the minimum proficiency level, and conversely to calculate the learning deprivation.\nThe Proficiency and Grade Levels used for each assessment is as follows: PIRLS (grade 4) - Level 2 (Low international benchmark, 400 points); TIMSS (grade 4) - Level 2 (Low international benchmark, 400 points); LLECE (SERCE, grade 6) - Level 3 (513.66 points); PASEC (grades 5 and 6) - Level 4 (595.1 points); SEA-PLM (grade 5) - Level 6 and above; National Learning Assessment (grade 4, 5 and 6) - Varies by country. \nWhen a given country had administered multiple types of learning assessments, a hierarchy is applied in the order listed below to ensure best comparability across countries: International or Regional Learning Assessment for Reading (PIRLS, LLECE, PASEC, SEA-PLM) > TIMSS Science > Statistical or Pairwise Linking Exercises > AMPL-bs, Policy Linked National Learning Assessments or Policy Linked Service Delivery Indicators (SDIs) > Non-Policy Linked NLAs (Interim Reporting).\nNote that as the GAML and joint coalitions continue their efforts to improve learning data coverage, the hierarchy may be revised.\nStatistical concept(s): Minimum Proficiency Level (MPL) in Reading","theme":"education","source_group":"wb"},{"code":"SE.SEC.ENRL.LO.TC.ZS","name":"Ratio élèves-enseignant dans le premier cycle de l'enseignement secondaire","description":"Le ratio élèves-enseignant du premier cycle du secondaire est le nombre moyen d’élèves par enseignant dans le premier cycle du secondaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.ENRL.LO.TC.ZS?locations=CI","methodology":"Methodology: Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.PRE.ENRL.TC.ZS","name":"Ratio élèves-enseignant pour le préprimaire","description":"Le ratio élèves-enseignant de l’école maternelle est le nombre moyen d’élèves par enseignant dans l’école préscolaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRE.ENRL.TC.ZS?locations=CI","methodology":"Methodology: Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.PRM.ENRL.TC.ZS","name":"Ratio élèves-enseignant dans l'enseignement primaire","description":"Le ratio élèves-enseignant du primaire est le nombre moyen d’élèves par enseignant à l’école primaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.ENRL.TC.ZS?locations=CI","methodology":"Methodology: Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.SEC.ENRL.TC.ZS","name":"Ratio élèves-enseignant dans le secondaire","description":"Le ratio élèves-enseignant du secondaire est le nombre moyen d’élèves par enseignant dans l’école secondaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.ENRL.TC.ZS?locations=CI","methodology":"Methodology: Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.TER.ENRL.TC.ZS","name":"Ratio élèves-enseignant dans l'enseignement supérieur","description":"Le ratio élèves-enseignant dans l’enseignement supérieur est le nombre moyen d’élèves par enseignant dans l’enseignement supérieur.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.ENRL.TC.ZS?locations=CI","methodology":"Methodology: Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.SEC.ENRL.UP.TC.ZS","name":"Ratio élèves-enseignant dans le deuxième cycle de l'enseignement secondaire","description":"Le ratio élèves-enseignant du deuxième cycle du secondaire est le nombre moyen d’élèves par enseignant dans le deuxième cycle du secondaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.ENRL.UP.TC.ZS?locations=CI","methodology":"Methodology: Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"IS.RRS.TOTL.KM","name":"Lignes ferroviaires (nombre total de kilomètres parcourus)","description":"La longueur totale de la ligne ferroviaire du pays était destinée au transport de passagers, au transport de marchandises ou aux deux.","source_link":"https://donnees.banquemondiale.org/indicateur/IS.RRS.TOTL.KM?locations=CI","methodology":"Methodology: Rail lines are the length of railway route available for train service, irrespective of the number of parallel tracks. It includes railway routes that are open for public passenger and freight services and excludes dedicated private resource railways.\n\nGauge:\tN (standard gauge: 1,435 m); L (broad gauge: exact rail gauge inserted); E (narrow gauge: exact rail gauge inserted). The length of railway lines worked is obtained by taking these sections including main-line track listed in the Capital Expenditure Account.\n\nSections not worked are deducted only in cases where they are permanently out of use, that is, if they are no longer maintained in working order. Lines temporarily out of use continue to form part of the length of lines worked.\n\nThe length of a section is measured in the middle of the section, from center to the center of the passenger buildings, or of the corresponding service buildings, of stations which are shown as independent points of departure or arrival for the conveyance of passengers or freight. If the boundary of the rail network falls in open track, the length of the section is measured up to that point.\n\nThe section situated between a station approach and the join to the main line of two lines or more which is used by all trains in either direction over these lines, is only counted once. However, if for one or more of these lines, tracks are normally allocated, the length of these lines is counted separately.\n\nIf between two stations there are one or more parallel tracks (siding-lines) to the main line, only the length of the latter is counted.\n\nIn the case of regular lines worked exclusively during part of the year (seasonal lines), their length is included in the end-of-year statement (Var 1112: Total length of lines worked at the end of the year in the Railisa database).\nStatistical concept(s): Railway line: one or more adjacent running tracks forming a route between two points. Where a section of network comprises two or more lines running alongside one another, there are as many lines as routes to which tracks are allotted exclusively.","theme":"territory","source_group":"wb"},{"code":"IS.RRS.GOOD.MT.K6","name":"Chemins de fer, marchandises transportées (millions de tonnes-km)","description":"Les marchandises transportées par chemin de fer correspondent au volume de marchandises transportées par chemin de fer, mesuré en tonnes métriques ...","source_link":"https://donnees.banquemondiale.org/indicateur/IS.RRS.GOOD.MT.K6?locations=CI","methodology":"Methodology: Freight traffic on any mode is typically measured in tons and ton-kilometers. A ton-kilometer equals cargo weight transported times distance transported. For railways, an important measure of work performed is gross ton-kilometers, this measure includes rail wagons' empty weight for both empty and loaded movements. This measure of gross ton-kilometers is also called ‘trailing tons' or the total tons being hauled. Sometimes gross ton-kilometer measures include the weight of locomotives used to haul freight trains.\n\nThe indicator measures the tonne.kilometers of freight on the national territory of the railway.\n\nThe weight taken into account is the actual weight or chargeable weight of the goods carried. Weight means the quantity of goods in thousands of tonnes. The weight to be taken into consideration includes, in addition to the weight of the goods transported, the weight of packaging and the tare weight of containers, swap bodies, pallets as well as road vehicles transported by rail in the course of combined transport operations. If the goods are transported using the services of more than one railway undertaking (e.g. within the group etc.), when possible the weight of goods should not be counted more than once.\n\nThe number of tonne-kilometres in millions represents the weight of freight traffic (in millions of tonnes) over the charging distance (in kilometres). \n\nStatistical concept(s): Tonne-kilometre (tkm) is a unit of measurement of goods transport which represents the transport of one tonne of goods over a distance of one kilometre.\n\nThe distance to be covered is the distance actually travelled on the considered network. To avoid double counting each country should count only the tkm performed on its territory. If it is not available, then the distance charged or estimated should be taken into account.","theme":"territory","source_group":"wb"},{"code":"IS.RRS.PASG.KM","name":"Chemins de fer, passagers transportés (millions de passagers-km)","description":"Les passagers transportés par chemin de fer correspondent au nombre de passagers transportés par chemin de fer multiplié par les kilomètres parcourus.","source_link":"https://donnees.banquemondiale.org/indicateur/IS.RRS.PASG.KM?locations=CI","methodology":"Methodology: Passenger-kilometers are usually measured on the basis of the rail travel distance between origin and destination multiplied by the number of passengers traveling between each origin and destination. This variable relates to passengers, irrespective of the fare paid and also including free travelling passengers, but excluding members of the train crew. \n\nThe number of passengers should be calculated as number of passenger journeys. A journey is the act of moving from one place (origin) to another (destination) using a given transport mode (e.g. railway). A journey may consist of one or several stages depending on whether one has to change transport means (e.g. using more than one train) in order to get from the origin to the destination. In other words, a journey consists either of a single stage or a sequence of stages using the same transport mode (e.g. railway), following each other in such a way that the destination of one stage coincides with the origin of the next.\n\nJourneys should be considered finished when an overnight stay occurs. For practical purposes, journeys can be considered finished when a change in transport mode or transport company occurs.  \n\nPassenger-kilometers is the total distance travelled by all the passengers. For instance, one person travelling for 20km contributes for 20 passenger-kilometres; four people, travelling for 20km each, contribute for 80 passenger- kilometers\n\nStatistical concept(s): A passenger kilometer is performed when a passenger is carried for one kilometer. Rail passenger-kilometer (pkm) is a unit of measurement representing the transport of one rail passenger by rail over a distance of one kilometer.\n\nThe distance to be taken into consideration should be the distance actually travelled by the passenger on the network. To avoid double counting each country should count only the pkm performed on its territory. If this is not available, then the distance charged or estimated should be used.","theme":"territory","source_group":"wb"},{"code":"SL.TLF.CACT.FM.ZS","name":"Taux d'activité des femmes par rapport aux hommes ( %) (estimation modélisée de l'OIT)","description":"Le taux de participation à la population active est la proportion de la population âgée de 15 ans et plus qui est économiquement active : toutes le...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.CACT.FM.ZS?locations=CI","methodology":"Methodology: Ratio of female to male labor force participation rate is calculated by dividing female labor force participation rate by male labor force participation rate and multiplying by 100. The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"SL.TLF.CACT.FM.NE.ZS","name":"Taux d'activité des femmes par rapport aux hommes ( %) (estimation nationale)","description":"Le rapport entre le taux d’activité des femmes et celui des hommes est la proportion de la participation des femmes à la population active par rapp...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.TLF.CACT.FM.NE.ZS?locations=CI","methodology":"Methodology: Ratio of female to male labor force participation rate is calculated by dividing female labor force participation rate by male labor force participation rate and multiplying by 100. The labor force participation rate is calculated by expressing the number of persons in the labor force as a percentage of the population of a given age group. The labor force is the sum of the number of persons employed and the number of unemployed. \n\nLabor force surveys are typically the preferred source of information for determining the labor force participation rate. Such surveys can be designed to cover virtually the entire noninstitutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing (unpaid) family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force in a coherent framework. \n\nPopulation censuses are another major source of data on the labor force and its components. The labor force participation rates obtained from population censuses, however, tend to be lower, as the vastness of the census operation inhibits the recruitment of trained interviewers and does not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The labor force is the supply of labor available for producing goods and services in an economy. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.","theme":"emploi","source_group":"wb"},{"code":"PX.REX.REER","name":"Indice du taux de change effectif réel (2010 = 100)","description":"Le taux de change effectif réel est le taux de change effectif nominal (une mesure de la valeur d'une monnaie par rapport à une moyenne pondérée de...","source_link":"https://donnees.banquemondiale.org/indicateur/PX.REX.REER?locations=CI","methodology":"Methodology: The real effective exchange rate is a nominal effective exchange rate index adjusted for relative movements in national price or cost indicators of the home country, selected countries, and the euro area. A nominal effective exchange rate index is the ratio (expressed on the base 2010 = 100) of an index of a currency's period-average exchange rate to a weighted geometric average of exchange rates for currencies of selected countries and the euro area. For most high-income countries weights are derived from industrial country trade in manufactured goods. Data are compiled from the nominal effective exchange rate index and a cost indicator of relative normalized unit labor costs in manufacturing. For selected other countries the nominal effective exchange rate index is based on manufactured goods and primary products trade with partner or competitor countries. For these countries the real effective exchange rate index is the nominal index adjusted for relative changes in consumer prices; an increase represents an appreciation of the local currency.\nStatistical concept(s): The real effective exchange rate is a nominal effective exchange rate index adjusted for relative movements in national price or cost indicators of the home country, selected countries, and the euro area. A nominal effective exchange rate index is the ratio (expressed on the base 2010 = 100) of an index of a currency's period-average exchange rate to a weighted geometric average of exchange rates for currencies of selected countries and the euro area. For most high-income countries weights are derived from industrial country trade in manufactured goods. Data are compiled from the nominal effective exchange rate index and a cost indicator of relative normalized unit labor costs in manufacturing. For selected other countries the nominal effective exchange rate index is based on manufactured goods and primary products trade with partner or competitor countries. For these countries the real effective exchange rate index is the nominal index adjusted for relative changes in consumer prices; an increase represents an appreciation of the local currency.","theme":"macro","source_group":"wb"},{"code":"FR.INR.RINR","name":"Taux d'intérêt réel ( %)","description":"Un taux d'intérêt est le montant facturé, exprimé en pourcentage du principal sur une période donnée, par les propriétaires de certains types d'act...","source_link":"https://donnees.banquemondiale.org/indicateur/FR.INR.RINR?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"SM.POP.RHCR.EA","name":"Réfugiés relevant du mandat du HCR par pays ou territoire d'asile","description":"Les réfugiés relevant du mandat du Haut-Commissariat des Nations Unies pour les réfugiés (HCR) comprennent les personnes reconnues en vertu de la C...","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.RHCR.EA?locations=CI","methodology":"Methodology: Data collection on refugees (and people in a refugee-like situation) under the mandate of the Office of the United Nations High Commissioner for Refugees (UNHCR) is based on a coordinated effort between national governments and UNHCR.\n\n\n\nThe primary sources of data include administrative records and registration systems maintained by immigration or asylum agencies, including UNHCR itself, which provide detailed demographic information, such as age, sex, and nationality. These records are generally reported as stock data, reflecting the number of refugees at a specific point in time, typically at the end of the calendar year. \n\n\n\nThe collection process follows the guidelines outlined in the International Recommendations on Refugee Statistics (IRRS), developed by the Expert Group on Refugee, IDP and Statelessness Statistics (EGRISS). The IRRS helps to standardize data collection methods across different countries. The IRRS emphasizes the importance of disaggregating data by key demographic variables and geographical locations, facilitating a more granular analysis of refugee populations.","theme":"demo","source_group":"wb"},{"code":"SM.POP.RHCR.EO","name":"Réfugiés relevant du mandat du HCR par pays ou territoire d'origine","description":"Les réfugiés relevant du mandat du Haut-Commissariat des Nations Unies pour les réfugiés (HCR) comprennent les personnes reconnues en vertu de la C...","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.RHCR.EO?locations=CI","methodology":"Methodology: Data collection on refugees (and people in a refugee-like situation) under the mandate of the Office of the United Nations High Commissioner for Refugees (UNHCR) is based on a coordinated effort between national governments and UNHCR.\n\n\n\nThe primary sources of data include administrative records and registration systems maintained by immigration or asylum agencies, including UNHCR itself, which provide detailed demographic information, such as age, sex, and nationality. These records are generally reported as stock data, reflecting the number of refugees at a specific point in time, typically at the end of the calendar year. \n\n\n\nThe collection process follows the guidelines outlined in the International Recommendations on Refugee Statistics (IRRS), developed by the Expert Group on Refugee, IDP and Statelessness Statistics (EGRISS). The IRRS helps to standardize data collection methods across different countries. The IRRS emphasizes the importance of disaggregating data by key demographic variables and geographical locations, facilitating a more granular analysis of refugee populations.","theme":"demo","source_group":"wb"},{"code":"SM.POP.RRWA.EA","name":"Réfugiés relevant du mandat de l'UNRWA, par pays ou territoire d'asile","description":"Les réfugiés relevant du mandat de l'Office de secours et de travaux des Nations Unies pour les réfugiés de Palestine dans le Proche-Orient (UNRWA)...","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.RRWA.EA?locations=CI","methodology":"Methodology: Data collection on refugees under the mandate of the United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA) is primarily based on administrative records maintained by the UNRWA in line with UNRWA’s internal guidelines and operational frameworks.\n\n\n\nUNRWA's registration system is a key source, capturing detailed information on individuals registered as Palestine refugees, including their demographic characteristics as well as the country or territory of asylum, to facilitate a nuanced understanding of the refugee population's distribution and characteristics.\n\n\n\nIn addition to administrative records, UNRWA also collaborates with host countries and other international organizations to enrich its data, particularly in contexts where operational challenges might limit direct data collection.","theme":"demo","source_group":"wb"},{"code":"SM.POP.RRWA.EO","name":"Réfugiés relevant du mandat de l'UNRWA, par pays ou territoire d'origine","description":"Les réfugiés relevant du mandat de l'Office de secours et de travaux des Nations Unies pour les réfugiés de Palestine dans le Proche-Orient (UNRWA)...","source_link":"https://donnees.banquemondiale.org/indicateur/SM.POP.RRWA.EO?locations=CI","methodology":"Methodology: Data collection on refugees under the mandate of the United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA) is primarily based on administrative records maintained by the UNRWA in line with UNRWA’s internal guidelines and operational frameworks.\n\n\n\nUNRWA's registration system is a key source, capturing detailed information on individuals registered as Palestine refugees, including their demographic characteristics as well as the country or territory of asylum, to facilitate a nuanced understanding of the refugee population's distribution and characteristics.\n\n\n\nIn addition to administrative records, UNRWA also collaborates with host countries and other international organizations to enrich its data, particularly in contexts where operational challenges might limit direct data collection.","theme":"demo","source_group":"wb"},{"code":"RQ.EST","name":"Qualité réglementaire : estimation","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/RQ.EST?locations=CI","methodology":"","theme":"politique","source_group":"wb"},{"code":"RQ.NO.SRC","name":"Qualité réglementaire : nombre de sources","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/RQ.NO.SRC?locations=CI","methodology":"Methodology: The WGI compile and summarize information from over 30 existing data sources that report the views and experiences of citizens, entrepreneurs, and experts in the public, private and NGO sectors from around the world, on the quality of various aspects of governance.\n\n•\tThe data sources must provide subjective perceptions of relevant dimensions of governance, as the WGI are based exclusively on this type of data.\n•\tThe sources must provide original primary data produced using a well-defined methodology.\n•\tThe data sources must cover multiple countries, so that cross-country comparisons are possible.\n•\tThe data sources must be updated regularly, ideally every year, although some WGI data sources are updated once every two or three years.\n\nThe WGI draw on four different types of source data:\n\n•\tSurveys of households and firms, including the Afrobarometer surveys, Gallup World Poll, and Global Competitiveness Report survey,\n•\tCommercial business information providers, including the Economist Intelligence Unit, S&P Global, and Political Risk Services,\n•\tNon-governmental organizations, including Global Integrity, Freedom House, Reporters Without Borders, and\n•\tPublic sector organizations, including the Country Policy and Institutional Assessments (CPIA) assessments of World Bank and regional development banks.\n\nFor the detailed list of sources, please refer to: https://www.worldbank.org/en/publication/worldwide-governance-indicators/documentation#2  \nStatistical concept(s): Number of sources indicates the number of underlying data sources on which the aggregate estimate is based.\n\nVariables from the data sources are assigned to each of these six governance dimensions.  For example, an assessment of the quality of the bureaucracy would be assigned to Government Effectiveness, a question about confidence in the police or the courts would be assigned to Rule of Law, and a question about the perceived likelihood of having to pay a bribe would be assigned to Control of Corruption.  In some cases, a single data source will have multiple questions that can be assigned to the same dimension.  In this case, the WGI use the average across all relevant questions from that data source. In addition each question from each data source is assigned to only one of the six governance dimensions, selecting the dimension that best matches the content of the question.","theme":"politique","source_group":"wb"},{"code":"RQ.PER.RNK","name":"Qualité réglementaire : Rang centile","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/RQ.PER.RNK?locations=CI","methodology":"","theme":"politique","source_group":"wb"},{"code":"RQ.PER.RNK.LOWER","name":"Qualité réglementaire : rang centile, limite inférieure de l'intervalle de confiance à 90 %","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/RQ.PER.RNK.LOWER?locations=CI","methodology":"Methodology: A key feature of the WGI is that all country scores are accompanied by standard errors. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether.\n\nThe standard deviations are essential to the interpretation of the WGI.  It often is more appropriate to think of the WGI methodology as identifying a statistically likely range of values for the unobserved “true” level of governance in a country.  For example, the assumption of normality tells us that there is a 90 percent probability that the true unobserved level of governance conditional on the available data for a country is in a range given by plus or minus 1.64 standard deviations around the estimate of governance. These confidence intervals are informally referred to as the “margin of error” around the estimates of governance.\n\nThese 90 percent confidence interval are also reported in percentile rank terms (the percentile rank among all country estimates of governance, of the upper and lower bounds of the 90 percent confidence interval for each country).\nStatistical concept(s): Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank.  Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.  \n\nPercentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.","theme":"politique","source_group":"wb"},{"code":"RQ.PER.RNK.UPPER","name":"Qualité réglementaire : rang centile, limite supérieure de l'intervalle de confiance à 90 %","description":"La bonne gouvernance est essentielle au développement.","source_link":"https://donnees.banquemondiale.org/indicateur/RQ.PER.RNK.UPPER?locations=CI","methodology":"Methodology: A key feature of the WGI is that all country scores are accompanied by standard errors. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether.\n\nThe standard deviations are essential to the interpretation of the WGI.  It often is more appropriate to think of the WGI methodology as identifying a statistically likely range of values for the unobserved “true” level of governance in a country.  For example, the assumption of normality tells us that there is a 90 percent probability that the true unobserved level of governance conditional on the available data for a country is in a range given by plus or minus 1.64 standard deviations around the estimate of governance. These confidence intervals are informally referred to as the “margin of error” around the estimates of governance.\n\nThese 90 percent confidence interval are also reported in percentile rank terms (the percentile rank among all country estimates of governance, of the upper and lower bounds of the 90 percent confidence interval for each country).\nStatistical concept(s): Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. \n\nPercentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.","theme":"politique","source_group":"wb"},{"code":"RQ.STD.ERR","name":"Qualité réglementaire : Erreur-type","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/RQ.STD.ERR?locations=CI","methodology":"Methodology: The WGI are composite governance indicators based on over 30 underlying data sources. These data sources are rescaled and combined to create the six aggregate indicators using a statistical methodology known as an Unobserved Components Model (UCM). The six aggregate indicators are reported in two ways : (1) in their standard normal units, ranging from approximately -2.5 to 2.5, and (2) in percentile rank terms from 0 to 100, with higher values corresponding to better outcomes.\n\nA key feature of the WGI is that all country scores are accompanied by standard errors. These margins of error need to be taken into account when making comparisons across countries and over time. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether. \n\nPlease see more information at: https://www.worldbank.org/en/publication/worldwide-governance-indicators/documentation#1\nStatistical concept(s): Standard error indicates the precision of the estimate of governance. Larger values of the standard error indicate less precise estimates. A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.","theme":"politique","source_group":"wb"},{"code":"EG.ELC.RNEW.ZS","name":"Production d'électricité renouvelable ( % de la production totale d'électricité)","description":"L'électricité renouvelable est la part de l'électricité produite par les centrales électriques renouvelables dans l'électricité totale produite par...","source_link":"https://donnees.banquemondiale.org/indicateur/EG.ELC.RNEW.ZS?locations=CI","methodology":"Methodology: The share of renewable electricity output is calculated using the formula:\n\nRenewable Electricity Share(%)=(Electricity from Renewable Sources (MWh) / Total Electricity Output (MWh))×100\n\nWhere:\n\nElectricity from Renewable Sources = Total electricity generated from hydropower, wind, solar, biomass, geothermal, and ocean energy.\n\nTotal Electricity Output = Sum of electricity generated from all sources, including fossil fuels, nuclear, and renewables.","theme":"secondary","source_group":"wb"},{"code":"EG.FEC.RNEW.ZS","name":"Consommation d'énergie renouvelable ( % de la consommation totale d'énergie finale)","description":"La consommation d'énergie renouvelable est la part des énergies renouvelables dans la consommation totale d'énergie finale.","source_link":"https://donnees.banquemondiale.org/indicateur/EG.FEC.RNEW.ZS?locations=CI","methodology":"Methodology: The numerator includes the direct consumption of renewable energy sources plus the final consumption of gross electricity and heat estimated to have come from renewable sources, while the denominator is the total final energy consumption of all energy products.","theme":"secondary","source_group":"wb"},{"code":"ER.H2O.INTR.PC","name":"Ressources internes renouvelables en eau douce par habitant (mètres cubes)","description":"Les flux de ressources internes renouvelables en eau douce font référence aux ressources renouvelables internes (débits fluviaux internes et eaux s...","source_link":"https://donnees.banquemondiale.org/indicateur/ER.H2O.INTR.PC?locations=CI","methodology":"Methodology: Renewable water resources (internal and external) include average annual flow of rivers and recharge of aquifers generated from endogenous precipitation, and those water resources that are not generated in the country, such as inflows from upstream countries (groundwater and surface water), and part of the water of border lakes and/or rivers. Non-renewable water includes groundwater bodies (deep aquifers) that have a negligible rate of recharge on the human time-scale. While renewable water resources are expressed in flows, non-renewable water resources have to be expressed in quantity (stock). Runoff from glaciers where the mass balance is negative is considered non-renewable. Renewable internal freshwater resources per capita are calculated using the World Bank's population estimates. The unit of calculation is m3/year per inhabitant. Internal renewable freshwater resources per capita are calculated using the World Bank's population estimates.\n\n\n\n\n\n\n\n\n\n\n\nTotal actual renewable water resources correspond to the maximum theoretical yearly amount of water actually available for a country at a given moment. The unit of calculation is km3/year or 109 m3/year. Calculation Criteria is [Water resources: total renewable (actual)] = [Surface water: total renewable (actual)] + [Groundwater: total renewable (actual)] - [Overlap between surface water and groundwater].*\n\n\n\n\n\n\n\n\n\n\n\nFresh water is naturally occurring water on the Earth's surface. It is a renewable but limited natural resource. Fresh water can only be renewed through the process of the water cycle, where water from seas, lakes, forests, land, rivers, and dams evaporates, forms clouds, and returns as precipitation. However, if more fresh water is consumed through human activities than is restored by nature, the result is that the quantity of fresh water available in lakes, rivers, dams and underground waters can be reduced which can cause serious damage to the surrounding environment.\n\n\n\n\n\n\n\n\n\n\n\n* http://www.fao.org/nr/water/aquastat/data/glossary/search.html?termId=4188&submitBtn=s&cls=yes\nStatistical concept(s):","theme":"territory","source_group":"wb"},{"code":"ER.H2O.INTR.K3","name":"Ressources internes renouvelables en eau douce, total (milliards de mètres cubes)","description":"Les flux de ressources internes renouvelables en eau douce font référence aux ressources renouvelables internes (débits fluviaux internes et eaux s...","source_link":"https://donnees.banquemondiale.org/indicateur/ER.H2O.INTR.K3?locations=CI","methodology":"Methodology: The data on freshwater resources are based on estimates of runoff into rivers and recharge of groundwater. Renewable water resources (internal and external) include average annual flow of rivers and recharge of aquifers generated from endogenous precipitation, and those water resources that are not generated in the country, such as inflows from upstream countries (groundwater and surface water), and part of the water of border lakes and/or rivers. Non-renewable water includes groundwater bodies (deep aquifers) that have a negligible rate of recharge on the human time-scale. While renewable water resources are expressed in flows, non-renewable water resources have to be expressed in quantity (stock). Runoff from glaciers where the mass balance is negative is considered non-renewable.\nTotal actual renewable water resources correspond to the maximum theoretical yearly amount of water actually available for a country at a given moment. The unit of calculation is km3/year or 109 m3/year. Calculation Criteria is [Water resources: total renewable (actual)] = [Surface water: total renewable (actual)] + [Groundwater: total renewable (actual)] - [Overlap between surface water and groundwater].*\n\n\n\n\n\n\n\n\n\n\n\nFresh water is naturally occurring water on the Earth's surface. It is a renewable but limited natural resource. Fresh water can only be renewed through the process of the water cycle, where water from seas, lakes, forests, land, rivers, and dams evaporates, forms clouds, and returns as precipitation. However, if more fresh water is consumed through human activities than is restored by nature, the result is that the quantity of fresh water available in lakes, rivers, dams and underground waters can be reduced which can cause serious damage to the surrounding environment.\n\n\n\n\n\n\n\n\n\n\n\n* http://www.fao.org/nr/water/aquastat/data/glossary/search.html?termId=4188&submitBtn=s&cls=yes\nStatistical concept(s):","theme":"territory","source_group":"wb"},{"code":"SE.PRM.REPT.FE.ZS","name":"Redoublantes, primaires, femmes ( % des inscriptions féminines)","description":"Les redoublants à l'école primaire correspondent au nombre d'élèves inscrits dans la même année que l'année précédente, en pourcentage de l'ensembl...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.REPT.FE.ZS?locations=CI","methodology":"Methodology: Share of repeaters in primary school is calculated by dividing the sum of repeaters in all grades of primary school by the total number of students enrolled in primary school, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.PRM.REPT.MA.ZS","name":"Redoublants, primaires, masculins ( % des inscriptions masculines)","description":"Les redoublants à l'école primaire correspondent au nombre d'élèves inscrits dans la même année que l'année précédente, en pourcentage de l'ensembl...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.REPT.MA.ZS?locations=CI","methodology":"Methodology: Share of repeaters in primary school is calculated by dividing the sum of repeaters in all grades of primary school by the total number of students enrolled in primary school, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.PRM.REPT.ZS","name":"Redoublants, primaires, total ( % du total des inscriptions)","description":"Les redoublants à l'école primaire correspondent au nombre d'élèves inscrits dans la même année que l'année précédente, en pourcentage de l'ensembl...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.REPT.ZS?locations=CI","methodology":"Methodology: Share of repeaters in primary school is calculated by dividing the sum of repeaters in all grades of primary school by the total number of students enrolled in primary school, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"GB.XPD.RSDV.GD.ZS","name":"Dépenses de recherche et développement (en % du PIB)","description":"Dépenses intérieures brutes en recherche et développement (R&D), exprimées en pourcentage du PIB.","source_link":"https://donnees.banquemondiale.org/indicateur/GB.XPD.RSDV.GD.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by taking the number of researchers in a specified year, dividing it by the total population—referencing the mid-year population figure—and then multiplying the result by one million.\nThe calculation of this indicator is performed by dividing the total domestic intramural expenditure on research and development (R&D) for a specified year by the gross domestic product (GDP)—which is the aggregate of gross value added by all resident producers in the economy, inclusive of distributive trades and transport, along with product taxes and less any subsidies not included in product values—and then multiplying the quotient by 100.  \nData are collected through national research and experimental development (R&D) surveys, either by the national statistical office or a line ministry (such as the Ministry for Science and Technology).  The data compilers are the UNESCO Institute for Statistics (UIS), Organisation for Economic Co-operation and Development (OECD), Eurostat (Statistical Office of the European Union) and the Network on Science and Technology Indicators – Ibero-American and Inter-American (RICYT), African Science, Technology and Innovation (STI) Indicators Initiative (ASTII) of the African Union Development Agency-NEPAD (AUDA-NEPAD).\nStatistical concept(s): The gross domestic expenditure on R&D indicator consists of the total expenditure (current and capital) on R&D by all resident companies, research institutes, university and government laboratories, etc. It excludes R&D expenditures financed by domestic firms but performed abroad. \nThe OECD's Frascati Manual defines research and experimental development as \"creative work undertaken on a systemic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications.\" R&D covers basic research, applied research, and experimental development.\n(1) Basic research - Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundation of phenomena and observable facts, without any particular application or use in view\n(2) Applied research - Applied research is also original investigation undertaken in order to acquire new knowledge; it is, however, directed primarily towards a specific practical aim or objective.\n(3) Experimental development - Experimental development is systematic work, drawing on existing knowledge gained from research and/or practical experience, which is directed to producing new materials, products or devices, to installing new processes, systems and services, or to improving substantially those already produced or installed.\nThe fields of science and technology used to classify R&D according to the Revised Fields of Science and Technology Classification are:\n1. Natural sciences;\n2. Engineering and technology;\n3. Medical and health sciences;\n4. Agricultural sciences;\n5. Social sciences;\n6. Humanities and the arts.\nThe data are obtained through statistical surveys which are regularly conducted at national level covering R&D performing entities in the private and public sectors.","theme":"tertiary","source_group":"wb"},{"code":"SP.POP.SCIE.RD.P6","name":"Chercheurs en R&D (par million d'habitants)","description":"Le nombre de chercheurs engagés dans la recherche et le développement (R&D), exprimé en millions.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.SCIE.RD.P6?locations=CI","methodology":"Methodology: This indicator is calculated by taking the number of researchers in a specified year, dividing it by the total population—referencing the mid-year population figure—and then multiplying the result by one million.\nData are collected through national research and experimental development (R&D) surveys, either by the national statistical office or a line ministry (such as the Ministry for Science and Technology).  The data compilers are the UNESCO Institute for Statistics (UIS), Organisation for Economic Co-operation and Development (OECD), Eurostat (Statistical Office of the European Union) and the Network on Science and Technology Indicators – Ibero-American and Inter-American (RICYT), African Science, Technology and Innovation (STI) Indicators Initiative (ASTII) of the African Union Development Agency-NEPAD (AUDA-NEPAD).\nStatistical concept(s): Researchers are professionals engaged in the conception or creation of new knowledge, products, processes, methods and systems, as well as in the management of these projects. Students studying at the master’s or doctoral level (ISCED2011 level 7 or 8) engaged in R&D are included. \nThe OECD's Frascati Manual defines research and experimental development as \"creative work undertaken on a systemic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications.\" R&D covers basic research, applied research, and experimental development (Reference: https://www.oecd-ilibrary.org/science-and-technology/frascati-manual-2015_9789264239012-en).  \n\n\n\n\n\n\n\n(1) Basic research - Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundation of phenomena and observable facts, without any particular application or use in view.\n\n\n\n\n\n\n\n(2) Applied research - Applied research is also original investigation undertaken in order to acquire new knowledge; it is, however, directed primarily towards a specific practical aim or objective.\n\n\n\n\n\n\n\n(3) Experimental development - Experimental development is systematic work, drawing on existing knowledge gained from research and/or practical experience, which is directed to producing new materials, products or devices, to installing new processes, systems and services, or to improving substantially those already produced or installed.\n\n\n\n\n\n\n\nThe fields of science and technology used to classify R&D according to the Revised Fields of Science and Technology Classification are:\n\n\n\n1. Natural sciences;\n\n\n\n2. Engineering and technology;\n\n\n\n3. Medical and health sciences;\n\n\n\n4. Agricultural sciences;\n\n\n\n5. Social sciences;\n\n\n\n6. Humanities and the arts.\n\n\n\n\n\n\n\nData are for full-time equivalent (FTE); the FTE of R&D personnel is defined as the ratio of working hours actually spent on R&D during a specific reference period (usually a calendar year) divided by the total number of hours conventionally worked in the same period by an individual or by a group. \n\n\n\n\n\n\n\nThe data are obtained through statistical surveys which are regularly conducted at national level covering R&D performing entities in the private and public sectors.","theme":"demo","source_group":"wb"},{"code":"BN.RES.INCL.CD","name":"Réserves et éléments connexes ($ US courants, balance des paiements)","description":"Les réserves et éléments connexes représentent la variation nette des avoirs en réserves internationales d'un pays résultant des transactions sur l...","source_link":"https://donnees.banquemondiale.org/indicateur/BN.RES.INCL.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"GC.REV.XGRT.GD.ZS","name":"Recettes, hors dons ( % du PIB)","description":"Le revenu est une augmentation de la valeur nette résultant d'une transaction.","source_link":"https://donnees.banquemondiale.org/indicateur/GC.REV.XGRT.GD.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.REV.XGRT.CN","name":"Chiffre d'affaires, hors subventions (LCU courante)","description":"Le revenu est une augmentation de la valeur nette résultant d'une transaction.","source_link":"https://donnees.banquemondiale.org/indicateur/GC.REV.XGRT.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"SH.SGR.CRSK.ZS","name":"Risque de dépenses catastrophiques pour les soins chirurgicaux ( % des personnes à risque)","description":"La proportion de la population exposée au risque de dépenses catastrophiques lorsque des soins chirurgicaux sont nécessaires.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.SGR.CRSK.ZS?locations=CI","methodology":"Methodology: The probability of experiencing impoverishment when surgical care is required and the probability of experiencing catastrophic expenditure (10 percent of total income) when surgical care is required.\nStatistical concept(s): The Lancet Commission on Global Surgery, assembled in 2013 to assess surgical care around the world. Commissioners engaged in an iterative global consultative process with partners in over 110 countries to develop six core indicators of the strength of a surgical system. Two indicators assess a country’s preparedness to deliver safe surgery and anesthesia,  two assess the current delivery of safe care, and two assess the state of financial risk protection for those seeking surgery.","theme":"sante","source_group":"wb"},{"code":"SH.SGR.IRSK.ZS","name":"Risque d'appauvrissement des dépenses pour les soins chirurgicaux ( % des personnes à risque)","description":"La proportion de la population risquant de s'appauvrir lorsque des soins chirurgicaux sont nécessaires.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.SGR.IRSK.ZS?locations=CI","methodology":"Methodology: The probability of experiencing impoverishment when surgical care is required and the probability of experiencing catastrophic expenditure (10 percent of total income) when surgical care is required.\nStatistical concept(s): The Lancet Commission on Global Surgery, assembled in 2013 to assess surgical care around the world. Commissioners engaged in an iterative global consultative process with partners in over 110 countries to develop six core indicators of the strength of a surgical system. Two indicators assess a country’s preparedness to deliver safe surgery and anesthesia,  two assess the current delivery of safe care, and two assess the state of financial risk protection for those seeking surgery.","theme":"sante","source_group":"wb"},{"code":"FR.INR.RISK","name":"Prime de risque sur le prêt (taux débiteur moins taux des bons du Trésor, %)","description":"La prime de risque sur les prêts est le taux d'intérêt appliqué par les banques sur les prêts aux clients du secteur privé moins le taux d'intérêt ...","source_link":"https://donnees.banquemondiale.org/indicateur/FR.INR.RISK?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"RL.EST","name":"État de droit : estimation","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/RL.EST?locations=CI","methodology":"","theme":"politique","source_group":"wb"},{"code":"RL.NO.SRC","name":"État de droit : nombre de sources","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/RL.NO.SRC?locations=CI","methodology":"Methodology: The WGI are composite governance indicators based on over 30 underlying data sources. \n\nThe WGI compile and summarize information from over 30 existing data sources that report the views and experiences of citizens, entrepreneurs, and experts in the public, private and NGO sectors from around the world, on the quality of various aspects of governance.\n\n•\tThe data sources must provide subjective perceptions of relevant dimensions of governance, as the WGI are based exclusively on this type of data.\n•\tThe sources must provide original primary data produced using a well-defined methodology.\n•\tThe data sources must cover multiple countries, so that cross-country comparisons are possible.\n•\tThe data sources must be updated regularly, ideally every year, although some WGI data sources are updated once every two or three years.\n\nThe WGI draw on four different types of source data:\n\n•\tSurveys of households and firms, including the Afrobarometer surveys, Gallup World Poll, and Global Competitiveness Report survey,\n•\tCommercial business information providers, including the Economist Intelligence Unit, S&P Global, and Political Risk Services,\n•\tNon-governmental organizations, including Global Integrity, Freedom House, Reporters Without Borders, and\n•\tPublic sector organizations, including the Country Policy and Institutional Assessments (CPIA) assessments of World Bank and regional development banks.\n\nFor the detailed list of sources, please refer to: https://www.worldbank.org/en/publication/worldwide-governance-indicators/documentation#2  \nStatistical concept(s): Number of sources indicates the number of underlying data sources on which the aggregate estimate is based.\n\nVariables from the data sources are assigned to each of these six governance dimensions.  For example, an assessment of the quality of the bureaucracy would be assigned to Government Effectiveness, a question about confidence in the police or the courts would be assigned to Rule of Law, and a question about the perceived likelihood of having to pay a bribe would be assigned to Control of Corruption.  In some cases, a single data source will have multiple questions that can be assigned to the same dimension.  In this case, the WGI use the average across all relevant questions from that data source. In addition each question from each data source is assigned to only one of the six governance dimensions, selecting the dimension that best matches the content of the question.","theme":"politique","source_group":"wb"},{"code":"RL.PER.RNK","name":"État de droit : rang centile","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/RL.PER.RNK?locations=CI","methodology":"","theme":"politique","source_group":"wb"},{"code":"RL.PER.RNK.LOWER","name":"État de droit : rang centile, limite inférieure de l'intervalle de confiance à 90 %","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/RL.PER.RNK.LOWER?locations=CI","methodology":"Methodology: A key feature of the WGI is that all country scores are accompanied by standard errors. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether.\n\nThe standard deviations are essential to the interpretation of the WGI.  It often is more appropriate to think of the WGI methodology as identifying a statistically likely range of values for the unobserved “true” level of governance in a country.  For example, the assumption of normality tells us that there is a 90 percent probability that the true unobserved level of governance conditional on the available data for a country is in a range given by plus or minus 1.64 standard deviations around the estimate of governance. These confidence intervals are informally referred to as the “margin of error” around the estimates of governance.\n\nThese 90 percent confidence interval are also reported in percentile rank terms (the percentile rank among all country estimates of governance, of the upper and lower bounds of the 90 percent confidence interval for each country).\nStatistical concept(s): Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank.  Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.  \n\nPercentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.","theme":"politique","source_group":"wb"},{"code":"RL.PER.RNK.UPPER","name":"Règle de droit : rang centile, limite supérieure de l'intervalle de confiance à 90 %","description":"La bonne gouvernance est essentielle au développement.","source_link":"https://donnees.banquemondiale.org/indicateur/RL.PER.RNK.UPPER?locations=CI","methodology":"Methodology: A key feature of the WGI is that all country scores are accompanied by standard errors. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether.\n\nThe standard deviations are essential to the interpretation of the WGI.  It often is more appropriate to think of the WGI methodology as identifying a statistically likely range of values for the unobserved “true” level of governance in a country.  For example, the assumption of normality tells us that there is a 90 percent probability that the true unobserved level of governance conditional on the available data for a country is in a range given by plus or minus 1.64 standard deviations around the estimate of governance. These confidence intervals are informally referred to as the “margin of error” around the estimates of governance.\n\nThese 90 percent confidence interval are also reported in percentile rank terms (the percentile rank among all country estimates of governance, of the upper and lower bounds of the 90 percent confidence interval for each country).\nStatistical concept(s): Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. \n\nPercentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.","theme":"politique","source_group":"wb"},{"code":"RL.STD.ERR","name":"État de droit : erreur type","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/RL.STD.ERR?locations=CI","methodology":"Methodology: The WGI are composite governance indicators based on over 30 underlying data sources. These data sources are rescaled and combined to create the six aggregate indicators using a statistical methodology known as an Unobserved Components Model (UCM). The six aggregate indicators are reported in two ways : (1) in their standard normal units, ranging from approximately -2.5 to 2.5, and (2) in percentile rank terms from 0 to 100, with higher values corresponding to better outcomes.\n\nA key feature of the WGI is that all country scores are accompanied by standard errors. These margins of error need to be taken into account when making comparisons across countries and over time. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether. \n\nPlease see more information at: https://www.worldbank.org/en/publication/worldwide-governance-indicators/documentation#1\nStatistical concept(s): Standard error indicates the precision of the estimate of governance. Larger values of the standard error indicate less precise estimates. A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.","theme":"politique","source_group":"wb"},{"code":"AG.LND.TOTL.RU.K2","name":"Superficie rurale (km²)","description":"Superficie des terres rurales en kilomètres carrés, dérivée de grilles d'étendue urbaine qui distinguent les zones urbaines et rurales en fonction ...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.TOTL.RU.K2?locations=CI","methodology":"Methodology: The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) urban extent grid distinguishes urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights . Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT)","theme":"primary","source_group":"wb"},{"code":"AG.LND.EL5M.RU.ZS","name":"Superficie rurale dont l'altitude est inférieure à 5 mètres ( % de la superficie totale des terres)","description":"La superficie des terres rurales inférieure à 5 m correspond au pourcentage de la superficie totale des terres dont l'élévation des terres rurales ...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.EL5M.RU.ZS?locations=CI","methodology":"Methodology: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).","theme":"primary","source_group":"wb"},{"code":"AG.LND.EL5M.RU.K2","name":"Zone rurale où l'altitude est inférieure à 5 mètres (km²)","description":"La superficie des terres rurales inférieures à 5 m correspond à la superficie totale des terres rurales en kilomètres carrés lorsque l'altitude est...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.EL5M.RU.K2?locations=CI","methodology":"Methodology: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).","theme":"primary","source_group":"wb"},{"code":"SP.RUR.TOTL","name":"Population rurale","description":"La population rurale fait référence aux personnes vivant dans les zones rurales telles que définies par les bureaux nationaux de statistique.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.RUR.TOTL?locations=CI","methodology":"Methodology: The indicator is calculated using World Bank's total population estimates and rural ratios derived from the United Nations World Urbanization Prospects.\nStatistical concept(s): Rural population is calculated as the difference between the total population and the urban population. Rural population is approximated as the midyear nonurban population. While a practical means of identifying the rural population, it is not a precise measure.","theme":"demo","source_group":"wb"},{"code":"SP.RUR.TOTL.ZS","name":"Population rurale (en % de la population totale)","description":"La population rurale fait référence aux personnes vivant dans les zones rurales telles que définies par les bureaux nationaux de statistique.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.RUR.TOTL.ZS?locations=CI","methodology":"Methodology: Percentages rural are calculated as the difference between 100 and the proportion of urban population in percentage.\nStatistical concept(s): Rural population is calculated as the difference between the total population and the urban population. Rural population is approximated as the midyear nonurban population. While a practical means of identifying the rural population, it is not a precise measure.","theme":"demo","source_group":"wb"},{"code":"SP.RUR.TOTL.ZG","name":"Croissance de la population rurale ( % annuel)","description":"Le taux de croissance annuel de la population rurale pour l’année t est le taux exponentiel de croissance de la population rurale en milieu d’année...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.RUR.TOTL.ZG?locations=CI","methodology":"Methodology: The indicator is calculated from rural population estimates. The rural population estimates are calulcated using World Bank's total population estimates and rural ratios derived from the United Nations World Urbanization Prospects.\nThe growth rate is computed using the exponential growth formula:\nr = ln(pn/p0)/n, \nwhere r is the exponential rate of growth, ln() is the natural logarithm, pn is the end period population, p0 is the beginning period population, and n is the number of years in between. Note that this is not the geometric growth rate used to compute compound growth over discrete periods.\nStatistical concept(s): Rural population is calculated as the difference between the total population and the urban population. Rural population is approximated as the midyear nonurban population. While a practical means of identifying the rural population, it is not a precise measure.","theme":"demo","source_group":"wb"},{"code":"EN.POP.EL5M.RU.ZS","name":"Population rurale vivant dans des zones où l'altitude est inférieure à 5 mètres ( % de la population totale)","description":"La population rurale de moins de 5 m correspond au pourcentage de la population totale vivant dans des zones où l'altitude est de 5 mètres ou moins.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.POP.EL5M.RU.ZS?locations=CI","methodology":"Methodology: Population counts in low elevation zones in the year 1990 as described by GRUMPv1 input estimates allocated into 3 arc second grid cells. Population counts in low elevation zones in the year 2000 as described by GRUMPv1 input estimates allocated into 3 arc second grid cells. Population counts in low elevation zones in the year 2010 derived from the application of United Nations 2000-2010 national growth rates to year 2000 population data from GRUMPv1 ( see documentation for full description of methodologies ).","theme":"demo","source_group":"wb"},{"code":"CM.MKT.INDX.ZG","name":"Indices S&P Global Equity (variation annuelle en %)","description":"Les indices S&P Global Equity mesurent la variation du prix du dollar américain sur les marchés boursiers couverts par les indices nationaux S&P BMI.","source_link":"https://donnees.banquemondiale.org/indicateur/CM.MKT.INDX.ZG?locations=CI","methodology":"Methodology: The S&P Global Broad Market Index (BMI) series is a global index suite with a transparent, modular structure that has been fully float-adjusted since 1989. It includes more than 14,000 stocks from 25 developed and 24 emerging markets. It is a rules-based index that measures global stock market performance. The index covers all publicly listed equities with float-adjusted market values of US$ 100 million or more and that meet minimum liquidity criteria measured by median daily value traded figures. The S&P Global BMI is made up of the S&P Developed BMI and S&P Emerging BMI. Additional information about methodology can be found on the S&P Global website: https://www.spglobal.com/spdji/en/documents/methodologies/methodology-sp-global-bmi-sp-ifci-indices.pdf\n\nThe percentage changes for France, Germany, Japan, the United Kingdom, and the United States refer to local stock market prices: CAC40, DAX, Nikkei, FTSE, S&P500.\nStatistical concept(s): Ratios of end-of-period levels in U.S. dollars over previous end-of-period values in U.S. dollars times 100.","theme":"business","source_group":"wb"},{"code":"SE.PRE.ENRR","name":"Inscriptions à l'école maternelle ( % brut)","description":"Le taux brut de scolarisation est le rapport entre la scolarisation totale, quel que soit l'âge, et la population du groupe d'âge qui correspond of...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRE.ENRR?locations=CI","methodology":"Methodology: Gross enrollment ratio for pre-primary school is calculated by dividing the number of students enrolled in pre-primary education regardless of age by the population of the age group which officially corresponds to pre-primary education, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.PRE.ENRR.FE","name":"Scolarisation, préprimaire, femmes ( % brut)","description":"Le taux brut de scolarisation est le rapport entre la scolarisation totale, quel que soit l'âge, et la population du groupe d'âge qui correspond of...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRE.ENRR.FE?locations=CI","methodology":"Methodology: Gross enrollment ratio for pre-primary school is calculated by dividing the number of students enrolled in pre-primary education regardless of age by the population of the age group which officially corresponds to pre-primary education, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.PRE.ENRR.MA","name":"Inscriptions scolaires, préprimaire, hommes ( % brut)","description":"Le taux brut de scolarisation est le rapport entre la scolarisation totale, quel que soit l'âge, et la population du groupe d'âge qui correspond of...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRE.ENRR.MA?locations=CI","methodology":"Methodology: Gross enrollment ratio for pre-primary school is calculated by dividing the number of students enrolled in pre-primary education regardless of age by the population of the age group which officially corresponds to pre-primary education, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.PRM.ENRR","name":"Inscriptions dans l'enseignement primaire ( % brut)","description":"Le taux brut de scolarisation est le rapport entre la scolarisation totale, quel que soit l'âge, et la population du groupe d'âge qui correspond of...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.ENRR?locations=CI","methodology":"Methodology: Gross enrollment ratio for primary school is calculated by dividing the number of students enrolled in primary education regardless of age by the population of the age group which officially corresponds to primary education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system.","theme":"education","source_group":"wb"},{"code":"SE.PRM.NENR","name":"Scolarisation, primaire ( % net)","description":"Le taux net de scolarisation est le rapport entre les enfants d’âge scolaire officiel qui sont inscrits à l’école et la population d’âge scolaire o...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.NENR?locations=CI","methodology":"Methodology: Net enrollment rate for primary school is calculated by dividing the number of students of official school age enrolled in primary education by the population of the age group which officially corresponds to primary education, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.ENR.PRIM.FM.ZS","name":"Scolarisation, primaire (brut), indice de parité hommes-femmes (IPS)","description":"L'indice de parité entre les sexes pour le taux brut de scolarisation dans l'enseignement primaire est le ratio filles/garçons inscrits au niveau p...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.ENR.PRIM.FM.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by dividing female gross enrollment ratio in primary education by male gross enrollment ratio in primary education. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.ENR.PRSC.FM.ZS","name":"Scolarisation, primaire et secondaire (brut), indice de parité hommes-femmes (IPS)","description":"L'indice de parité entre les sexes pour le taux brut de scolarisation dans l'enseignement primaire et secondaire est le ratio filles/garçons inscri...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.ENR.PRSC.FM.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by dividing female gross enrollment ratio in primary and secondary education by male gross enrollment ratio in primary and secondary education. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.PRM.ENRR.FE","name":"Scolarisation, primaire, femmes ( % brut)","description":"Le taux brut de scolarisation est le rapport entre la scolarisation totale, quel que soit l'âge, et la population du groupe d'âge qui correspond of...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.ENRR.FE?locations=CI","methodology":"Methodology: Gross enrollment ratio for primary school is calculated by dividing the number of students enrolled in primary education regardless of age by the population of the age group which officially corresponds to primary education, and multiplying by 100.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system.","theme":"education","source_group":"wb"},{"code":"SE.PRM.NENR.FE","name":"Scolarisation, primaire, femmes ( % net)","description":"Le taux net de scolarisation est le rapport entre les enfants d’âge scolaire officiel qui sont inscrits à l’école et la population d’âge scolaire o...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.NENR.FE?locations=CI","methodology":"Methodology: Net enrollment rate for primary school is calculated by dividing the number of students of official school age enrolled in primary education by the population of the age group which officially corresponds to primary education, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.PRM.ENRR.MA","name":"Scolarisation, primaire, hommes ( % brut)","description":"Le taux brut de scolarisation est le rapport entre la scolarisation totale, quel que soit l'âge, et la population du groupe d'âge qui correspond of...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.ENRR.MA?locations=CI","methodology":"Methodology: Gross enrollment ratio for primary school is calculated by dividing the number of students enrolled in primary education regardless of age by the population of the age group which officially corresponds to primary education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system.","theme":"education","source_group":"wb"},{"code":"SE.PRM.NENR.MA","name":"Scolarisation, primaire, garçons ( % net)","description":"Le taux net de scolarisation est le rapport entre les enfants d’âge scolaire officiel qui sont inscrits à l’école et la population d’âge scolaire o...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.NENR.MA?locations=CI","methodology":"Methodology: Net enrollment rate for primary school is calculated by dividing the number of students of official school age enrolled in primary education by the population of the age group which officially corresponds to primary education, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.PRM.PRIV.ZS","name":"Inscriptions dans les écoles, primaires, privées ( % du total des écoles primaires)","description":"Les inscriptions privées font référence aux élèves ou étudiants inscrits dans des établissements qui ne sont pas gérés par une autorité publique ma...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.PRIV.ZS?locations=CI","methodology":"Methodology: The share of students in private primary school is calculated by dividing the number of students enrolled in private educational institutions at primary level by total enrollment (public and private) at the same level of education, and multiplying by 100.\n\n\n\n\n\n\n\n\n\n\n\n\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\n\n\n\n\n\n\n\n\n\n\n\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The share of enrollment in private institutions indicates the scale and capacity of private education within a country. A high percentage suggests strong involvement of the non-governmental sector (including religious bodies, other organizations, associations, communities, private enterprises or persons) in providing organized educational programmes. However, in countries where private institutions are substantially subsidized or aided by the government, the distinction between private and public educational institutions may be less clear-cut especially when certain students are directly financed through government scholarships.","theme":"education","source_group":"wb"},{"code":"SE.SEC.ENRR","name":"Inscriptions dans le secondaire ( % brut)","description":"Le taux brut de scolarisation est le rapport entre la scolarisation totale, quel que soit l'âge, et la population du groupe d'âge qui correspond of...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.ENRR?locations=CI","methodology":"Methodology: Gross enrollment ratio for secondary school is calculated by dividing the number of students enrolled in secondary education regardless of age by the population of the age group which officially corresponds to secondary education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system.","theme":"education","source_group":"wb"},{"code":"SE.SEC.NENR","name":"Inscriptions dans le secondaire ( % net)","description":"Le taux net de scolarisation est le rapport entre les enfants d’âge scolaire officiel qui sont inscrits à l’école et la population d’âge scolaire o...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.NENR?locations=CI","methodology":"Methodology: Net enrollment rate for secondary school is calculated by dividing the number of students of official school age enrolled in secondary education by the population of the age group which officially corresponds to secondary education, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.ENR.SECO.FM.ZS","name":"Scolarisation, secondaire (brut), indice de parité hommes-femmes (IPS)","description":"L'indice de parité entre les sexes pour le taux brut de scolarisation dans l'enseignement secondaire est le ratio filles/garçons inscrits au niveau...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.ENR.SECO.FM.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by dividing female gross enrollment ratio in secondary education by male gross enrollment ratio in secondary education. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.SEC.ENRR.FE","name":"Scolarisation, secondaire, femmes ( % brut)","description":"Le taux brut de scolarisation est le rapport entre la scolarisation totale, quel que soit l'âge, et la population du groupe d'âge qui correspond of...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.ENRR.FE?locations=CI","methodology":"Methodology: Gross enrollment ratio for secondary school is calculated by dividing the number of students enrolled in secondary education regardless of age by the population of the age group which officially corresponds to secondary education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system.","theme":"education","source_group":"wb"},{"code":"SE.SEC.NENR.FE","name":"Scolarisation, secondaire, femmes ( % net)","description":"Le taux net de scolarisation est le rapport entre les enfants d’âge scolaire officiel qui sont inscrits à l’école et la population d’âge scolaire o...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.NENR.FE?locations=CI","methodology":"Methodology: Net enrollment rate for secondary school is calculated by dividing the number of students of official school age enrolled in secondary education by the population of the age group which officially corresponds to secondary education, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.SEC.ENRR.MA","name":"Scolarisation, secondaire, hommes ( % brut)","description":"Le taux brut de scolarisation est le rapport entre la scolarisation totale, quel que soit l'âge, et la population du groupe d'âge qui correspond of...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.ENRR.MA?locations=CI","methodology":"Methodology: Gross enrollment ratio for secondary school is calculated by dividing the number of students enrolled in secondary education regardless of age by the population of the age group which officially corresponds to secondary education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system.","theme":"education","source_group":"wb"},{"code":"SE.SEC.NENR.MA","name":"Scolarisation, secondaire, hommes ( % net)","description":"Le taux net de scolarisation est le rapport entre les enfants d’âge scolaire officiel qui sont inscrits à l’école et la population d’âge scolaire o...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.NENR.MA?locations=CI","methodology":"Methodology: Net enrollment rate for secondary school is calculated by dividing the number of students of official school age enrolled in secondary education by the population of the age group which officially corresponds to secondary education, and multiplying by 100. \n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s):","theme":"education","source_group":"wb"},{"code":"SE.SEC.PRIV.ZS","name":"Inscriptions dans les écoles, secondaires, privées ( % du total des écoles secondaires)","description":"Les inscriptions privées font référence aux élèves ou étudiants inscrits dans des établissements qui ne sont pas gérés par une autorité publique ma...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.PRIV.ZS?locations=CI","methodology":"Methodology: The share of students in private secondary school is calculated by dividing the number of students enrolled in private educational institutions at secondary level by total enrollment (public and private) at the same level of education, and multiplying by 100.\n\n\n\n\n\n\n\n\n\n\n\n\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\n\n\n\n\n\n\n\n\n\n\n\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The share of enrollment in private institutions indicates the scale and capacity of private education within a country. A high percentage suggests strong involvement of the non-governmental sector (including religious bodies, other organizations, associations, communities, private enterprises or persons) in providing organized educational programmes. However, in countries where private institutions are substantially subsidized or aided by the government, the distinction between private and public educational institutions may be less clear-cut especially when certain students are directly financed through government scholarships.","theme":"education","source_group":"wb"},{"code":"SE.TER.ENRR","name":"Inscriptions dans l'enseignement supérieur ( % brut)","description":"Le taux brut de scolarisation est le rapport entre la scolarisation totale, quel que soit l'âge, et la population du groupe d'âge qui correspond of...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.ENRR?locations=CI","methodology":"Methodology: Gross enrollment ratio for tertiary school is calculated by dividing the number of students enrolled in tertiary education regardless of age by the population of the age group which officially corresponds to tertiary education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system.","theme":"education","source_group":"wb"},{"code":"SE.ENR.TERT.FM.ZS","name":"Scolarisation, enseignement supérieur (brut), indice de parité hommes-femmes (IPS)","description":"L'indice de parité entre les sexes pour le taux brut de scolarisation dans l'enseignement supérieur est le ratio femmes/hommes inscrits au niveau s...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.ENR.TERT.FM.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by dividing female gross enrollment ratio in tertiary education by male gross enrollment ratio in tertiary education. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The Gender Parity Index (GPI) indicates parity between girls and boys. A GPI of less than 1 suggests girls are more disadvantaged than boys in learning opportunities and a GPI of greater than 1 suggests the other way around.","theme":"education","source_group":"wb"},{"code":"SE.TER.ENRR.FE","name":"Scolarisation, enseignement supérieur, femmes ( % brut)","description":"Le taux brut de scolarisation est le rapport entre la scolarisation totale, quel que soit l'âge, et la population du groupe d'âge qui correspond of...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.ENRR.FE?locations=CI","methodology":"Methodology: Gross enrollment ratio for tertiary school is calculated by dividing the number of students enrolled in tertiary education regardless of age by the population of the age group which officially corresponds to tertiary education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system.","theme":"education","source_group":"wb"},{"code":"SE.TER.ENRR.MA","name":"Scolarisation, enseignement supérieur, hommes ( % brut)","description":"Le taux brut de scolarisation est le rapport entre la scolarisation totale, quel que soit l'âge, et la population du groupe d'âge qui correspond of...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.ENRR.MA?locations=CI","methodology":"Methodology: Gross enrollment ratio for tertiary school is calculated by dividing the number of students enrolled in tertiary education regardless of age by the population of the age group which officially corresponds to tertiary education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system.","theme":"education","source_group":"wb"},{"code":"IP.JRN.ARTC.SC","name":"Articles de revues scientifiques et techniques","description":"Le nombre d'articles fait référence à des publications provenant d'une sélection d'actes de conférence et de revues à comité de lecture de Scopus d...","source_link":"https://donnees.banquemondiale.org/indicateur/IP.JRN.ARTC.SC?locations=CI","methodology":"Methodology: The Science and Engineering Indicators 2024 report “Publications Output: U.S. Trends and International Comparisons” uses a large database of publication records as a source of bibliometric data. Bibliometric data include each article’s title, author(s), authors’ institution(s), references, journal title, unique article-identifying information (journal volume, issue, and page numbers or digital object identifier), and year or date of publication. The PBS report uses Scopus, a bibliometric database owned by Elsevier and containing scientific literature with English titles and abstracts, to examine national and global scientific publication–related activity.? \n\nArticle counts refer to publications from a selection of conference proceedings and peer-reviewed journals in science and engineering fields from Scopus, according to the National Center for Science and Engineering Statistics Taxonomy of Disciplines:  agricultural sciences, astronomy and astrophysics, biological and biomedical sciences, chemistry, computer and information sciences; engineering; geosciences, atmospheric sciences, and ocean sciences; health sciences; material sciences; mathematics and statistics; natural resources and conservation; physics; psychology; social sciences.\n\n\n\nStatistical concept(s): The number of journal articles is presented using fractional counting: a method of counting science and engineering publications in which credit for coauthored publications is divided among the collaborating institutions or regions, countries, or economies based on the proportion of their participating authors. Fractional counting allocates the publication count based on the proportion of the coauthors named on the article with institutional addresses from each region, country, or economy. Fractional counting enables the counts to sum up to the number of total articles. (Source: https://ncses.nsf.gov/pubs/nsb202333/glossary)","theme":"education","source_group":"wb"},{"code":"SE.SEC.DURS","name":"Enseignement secondaire, durée (années)","description":"La durée du secondaire fait référence au nombre de années (années) dans l'école secondaire.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.DURS?locations=CI","methodology":"Methodology: Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Aggregate data are based on World Bank estimates.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator measures the number of years that a country's laws or regulations specify for secondary education.  It aids in identifying the population of school-aged children at different educational levels. Additionally, this metric serves as crucial input data necessary for generating various indicators and evaluating a country's capacity to meet educational demand.","theme":"education","source_group":"wb"},{"code":"SE.SEC.ENRL.GC","name":"Enseignement secondaire, élèves généraux","description":"Les élèves du secondaire général correspondent au nombre d'élèves du secondaire inscrits dans des programmes d'enseignement général, y compris la f...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.ENRL.GC?locations=CI","methodology":"Methodology: Enrollment includes Individuals officially registered in a given educational programme, or stage or module thereof, regardless of age.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.SEC.ENRL.GC.FE.ZS","name":"Enseignement secondaire, élèves du secteur général ( % de filles)","description":"Les élèves du secondaire général correspondent au nombre d'élèves du secondaire inscrits dans des programmes d'enseignement général, y compris la f...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.ENRL.GC.FE.ZS?locations=CI","methodology":"Methodology: Percentage of female enrollment is calculated by dividing the total number of female students at a given level of education by the total enrollment at the same level, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.SEC.ENRL","name":"Enseignement secondaire, élèves","description":"Les élèves de l'enseignement secondaire correspondent au nombre total d'élèves inscrits au niveau secondaire dans les écoles publiques et privées.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.ENRL?locations=CI","methodology":"Methodology: Enrollment includes Individuals officially registered in a given educational programme, or stage or module thereof, regardless of age.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The International Standard Classification of Education (ISCED) differentiates between lower secondary education and upper secondary education within its educational programs. ISCED level 2, or  lower secondary education, are designed to build upon the foundational literacy and numeracy skills acquired at ISCED level 1. The objective at this stage is to establish a base for lifelong learning and human development, which can be further enhanced by subsequent educational opportunities. Certain education systems may introduce vocational education programs at this level to equip individuals with skills that are directly applicable to the workforce.\n\n\n\n\n\n\n\n\n\n\n\n\n\nAt ISCED level 3, or upper secondary education, programs are structured to finalize the secondary education phase, preparing students for higher education or to enter the job market with relevant skills, or in some cases, to achieve both objectives.","theme":"education","source_group":"wb"},{"code":"SE.SEC.ENRL.FE.ZS","name":"Enseignement secondaire, élèves ( % de filles)","description":"Le pourcentage d'élèves de sexe féminin dans le total des élèves du secondaire comprend les inscriptions dans les écoles publiques et privées.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.ENRL.FE.ZS?locations=CI","methodology":"Methodology: Percentage of female enrollment is calculated by dividing the total number of female students at a given level of education by the total enrollment at the same level, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.SEC.TCHR","name":"Enseignement secondaire, enseignants","description":"Dans l'enseignement secondaire, les enseignants font référence au nombre total d'enseignants au niveau secondaire, y compris les enseignants à temp...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.TCHR?locations=CI","methodology":"Methodology: Teachers refer to persons employed full-time or part-time in an official capacity to guide and direct the learning experience of pupils and students, irrespective of their qualifications or the delivery mechanism, i.e. face-to-face and/or at a distance. This definition excludes educational personnel who have no active teaching duties (e.g. headmasters, headmistresses or principals who do not teach) or who work occasionally or in a voluntary capacity in educational institutions.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The metric of personnel count primarily engaged in teaching and/or research reflects the scale, diversity, and distribution of educational staff within a nation's academic institutions. An increased count is anticipated to enrich the educational setting by means of dedicated teaching, practical research, academic pursuits, and contributions to the service of national educational policies.","theme":"education","source_group":"wb"},{"code":"SE.SEC.TCHR.FE.ZS","name":"Enseignement secondaire, enseignants ( % de femmes)","description":"Les enseignantes en pourcentage du nombre total d’enseignants dans l’enseignement secondaire comprennent les enseignantes à temps plein et à temps ...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.TCHR.FE.ZS?locations=CI","methodology":"Methodology: The share of female teachers in secondary education is calculated by dividing the total number of female teachers at secondary level of education by the total number of teachers at the same level, and multiplying by 100.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The share of female teachers shows the level of gender representation in the teaching force. A value of greater than 50% indicates more opportunities or preference for women to participate in teaching activities.","theme":"education","source_group":"wb"},{"code":"SE.SEC.TCHR.FE","name":"Enseignement secondaire, enseignants, femmes","description":"L'enseignement secondaire, enseignantes, fait référence au nombre total d'enseignantes au niveau secondaire, y compris les enseignantes à temps ple...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.TCHR.FE?locations=CI","methodology":"Methodology: Teachers refer to persons employed full-time or part-time in an official capacity to guide and direct the learning experience of pupils and students, irrespective of their qualifications or the delivery mechanism, i.e. face-to-face and/or at a distance. This definition excludes educational personnel who have no active teaching duties (e.g. headmasters, headmistresses or principals who do not teach) or who work occasionally or in a voluntary capacity in educational institutions.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The metric of personnel count primarily engaged in teaching and/or research reflects the scale, diversity, and distribution of educational staff within a nation's academic institutions. An increased count is anticipated to enrich the educational setting by means of dedicated teaching, practical research, academic pursuits, and contributions to the service of national educational policies.","theme":"education","source_group":"wb"},{"code":"SE.SEC.ENRL.VO","name":"Enseignement secondaire, élèves de l'enseignement professionnel","description":"Les élèves du secondaire professionnel correspondent au nombre d'élèves du secondaire inscrits dans des programmes d'enseignement technique et prof...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.ENRL.VO?locations=CI","methodology":"Methodology: Enrollment includes Individuals officially registered in a given educational programme, or stage or module thereof, regardless of age.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"SE.SEC.ENRL.VO.FE.ZS","name":"Enseignement secondaire, élèves de l'enseignement professionnel ( % de filles)","description":"Les élèves du secondaire professionnel correspondent au nombre d'élèves du secondaire inscrits dans des programmes d'enseignement technique et prof...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.ENRL.VO.FE.ZS?locations=CI","methodology":"Methodology: Percentage of female enrollment is calculated by dividing the total number of female students at a given level of education by the total enrollment at the same level, and multiplying by 100.\n\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \n\nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).","theme":"education","source_group":"wb"},{"code":"BX.TRF.CURR.CD","name":"Recettes des revenus secondaires (BdP, $ US courants)","description":"Le revenu secondaire fait référence aux transferts enregistrés dans la balance des paiements chaque fois qu'une économie fournit ou reçoit des bien...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.TRF.CURR.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BM.TRF.PRVT.CD","name":"Revenu secondaire, autres secteurs, paiements (BdP, $ US courants)","description":"Le revenu secondaire fait référence aux transferts enregistrés dans la balance des paiements chaque fois qu'une économie fournit ou reçoit des bien...","source_link":"https://donnees.banquemondiale.org/indicateur/BM.TRF.PRVT.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"IT.NET.SECR","name":"Serveurs Internet sécurisés","description":"Le nombre de certificats TLS/SSL distincts et de confiance publique trouvés dans l'enquête Netcraft Secure Server (par pays d'hébergement).","source_link":"https://donnees.banquemondiale.org/indicateur/IT.NET.SECR?locations=CI","methodology":"Methodology: Netcraft's survey counts (unique) valid certificates issued by widely-trusted third-party certification authorities. A certificate must be valid, that is it must be within its validity period (certificates are usually valid for up to 39 months), and the digital signatures on the certificate must check successfully. It must be issued by third party certificate issuer that is recognised by Netcraft. \nNetcraft gathers a list of possible SSL web sites to investigate from a range of different sources.  The data reflects the December survey in that year.\n\nSSL (Secure Socket Layer) is a protocol developed by Netscape for encrypted transmission over TCP/IP networks. It sets up a secure end-to-end link over which HTTP or any other application protocol can operate. The most common application of SSL is HTTPS for SSL-encrypted HTTP. It has now been replaced with a IETF-standardised version, TLS.\n\nSurveying: Netcraft only visits sites on the standard HTTPS port, 443. Whilst it is possible to run an HTTPS server on a different port (using a URL like https://example.com:7000) this behavior is quite rare on public websites. For example, usual ports are often used for administrative interfaces and other services not intended for the general public.\n\nNetcraft tries to visit every public secure website. Note that the survey does not include secure mail servers (SMTP) or intranet sites. So the final number of certificates for each certificate authority will be lower than the total number of server certificates sold by that authority. The survey makes multiple HTTPS request types to identify both web server capabilities, and the certificates in use. Netcraft makes retry visits to any non-responding IP addresses once, several hours after the failed visits. The information made available by an HTTPS server is more substantial than with http servers. The most interesting piece of information available from HTTP servers is the server signature; this can be analyzed to give straightforward empirical evidence about the relative popularity of server software on web sites across the Internet. The same information is also available from HTTPS servers. Additionally, the content of the site's X.509 certificate is available, providing details about both the company or organization owning the site, and the certificate issuer. Furthermore, in most cases the TCP/IP characteristics of the network connection allows to determine the operating system used.\n\nStatistical concept(s): The survey examines the use of encrypted transactions through extensive automated exploration, tallying the number of web sites using HTTPS. This analysis relates to those sites found in the survey where the certificate is valid for the hostname, and the certificate has been issued from a publicly-trusted root. The indicator refers to valid, third-party certificates. Included are sites found in the survey where the common name in the certificate matched the hostname, and the certificate's digital signature was not detected as being self-signed. The location is derived from the hosting location of the sites using the certificates (rather than the countries indicated on the certificates themselves.) This analysis relates to those sites found in the survey where the common name in the certificate matched the hostname, and the certificate's digital signature was not detected as being self-signed.","theme":"tertiary","source_group":"wb"},{"code":"IT.NET.SECR.P6","name":"Serveurs Internet sécurisés (pour 1 million de personnes)","description":"Le nombre de certificats TLS/SSL distincts et de confiance publique trouvés dans l'enquête Netcraft Secure Server (par pays d'hébergement), pour 1 ...","source_link":"https://donnees.banquemondiale.org/indicateur/IT.NET.SECR.P6?locations=CI","methodology":"Methodology: Netcraft's survey counts (unique) valid certificates issued by widely-trusted third-party certification authorities. A certificate must be valid, that is it must be within its validity period (certificates are usually valid for up to 39 months), and the digital signatures on the certificate must check successfully. It must be issued by third party certificate issuer that is recognised by Netcraft. \nNetcraft gathers a list of possible SSL web sites to investigate from a range of different sources.  The data reflects the December survey in that year.\n\nSSL (Secure Socket Layer) is a protocol developed by Netscape for encrypted transmission over TCP/IP networks. It sets up a secure end-to-end link over which HTTP or any other application protocol can operate. The most common application of SSL is HTTPS for SSL-encrypted HTTP. It has now been replaced with a IETF-standardised version, TLS.\n\nSurveying: Netcraft only visits sites on the standard HTTPS port, 443. Whilst it is possible to run an HTTPS server on a different port (using a URL like https://example.com:7000) this behavior is quite rare on public websites. For example, usual ports are often used for administrative interfaces and other services not intended for the general public.\n\nNetcraft tries to visit every public secure website. Note that the survey does not include secure mail servers (SMTP) or intranet sites. So the final number of certificates for each certificate authority will be lower than the total number of server certificates sold by that authority. The survey makes multiple HTTPS request types to identify both web server capabilities, and the certificates in use. Netcraft makes retry visits to any non-responding IP addresses once, several hours after the failed visits. The information made available by an HTTPS server is more substantial than with http servers. The most interesting piece of information available from HTTP servers is the server signature; this can be analyzed to give straightforward empirical evidence about the relative popularity of server software on web sites across the Internet. The same information is also available from HTTPS servers. Additionally, the content of the site's X.509 certificate is available, providing details about both the company or organization owning the site, and the certificate issuer. Furthermore, in most cases the TCP/IP characteristics of the network connection allows to determine the operating system used.\nStatistical concept(s): The survey examines the use of encrypted transactions through extensive automated exploration, tallying the number of web sites using HTTPS. This analysis relates to those sites found in the survey where the certificate is valid for the hostname, and the certificate has been issued from a publicly-trusted root. The indicator refers to valid, third-party certificates. Included are sites found in the survey where the common name in the certificate matched the hostname, and the certificate's digital signature was not detected as being self-signed. The location is derived from the hosting location of the sites using the certificates (rather than the countries indicated on the certificates themselves.) This analysis relates to those sites found in the survey where the common name in the certificate matched the hostname, and the certificate's digital signature was not detected as being self-signed.","theme":"tertiary","source_group":"wb"},{"code":"SL.EMP.SELF.FE.ZS","name":"Travailleurs indépendants, femmes ( % de l'emploi féminin) (estimation modélisée de l'OIT)","description":"Les travailleurs autonomes sont les travailleurs qui, travaillant à leur propre compte ou avec un ou plusieurs associés ou en coopérative, occupent...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.SELF.FE.ZS?locations=CI","methodology":"Methodology: The proportion of self-employed workers to the total employed is calculated as follows: Self-employed workers/Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.SELF.MA.ZS","name":"Travailleurs indépendants, hommes ( % de l'emploi masculin) (estimation modélisée de l'OIT)","description":"Les travailleurs autonomes sont les travailleurs qui, travaillant à leur propre compte ou avec un ou plusieurs associés ou en coopérative, occupent...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.SELF.MA.ZS?locations=CI","methodology":"Methodology: The proportion of self-employed workers to the total employed is calculated as follows: Self-employed workers/Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.SELF.ZS","name":"Travailleurs indépendants, total ( % de l'emploi total) (estimation modélisée de l'OIT)","description":"Les travailleurs autonomes sont les travailleurs qui, travaillant à leur propre compte ou avec un ou plusieurs associés ou en coopérative, occupent...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.SELF.ZS?locations=CI","methodology":"Methodology: The proportion of self-employed workers to the total employed is calculated as follows: Self-employed workers/Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"BX.GSR.NFSV.CD","name":"Exportations de services ($ US courants, BdP)","description":"Les exportations de services sont des services fournis par des résidents à des non-résidents.","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GSR.NFSV.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BM.GSR.NFSV.CD","name":"Importations de services ($ US courants, BdP)","description":"Les importations de services sont des services fournis par des non-résidents aux résidents.","source_link":"https://donnees.banquemondiale.org/indicateur/BM.GSR.NFSV.CD?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"NV.SRV.TOTL.ZS","name":"Services, valeur ajoutée ( % du PIB)","description":"Les industries de services correspondent aux divisions 45 à 99 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.SRV.TOTL.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"tertiary","source_group":"wb"},{"code":"NV.SRV.TOTL.KD.ZG","name":"Services, valeur ajoutée (croissance annuelle en %)","description":"Les industries de services correspondent aux divisions 45 à 99 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.SRV.TOTL.KD.ZG?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"tertiary","source_group":"wb"},{"code":"NV.SRV.TOTL.KD","name":"Services, valeur ajoutée (en dollars constants de 2015)","description":"Les industries de services correspondent aux divisions 45 à 99 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.SRV.TOTL.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"tertiary","source_group":"wb"},{"code":"NV.SRV.TOTL.KN","name":"Services, valeur ajoutée (UCT constantes)","description":"Les industries de services correspondent aux divisions 45 à 99 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.SRV.TOTL.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"tertiary","source_group":"wb"},{"code":"NV.SRV.TOTL.CN","name":"Services, valeur ajoutée (LCU actuelle)","description":"Les industries de services correspondent aux divisions 45 à 99 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.SRV.TOTL.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"tertiary","source_group":"wb"},{"code":"NV.SRV.TOTL.CD","name":"Services, valeur ajoutée (en dollars américains courants)","description":"Les industries de services correspondent aux divisions 45 à 99 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.SRV.TOTL.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"tertiary","source_group":"wb"},{"code":"NV.SRV.EMPL.KD","name":"Services, valeur ajoutée par travailleur (en dollars constants de 2015)","description":"Les industries de services correspondent aux divisions 45 à 99 de la CITI (Rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.SRV.EMPL.KD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Value added per worker is calculated by dividing value added of a sector by the number employed in the sector.\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"tertiary","source_group":"wb"},{"code":"SP.POP.BRTH.MF","name":"Rapport de masculinité à la naissance (naissances masculines par naissances féminines)","description":"Le sex-ratio à la naissance fait référence aux naissances masculines par rapport aux naissances féminines.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.BRTH.MF?locations=CI","methodology":"Methodology: Sex ratio at birth is calculated as number of male births divided by number of female births.\nStatistical concept(s): If the sex ratio at birth is greater than 1, it indicates more boys born that year than girls.","theme":"demo","source_group":"wb"},{"code":"SL.UEM.NEET.FE.ZS","name":"Proportion de femmes parmi les jeunes qui ne sont ni scolarisés, ni en emploi, ni en formation ( % de la population féminine jeune)","description":"La part des jeunes ne suivant pas d’études, d’emploi ou de formation (également connue sous le nom de « taux NEET ») indique le nombre de jeunes ne...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.NEET.FE.ZS?locations=CI","methodology":"Methodology: The youth NEET rate is calculated as follows: NEET rate = (Youth – Youth in employment – Youth not in employment but in education or training) / Youth x 100. \n\nIt is important to note here that youth both in employment and education or training simultaneously should not be double counted when subtracted from the total number of youth. The formula can also be expressed as: NEET rate =  [(Unemployed youth + Youth outside the labor force) – (Unemployed youth in education or training + Youth outside the labor force in education or training)]  / Youth x 100. \n\nThe calculation of this indicator requires having reliable information on both the labor market status and the participation in education or training of youth. The quality of such information is heavily dependent on the questionnaire design, the sample size and design and the accuracy of respondents' answers. To avoid misinterpreting this indicator, it is important to bear in mind that it is composed of two different sub-groups (unemployed youth not in education or training and youth outside the labor force not in education or training). The prevalence and composition of each sub-group would have policy implications, and thus should also be considered when analyzing the NEET rate.\n\n\n\n\n\n\n\nThe preferred official national data source for this indicator is a household-based labor force survey. In the absence of a labor force survey, a population census and/or other type of household survey with an appropriate employment module may be used to obtain the required data.\nStatistical concept(s): For the purposes of these indicators, persons will be considered in education if they are in formal or non-formal education, but excluding informal learning.\n\n\n\n\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). \n\n\n\n\n\n\n\nPersons are considered to be in training if they are in a nonacademic learning activity through which they acquire specific skills intended for vocational or technical jobs. Vocational training prepares trainees for jobs that are based on manual or practical activities, and for skilled operative jobs, both blue and white collar related to a specific trade, occupation or vocation. Technical training on the other hand imparts learning that can be applied in intermediate-level jobs, in particular those of technicians and middle managers. The coverage of vocational and technical training includes only programmes that are solely school-based vocational and technical training. Employer-based training is, by definition, excluded from the scope of this indicator.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.NEET.FE.ME.ZS","name":"Proportion de femmes parmi les jeunes qui ne sont ni scolarisés, ni en emploi, ni en formation ( % de la population féminine jeune) (estimation modélisée de l'OIT)","description":"La part des jeunes ne suivant pas d’études, d’emploi ou de formation (également connue sous le nom de « taux NEET ») indique le nombre de jeunes ne...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.NEET.FE.ME.ZS?locations=CI","methodology":"Methodology: The youth NEET rate is calculated as follows: NEET rate = (Youth – Youth in employment – Youth not in employment but in education or training) / Youth x 100.  \n\nIt is important to note here that youth both in employment and education or training simultaneously should not be double counted when subtracted from the total number of youth. The formula can also be expressed as: NEET rate =  [(Unemployed youth + Youth outside the labor force) – (Unemployed youth in education or training + Youth outside the labor force in education or training)]  / Youth x 100. \n\nThe calculation of this indicator requires having reliable information on both the labor market status and the participation in education or training of youth. The quality of such information is heavily dependent on the questionnaire design, the sample size and design and the accuracy of respondents' answers. To avoid misinterpreting this indicator, it is important to bear in mind that it is composed of two different sub-groups (unemployed youth not in education or training and youth outside the labor force not in education or training). The prevalence and composition of each sub-group would have policy implications, and thus should also be considered when analyzing the NEET rate.\n\nThe preferred official national data source for this indicator is a household-based labor force survey. In the absence of a labor force survey, a population census and/or other type of household survey with an appropriate employment module may be used to obtain the required data.\nStatistical concept(s): For the purposes of these indicators, persons will be considered in education if they are in formal or non-formal education, but excluding informal learning.\n\n\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). \n\n\n\n\n\nPersons are considered to be in training if they are in a nonacademic learning activity through which they acquire specific skills intended for vocational or technical jobs. Vocational training prepares trainees for jobs that are based on manual or practical activities, and for skilled operative jobs, both blue and white collar related to a specific trade, occupation or vocation. Technical training on the other hand imparts learning that can be applied in intermediate-level jobs, in particular those of technicians and middle managers. The coverage of vocational and technical training includes only programmes that are solely school-based vocational and technical training. Employer-based training is, by definition, excluded from the scope of this indicator.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.NEET.MA.ZS","name":"Proportion de jeunes sans études, ni emploi, ni formation (en % de la population masculine)","description":"La part des jeunes ne suivant pas d’études, d’emploi ou de formation (également connue sous le nom de « taux NEET ») indique le nombre de jeunes ne...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.NEET.MA.ZS?locations=CI","methodology":"Methodology: The youth NEET rate is calculated as follows: NEET rate = (Youth – Youth in employment – Youth not in employment but in education or training) / Youth x 100.  \n\nIt is important to note here that youth both in employment and education or training simultaneously should not be double counted when subtracted from the total number of youth. The formula can also be expressed as: NEET rate =  [(Unemployed youth + Youth outside the labor force) – (Unemployed youth in education or training + Youth outside the labor force in education or training)]  / Youth x 100. \n\nThe calculation of this indicator requires having reliable information on both the labor market status and the participation in education or training of youth. The quality of such information is heavily dependent on the questionnaire design, the sample size and design and the accuracy of respondents' answers. To avoid misinterpreting this indicator, it is important to bear in mind that it is composed of two different sub-groups (unemployed youth not in education or training and youth outside the labor force not in education or training). The prevalence and composition of each sub-group would have policy implications, and thus should also be considered when analyzing the NEET rate.\n\nThe preferred official national data source for this indicator is a household-based labor force survey. In the absence of a labor force survey, a population census and/or other type of household survey with an appropriate employment module may be used to obtain the required data.\nStatistical concept(s): For the purposes of these indicators, persons will be considered in education if they are in formal or non-formal education, but excluding informal learning.\n\n\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). \n\n\n\n\n\nPersons are considered to be in training if they are in a nonacademic learning activity through which they acquire specific skills intended for vocational or technical jobs. Vocational training prepares trainees for jobs that are based on manual or practical activities, and for skilled operative jobs, both blue and white collar related to a specific trade, occupation or vocation. Technical training on the other hand imparts learning that can be applied in intermediate-level jobs, in particular those of technicians and middle managers. The coverage of vocational and technical training includes only programmes that are solely school-based vocational and technical training. Employer-based training is, by definition, excluded from the scope of this indicator.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.NEET.MA.ME.ZS","name":"Proportion de jeunes non scolarisés, sans emploi ou en formation, hommes ( % de la population masculine) (estimation modélisée de l'OIT)","description":"La part des jeunes ne suivant pas d’études, d’emploi ou de formation (également connue sous le nom de « taux NEET ») indique le nombre de jeunes ne...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.NEET.MA.ME.ZS?locations=CI","methodology":"Methodology: The youth NEET rate is calculated as follows: NEET rate = (Youth – Youth in employment – Youth not in employment but in education or training) / Youth x 100.  \n\nIt is important to note here that youth both in employment and education or training simultaneously should not be double counted when subtracted from the total number of youth. The formula can also be expressed as: NEET rate =  [(Unemployed youth + Youth outside the labor force) – (Unemployed youth in education or training + Youth outside the labor force in education or training)]  / Youth x 100. \n\nThe calculation of this indicator requires having reliable information on both the labor market status and the participation in education or training of youth. The quality of such information is heavily dependent on the questionnaire design, the sample size and design and the accuracy of respondents' answers. To avoid misinterpreting this indicator, it is important to bear in mind that it is composed of two different sub-groups (unemployed youth not in education or training and youth outside the labor force not in education or training). The prevalence and composition of each sub-group would have policy implications, and thus should also be considered when analyzing the NEET rate.\n\nThe preferred official national data source for this indicator is a household-based labor force survey. In the absence of a labor force survey, a population census and/or other type of household survey with an appropriate employment module may be used to obtain the required data.\nStatistical concept(s): For the purposes of these indicators, persons will be considered in education if they are in formal or non-formal education, but excluding informal learning.\n\n\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). \n\n\n\n\n\nPersons are considered to be in training if they are in a nonacademic learning activity through which they acquire specific skills intended for vocational or technical jobs. Vocational training prepares trainees for jobs that are based on manual or practical activities, and for skilled operative jobs, both blue and white collar related to a specific trade, occupation or vocation. Technical training on the other hand imparts learning that can be applied in intermediate-level jobs, in particular those of technicians and middle managers. The coverage of vocational and technical training includes only programmes that are solely school-based vocational and technical training. Employer-based training is, by definition, excluded from the scope of this indicator.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.NEET.ZS","name":"Proportion de jeunes sans études, ni emploi, ni formation (en % de la population jeune)","description":"La part des jeunes ne suivant pas d’études, d’emploi ou de formation (également connue sous le nom de « taux NEET ») indique le nombre de jeunes ne...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.NEET.ZS?locations=CI","methodology":"Methodology: The youth NEET rate is calculated as follows: NEET rate = (Youth – Youth in employment – Youth not in employment but in education or training) / Youth x 100.  \n\nIt is important to note here that youth both in employment and education or training simultaneously should not be double counted when subtracted from the total number of youth. The formula can also be expressed as: NEET rate =  [(Unemployed youth + Youth outside the labor force) – (Unemployed youth in education or training + Youth outside the labor force in education or training)]  / Youth x 100. \n\nThe calculation of this indicator requires having reliable information on both the labor market status and the participation in education or training of youth. The quality of such information is heavily dependent on the questionnaire design, the sample size and design and the accuracy of respondents' answers. To avoid misinterpreting this indicator, it is important to bear in mind that it is composed of two different sub-groups (unemployed youth not in education or training and youth outside the labor force not in education or training). The prevalence and composition of each sub-group would have policy implications, and thus should also be considered when analyzing the NEET rate.\n\nThe preferred official national data source for this indicator is a household-based labor force survey. In the absence of a labor force survey, a population census and/or other type of household survey with an appropriate employment module may be used to obtain the required data.\nStatistical concept(s): For the purposes of these indicators, persons will be considered in education if they are in formal or non-formal education, but excluding informal learning.\n\n\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). \n\n\n\n\n\nPersons are considered to be in training if they are in a nonacademic learning activity through which they acquire specific skills intended for vocational or technical jobs. Vocational training prepares trainees for jobs that are based on manual or practical activities, and for skilled operative jobs, both blue and white collar related to a specific trade, occupation or vocation. Technical training on the other hand imparts learning that can be applied in intermediate-level jobs, in particular those of technicians and middle managers. The coverage of vocational and technical training includes only programmes that are solely school-based vocational and technical training. Employer-based training is, by definition, excluded from the scope of this indicator.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.NEET.ME.ZS","name":"Part des jeunes qui ne sont ni scolarisés, ni en emploi, ni en formation (en % de la population jeune) (estimation modélisée de l'OIT)","description":"La part des jeunes ne suivant pas d’études, d’emploi ou de formation (également connue sous le nom de « taux NEET ») indique le nombre de jeunes ne...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.NEET.ME.ZS?locations=CI","methodology":"Methodology: The youth NEET rate is calculated as follows: NEET rate = (Youth – Youth in employment – Youth not in employment but in education or training) / Youth x 100.  \n\nIt is important to note here that youth both in employment and education or training simultaneously should not be double counted when subtracted from the total number of youth. The formula can also be expressed as: NEET rate =  [(Unemployed youth + Youth outside the labor force) – (Unemployed youth in education or training + Youth outside the labor force in education or training)]  / Youth x 100. \n\nThe calculation of this indicator requires having reliable information on both the labor market status and the participation in education or training of youth. The quality of such information is heavily dependent on the questionnaire design, the sample size and design and the accuracy of respondents' answers. To avoid misinterpreting this indicator, it is important to bear in mind that it is composed of two different sub-groups (unemployed youth not in education or training and youth outside the labor force not in education or training). The prevalence and composition of each sub-group would have policy implications, and thus should also be considered when analyzing the NEET rate.\n\n\n\n\n\n\n\nThe preferred official national data source for this indicator is a household-based labor force survey. In the absence of a labor force survey, a population census and/or other type of household survey with an appropriate employment module may be used to obtain the required data.\nStatistical concept(s): For the purposes of these indicators, persons will be considered in education if they are in formal or non-formal education, but excluding informal learning.\n\n\n\n\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). \n\n\n\n\n\n\n\nPersons are considered to be in training if they are in a nonacademic learning activity through which they acquire specific skills intended for vocational or technical jobs. Vocational training prepares trainees for jobs that are based on manual or practical activities, and for skilled operative jobs, both blue and white collar related to a specific trade, occupation or vocation. Technical training on the other hand imparts learning that can be applied in intermediate-level jobs, in particular those of technicians and middle managers. The coverage of vocational and technical training includes only programmes that are solely school-based vocational and technical training. Employer-based training is, by definition, excluded from the scope of this indicator.","theme":"emploi","source_group":"wb"},{"code":"DT.DOD.DSTC.XP.ZS","name":"Dette à court terme ( % des exportations de biens, de services et de revenus primaires)","description":"La dette extérieure à court terme est définie comme une dette dont l’échéance initiale est d’un an ou moins.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.DSTC.XP.ZS?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value. \n\nThe data is presented as a percentage of \"Exports of goods, services and primary income (BoP, current US$)\" (BX.GSR.TOTL.CD), sourced from the International Monetary Fund's Balance of Payments Statistics Yearbook and data files.","theme":"finance","source_group":"wb"},{"code":"DT.DOD.DSTC.ZS","name":"Dette à court terme ( % de la dette extérieure totale)","description":"La dette à court terme comprend toutes les dettes ayant une échéance initiale d'un an ou moins ainsi que les intérêts de retard sur la dette à long...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.DSTC.ZS?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.DOD.DSTC.IR.ZS","name":"Dette à court terme ( % du total des réserves)","description":"La dette à court terme comprend toutes les dettes ayant une échéance initiale d'un an ou moins ainsi que les intérêts de retard sur la dette à long...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.DSTC.IR.ZS?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"GC.REV.SOCL.ZS","name":"Cotisations sociales ( % des recettes)","description":"Les cotisations sociales sont des cotisations réelles ou fictives payables aux régimes d'assurance sociale pour\n\n\nprévoir le versement de prestatio...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.REV.SOCL.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.REV.SOCL.CN","name":"Cotisations sociales (LCU actuelles)","description":"Les cotisations sociales sont des cotisations réelles ou fictives payables aux régimes d'assurance sociale pour\n\n\nprévoir le versement de prestatio...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.REV.SOCL.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"SH.MED.SAOP.P5","name":"Main-d'œuvre chirurgicale spécialisée (pour 100 000 habitants)","description":"Le personnel chirurgical spécialisé correspond au nombre de prestataires spécialisés en chirurgie, anesthésie et obstétrique (SAO) qui travaillent ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.MED.SAOP.P5?locations=CI","methodology":"Methodology: The number of specialist surgical, anaesthetic, and obstetric (SAO) providers who are working in each country per 100 000 population.\nStatistical concept(s): The Lancet Commission on Global Surgery, assembled in 2013 to assess surgical care around the world. Commissioners engaged in an iterative global consultative process with partners in over 110 countries to develop six core indicators of the strength of a surgical system. Two indicators assess a country’s preparedness to deliver safe surgery and anesthesia,  two assess the current delivery of safe care, and two assess the state of financial risk protection for those seeking surgery.","theme":"sante","source_group":"wb"},{"code":"IQ.SPI.OVRL","name":"Indicateurs statistiques de performance (IPS) : Note globale (échelle de 0 à 100)","description":"Le score global SPI est un score composite mesurant la performance du pays sur cinq piliers : utilisation des données, services de données, produit...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.SPI.OVRL?locations=CI","methodology":"Methodology: Weighted average of all statistical performance indicators.  Scores range from 0-100 with 100 representing the best score.\nStatistical concept(s): Composite Multi-dimensional Index","theme":"politique","source_group":"wb"},{"code":"IQ.SPI.PIL1","name":"Indicateurs statistiques de performance (IPS) : score d'utilisation des données du pilier 1 (échelle de 0 à 100)","description":"Le score global d’utilisation des données est un score composite mesurant l’aspect demande du système statistique.","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.SPI.PIL1?locations=CI","methodology":"Methodology: Weighted average of statistical performance indicators related to data use.  Scores range from 0-100 with 100 representing the best score.\nStatistical concept(s): Composite Multi-dimensional Index","theme":"politique","source_group":"wb"},{"code":"IQ.SPI.PIL2","name":"Indicateurs statistiques de performance (IPS) : score des services de données du pilier 2 (échelle de 0 à 100)","description":"La note globale du pilier Services de données est un indicateur composite basé sur quatre dimensions des services de données : (i) la qualité des p...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.SPI.PIL2?locations=CI","methodology":"Methodology: Weighted average of statistical performance indicators related to data services.  Scores range from 0-100 with 100 representing the best score.\nStatistical concept(s): Composite Multi-dimensional Index","theme":"politique","source_group":"wb"},{"code":"IQ.SPI.PIL3","name":"Indicateurs statistiques de performance (IPS) : score des produits de données du pilier 3 (échelle de 0 à 100)","description":"Le score global des produits de données est un score composite mesurant si le pays est capable de produire des indicateurs pertinents, principaleme...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.SPI.PIL3?locations=CI","methodology":"Methodology: Weighted average of statistical performance indicators related to data products.  Scores range from 0-100 with 100 representing the best score.\nStatistical concept(s): Composite Multi-dimensional Index","theme":"politique","source_group":"wb"},{"code":"IQ.SPI.PIL4","name":"Indicateurs statistiques de performance (IPS) : score des sources de données du pilier 4 (échelle de 0 à 100)","description":"Le score global des sources de données est une mesure de composition indiquant si les pays disposent de données provenant des sources suivantes : r...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.SPI.PIL4?locations=CI","methodology":"Methodology: Weighted average of statistical performance indicators related to data sources.  Scores range from 0-100 with 100 representing the best score.\nStatistical concept(s): Composite Multi-dimensional Index","theme":"politique","source_group":"wb"},{"code":"IQ.SPI.PIL5","name":"Indicateurs statistiques de performance (IPS) : score de l'infrastructure de données du pilier 5 (échelle de 0 à 100)","description":"Le score global du pilier infrastructure de données mesure les segments des infrastructures matérielles et logicielles, énumérant les exigences tra...","source_link":"https://donnees.banquemondiale.org/indicateur/IQ.SPI.PIL5?locations=CI","methodology":"Methodology: Weighted average of statistical performance indicators related to data infrastructure.  Scores range from 0-100 with 100 representing the best score.\nStatistical concept(s): Composite Multi-dimensional Index","theme":"politique","source_group":"wb"},{"code":"CM.MKT.TRAD.GD.ZS","name":"Actions échangées, valeur totale ( % du PIB)","description":"La valeur des actions négociées correspond au nombre total d'actions négociées, tant nationales qu'étrangères, multiplié par leurs prix corresponda...","source_link":"https://donnees.banquemondiale.org/indicateur/CM.MKT.TRAD.GD.ZS?locations=CI","methodology":"Methodology: The value of shares traded represent the transfer of ownership effected automatically through the exchange's electronic order book (EOB), where orders placed by trading members are usually exposed to all market users and automatically matched according to precise rules set up by the exchange, generally on a price/time priority basis. For data before 2001, the WFE used two different approaches for the collection of trading data, depending on the individual stock exchange's market organization and rules. The first approach is the Trading System View (TSV). Stock exchanges adopting this view count only those transactions which pass through their trading system or trading floor. The TSV is generally adopted by exchanges which operate a centralized order book (order-driven market). Trades done by their members off the exchange are not included. The second approach is the Regulated Environment View (REV). Stock exchanges in this category include all transactions subject to supervision by the market authority, including transactions made by members, and sometimes non-members, on outside trading systems and transactions into foreign markets. Figures reported under the REV approach will be higher than those reported under the TSV approach.\nStatistical concept(s): The value of shares traded represent the transfer of ownership effected automatically through the exchange's electronic order book (EOB), where orders placed by trading members are usually exposed to all market users and automatically matched according to precise rules set up by the exchange, generally on a price/time priority basis. For data before 2001, the WFE used two different approaches for the collection of trading data, depending on the individual stock exchange's market organization and rules. The first approach is the Trading System View (TSV). Stock exchanges adopting this view count only those transactions which pass through their trading system or trading floor. The TSV is generally adopted by exchanges which operate a centralized order book (order-driven market). Trades done by their members off the exchange are not included. The second approach is the Regulated Environment View (REV). Stock exchanges in this category include all transactions subject to supervision by the market authority, including transactions made by members, and sometimes non-members, on outside trading systems and transactions into foreign markets. Figures reported under the REV approach will be higher than those reported under the TSV approach.","theme":"business","source_group":"wb"},{"code":"CM.MKT.TRAD.CD","name":"Actions négociées, valeur totale ($ US courants)","description":"La valeur des actions négociées correspond au nombre total d'actions négociées, tant nationales qu'étrangères, multiplié par leurs prix corresponda...","source_link":"https://donnees.banquemondiale.org/indicateur/CM.MKT.TRAD.CD?locations=CI","methodology":"Methodology: The value of shares traded represent the transfer of ownership effected automatically through the exchange's electronic order book (EOB), where orders placed by trading members are usually exposed to all market users and automatically matched according to precise rules set up by the exchange, generally on a price/time priority basis. For data before 2001, the WFE used two different approaches for the collection of trading data, depending on the individual stock exchange's market organization and rules. The first approach is the Trading System View (TSV). Stock exchanges adopting this view count only those transactions which pass through their trading system or trading floor. The TSV is generally adopted by exchanges which operate a centralized order book (order-driven market). Trades done by their members off the exchange are not included. The second approach is the Regulated Environment View (REV). Stock exchanges in this category include all transactions subject to supervision by the market authority, including transactions made by members, and sometimes non-members, on outside trading systems and transactions into foreign markets. Figures reported under the REV approach will be higher than those reported under the TSV approach.\nStatistical concept(s):  The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates. The value of shares traded represent the transfer of ownership effected automatically through the exchange's electronic order book (EOB), where orders placed by trading members are usually exposed to all market users and automatically matched according to precise rules set up by the exchange, generally on a price/time priority basis. https://data.worldbank.org/indicator/CM.MKT.TRAD.CD","theme":"business","source_group":"wb"},{"code":"CM.MKT.TRNR","name":"Actions échangées, taux de rotation des actions nationales ( %)","description":"Le ratio de rotation est la valeur des actions nationales négociées divisée par leur capitalisation boursière.","source_link":"https://donnees.banquemondiale.org/indicateur/CM.MKT.TRNR?locations=CI","methodology":"Methodology: Turnover ratio is the value of electronic order book (EOB) domestic shares traded divided by their market capitalization. The value is annualized by multiplying the monthly average by 12, according to the following formula: (Monthly EOB domestic shares traded / Month-end domestic market capitalization) x 12.\nStatistical concept(s): Statistical Concept and Methodology: Turnover ratio is the value of electronic order book (EOB) domestic shares traded divided by their market capitalization. The value is annualized by multiplying the monthly average by 12, according to the following formula: (Monthly EOB domestic shares traded / Month-end domestic market capitalization) x 12.","theme":"business","source_group":"wb"},{"code":"GC.XPN.TRFT.ZS","name":"Subventions et autres transferts ( % de la dépense)","description":"Les subventions sont des paiements courants sans contrepartie que les unités gouvernementales, y compris les unités gouvernementales non résidentes...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.TRFT.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.XPN.TRFT.CN","name":"Subventions et autres transferts (LCU courante)","description":"Les subventions sont des paiements courants sans contrepartie que les unités gouvernementales, y compris les unités gouvernementales non résidentes...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.XPN.TRFT.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"SH.STA.SUIC.P5","name":"Taux de mortalité par suicide (pour 100 000 habitants)","description":"Le taux de mortalité par suicide correspond au nombre de décès par suicide sur une année pour 100 000 habitants.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.SUIC.P5?locations=CI","methodology":"Methodology: It is calculated by dividing the number of suicide deaths in a year by the mid-year population for the same calendar year, then multiplying by 100,000. The estimates are derived from the WHO Global Health Estimates (GHE). For countries with high-quality vital registration systems that include information on cause of death, the vital registration data submitted by member states to the WHO Mortality Database are used, with adjustments made where necessary (e.g., for under-reporting of deaths, unknown age and sex, and ill-defined causes of death). For countries without high-quality death registration data, cause of death estimates are calculated using other sources, including household surveys with verbal autopsy, sample or sentinel registration systems, and special studies. These estimates represent WHO's best calculations, using standard categories, definitions, and methods to ensure cross-country comparability. They may not be identical to official national estimates.","theme":"sante","source_group":"wb"},{"code":"SH.STA.SUIC.FE.P5","name":"Taux de mortalité par suicide, femmes (pour 100 000 femmes)","description":"Le taux de mortalité par suicide correspond au nombre de décès par suicide sur une année pour 100 000 habitants.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.SUIC.FE.P5?locations=CI","methodology":"Methodology: It is calculated by dividing the number of suicide deaths in a year by the mid-year population for the same calendar year, then multiplying by 100,000. The estimates are derived from the WHO Global Health Estimates (GHE). For countries with high-quality vital registration systems that include information on cause of death, the vital registration data submitted by member states to the WHO Mortality Database are used, with adjustments made where necessary (e.g., for under-reporting of deaths, unknown age and sex, and ill-defined causes of death). For countries without high-quality death registration data, cause of death estimates are calculated using other sources, including household surveys with verbal autopsy, sample or sentinel registration systems, and special studies. These estimates represent WHO's best calculations, using standard categories, definitions, and methods to ensure cross-country comparability. They may not be identical to official national estimates.","theme":"sante","source_group":"wb"},{"code":"SH.STA.SUIC.MA.P5","name":"Taux de mortalité par suicide, hommes (pour 100 000 hommes)","description":"Le taux de mortalité par suicide correspond au nombre de décès par suicide sur une année pour 100 000 habitants.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.STA.SUIC.MA.P5?locations=CI","methodology":"Methodology: It is calculated by dividing the number of suicide deaths in a year by the mid-year population for the same calendar year, then multiplying by 100,000. The estimates are derived from the WHO Global Health Estimates (GHE). For countries with high-quality vital registration systems that include information on cause of death, the vital registration data submitted by member states to the WHO Mortality Database are used, with adjustments made where necessary (e.g., for under-reporting of deaths, unknown age and sex, and ill-defined causes of death). For countries without high-quality death registration data, cause of death estimates are calculated using other sources, including household surveys with verbal autopsy, sample or sentinel registration systems, and special studies. These estimates represent WHO's best calculations, using standard categories, definitions, and methods to ensure cross-country comparability. They may not be identical to official national estimates.","theme":"sante","source_group":"wb"},{"code":"AG.SRF.TOTL.K2","name":"Superficie (km²)","description":"La superficie est la superficie totale d'un pays, y compris les zones situées sous les plans d'eau intérieurs et certaines voies navigables côtières.","source_link":"https://donnees.banquemondiale.org/indicateur/AG.SRF.TOTL.K2?locations=CI","methodology":"Methodology: Total land area includes inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area. Including areas of former states; for example, the areas of the Union of Soviet Socialist Republics (USSR) are counted in Russian Federationand other successor states.","theme":"primary","source_group":"wb"},{"code":"SI.SPR.PC40","name":"Consommation moyenne ou revenu par habitant de l'enquête, 40 % inférieurs de la population (2021 PPA $ par jour)","description":"Consommation moyenne ou revenu par habitant (2021 PPA $ par jour) des 40 % les plus pauvres, utilisé pour calculer le taux de croissance de l'agrég...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.SPR.PC40?locations=CI","methodology":"Methodology: Survey mean consumption or income per capita, bottom 40% of population measures the amount of consumption or income per person per day in the bottom 40% of the population. It is estimated from survey data and expressed in 2021 PPP dollars.\nStatistical concept(s): Survey mean consumption or income per capita, bottom 40% of population measures the amount of consumption or income per person per day in the bottom 40% of the population. It is estimated from survey data and expressed in 2021 PPP dollars.","theme":"social","source_group":"wb"},{"code":"SI.SPR.PCAP","name":"Consommation moyenne ou revenu par habitant de l'enquête, population totale ($ PPA de 2021 par jour)","description":"Consommation moyenne ou revenu par habitant ($ PPA 2021 par jour) utilisé pour calculer le taux de croissance de l'agrégat de bien-être de la popul...","source_link":"https://donnees.banquemondiale.org/indicateur/SI.SPR.PCAP?locations=CI","methodology":"Methodology: The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. \nStatistical concept(s): Survey mean consumption or income per capita, total population measures the amount of consumption or income per person per day in the population. It is estimated from survey data and expressed in 2021 PPP dollars.","theme":"social","source_group":"wb"},{"code":"SP.DYN.TO65.FE.ZS","name":"Survie jusqu'à 65 ans, femmes ( % de la cohorte)","description":"La survie jusqu'à 65 ans fait référence au pourcentage d'une cohorte de nouveau-nés qui survivraient jusqu'à 65 ans, s'ils étaient soumis aux taux ...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.TO65.FE.ZS?locations=CI","methodology":"Methodology: The indicator is calculated using number of survivors, l(x), at exact age x in a female period life table. The formula is: (l(65))/(l(0))*100.\nStatistical concept(s): Survival to age 65 is calculated in a period life table. It provides a population's mortality level up to age 65 at a given time. It therefore does not reflect the mortality level that a person actually experiences during his/her life, which can be calculated in a cohort life table.","theme":"sante","source_group":"wb"},{"code":"SP.DYN.TO65.MA.ZS","name":"Survie jusqu'à 65 ans, hommes ( % de la cohorte)","description":"La survie jusqu'à 65 ans fait référence au pourcentage d'une cohorte de nouveau-nés qui survivraient jusqu'à 65 ans, s'ils étaient soumis aux taux ...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.TO65.MA.ZS?locations=CI","methodology":"Methodology: The indicator is calculated using number of survivors l(x) at exact age x, in a male period life table. The formula is: (l(65))/(l(0))*100.\nStatistical concept(s): Survival to age 65 is calculated in a period life table. It provides a population's mortality level up to age 65 at a given time. It therefore does not reflect the mortality level that a person actually experiences during his/her life, which can be calculated in a cohort life table.","theme":"sante","source_group":"wb"},{"code":"TM.TAX.MRCH.SM.AR.ZS","name":"Taux de droits appliqués, moyenne simple, tous les produits ( %)","description":"La moyenne simple des droits appliqués est la moyenne non pondérée des taux effectivement appliqués pour tous les produits soumis à des droits calc...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.MRCH.SM.AR.ZS?locations=CI","methodology":"Methodology: This indicator represents the simple (unweighted) average of applied most-favored-nation (MFN) tariff rates across all tariff lines within the all products category. Each line is given equal weight regardless of the trade volume associated with it. The mean is calculated by summing the applied rates and dividing by the number of lines. Simple mean applied tariff is the unweighted average of effectively applied rates for all products subject to tariffs calculated for all traded goods. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of simple mean tariffs. Tariff data are primarily sourced from the World Trade Organization (World Trade Organization (WTO)) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. The indicator excludes missing or unreported lines. Harmonization across HS revisions is conducted to ensure international comparability, and no adjustments are made beyond validation of submitted data.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.MANF.SM.AR.ZS","name":"Taux de droits appliqués, moyenne simple, produits manufacturés ( %)","description":"La moyenne simple des droits appliqués est la moyenne non pondérée des taux effectivement appliqués pour tous les produits soumis à des droits calc...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.MANF.SM.AR.ZS?locations=CI","methodology":"Methodology: This indicator represents the simple (unweighted) average of applied most-favored-nation (MFN) tariff rates across all tariff lines within the manufactured products category. Each line is given equal weight regardless of the trade volume associated with it. The mean is calculated by summing the applied rates and dividing by the number of lines. Simple mean applied tariff is the unweighted average of effectively applied rates for all products subject to tariffs calculated for all traded goods. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of simple mean tariffs. Manufactured products are commodities classified in SITC revision 3 sections 5-8 excluding division 68. Tariff data are primarily sourced from the World Trade Organization (World Trade Organization (WTO)) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. The indicator excludes missing or unreported lines. Harmonization across HS revisions is conducted to ensure international comparability, and no adjustments are made beyond validation of submitted data.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.TCOM.SM.AR.ZS","name":"Taux de droits appliqués, moyenne simple, produits primaires ( %)","description":"La moyenne simple des droits appliqués est la moyenne non pondérée des taux effectivement appliqués pour tous les produits soumis à des droits calc...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.TCOM.SM.AR.ZS?locations=CI","methodology":"Methodology: This indicator represents the simple (unweighted) average of applied most-favored-nation (MFN) tariff rates across all tariff lines within the primary products category. Each line is given equal weight regardless of the trade volume associated with it. The mean is calculated by summing the applied rates and dividing by the number of lines. Simple mean applied tariff is the unweighted average of effectively applied rates for all products subject to tariffs calculated for all traded goods. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of simple mean tariffs. Primary products are commodities classified in SITC revision 3 sections 0-4 plus division 68 (nonferrous metals). Tariff data are primarily sourced from the World Trade Organization (World Trade Organization (WTO)) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. The indicator excludes missing or unreported lines. Harmonization across HS revisions is conducted to ensure international comparability, and no adjustments are made beyond validation of submitted data.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.MRCH.WM.AR.ZS","name":"Taux de droits appliqués, moyenne pondérée, tous produits ( %)","description":"Le droit moyen pondéré appliqué est la moyenne des taux effectivement appliqués pondérée par les parts d’importation de produits correspondant à ch...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.MRCH.WM.AR.ZS?locations=CI","methodology":"Methodology: This indicator computes the average of applied most-favored-nation (MFN) tariff rates for all products, using import values as weights. Tariff lines with higher trade volumes have a proportionally greater influence on the final average. The weighted mean is derived by multiplying each tariff rate by its corresponding import value, summing these products, and dividing by the total import value. Weighted mean applied tariff is the average of effectively applied rates weighted by the product import shares corresponding to each partner country. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups and import weights. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of weighted mean tariffs. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead. Tariff data are primarily sourced from the World Trade Organization (World Trade Organization (WTO)) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. Trade data used for weighting are obtained from official national or international sources. Only lines with both valid tariff rates and trade values are included. Harmonized classifications are used to align trade and tariff data consistently.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.MANF.WM.AR.ZS","name":"Taux de droits appliqués, moyenne pondérée, produits manufacturés ( %)","description":"Le droit moyen pondéré appliqué est la moyenne des taux effectivement appliqués pondérée par les parts d’importation de produits correspondant à ch...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.MANF.WM.AR.ZS?locations=CI","methodology":"Methodology: This indicator computes the average of applied most-favored-nation (MFN) tariff rates for manufactured products, using import values as weights. Tariff lines with higher trade volumes have a proportionally greater influence on the final average. The weighted mean is derived by multiplying each tariff rate by its corresponding import value, summing these products, and dividing by the total import value. Weighted mean applied tariff is the average of effectively applied rates weighted by the product import shares corresponding to each partner country. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups and import weights. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of weighted mean tariffs. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead. Manufactured products are commodities classified in SITC revision 3 sections 5-8 excluding division 68. Tariff data are primarily sourced from the World Trade Organization (World Trade Organization (WTO)) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. Trade data used for weighting are obtained from official national or international sources. Only lines with both valid tariff rates and trade values are included. Harmonized classifications are used to align trade and tariff data consistently.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.TCOM.WM.AR.ZS","name":"Taux de droits appliqués, moyenne pondérée, produits primaires ( %)","description":"Le droit moyen pondéré appliqué est la moyenne des taux effectivement appliqués pondérée par les parts d’importation de produits correspondant à ch...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.TCOM.WM.AR.ZS?locations=CI","methodology":"Methodology: This indicator computes the average of applied most-favored-nation (MFN) tariff rates for primary products, using import values as weights. Tariff lines with higher trade volumes have a proportionally greater influence on the final average. The weighted mean is derived by multiplying each tariff rate by its corresponding import value, summing these products, and dividing by the total import value. Weighted mean applied tariff is the average of effectively applied rates weighted by the product import shares corresponding to each partner country. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups and import weights. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of weighted mean tariffs. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead. Primary products are commodities classified in SITC revision 3 sections 0-4 plus division 68 (nonferrous metals). Tariff data are primarily sourced from the World Trade Organization (World Trade Organization (WTO)) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. Trade data used for weighting are obtained from official national or international sources. Only lines with both valid tariff rates and trade values are included. Harmonized classifications are used to align trade and tariff data consistently.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.MRCH.SM.FN.ZS","name":"Taux de droits, nation la plus favorisée, moyenne simple, tous les produits ( %)","description":"Le taux de droit moyen simple de la nation la plus favorisée est la moyenne non pondérée des taux de la nation la plus favorisée pour tous les prod...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.MRCH.SM.FN.ZS?locations=CI","methodology":"Methodology: This indicator calculates the simple (unweighted) mean of statutory most-favored-nation (MFN) tariff rates across all tariff lines for all products. It reflects tariff rates that apply to all World Trade Organization (WTO) members on a non-discriminatory basis unless preferential agreements are in force. Simple mean most favored nation tariff rate is the unweighted average of most favored nation rates for all products subject to tariffs calculated for all traded goods. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups. Tariff data are primarily sourced from the World Trade Organization (WTO) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. The calculation is performed by summing the MFN rates and dividing by the total number of tariff lines. No trade-based weighting is applied. Only reported rates are included, and harmonized classifications ensure comparability across countries.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.MANF.SM.FN.ZS","name":"Taux de droits, nation la plus favorisée, moyenne simple, produits manufacturés ( %)","description":"Le taux de droit moyen simple de la nation la plus favorisée est la moyenne non pondérée des taux de la nation la plus favorisée pour tous les prod...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.MANF.SM.FN.ZS?locations=CI","methodology":"Methodology: This indicator calculates the simple (unweighted) mean of statutory most-favored-nation (MFN) tariff rates across all tariff lines for manufactured products. It reflects tariff rates that apply to all World Trade Organization (WTO) members on a non-discriminatory basis unless preferential agreements are in force. Simple mean most favored nation tariff rate is the unweighted average of most favored nation rates for all products subject to tariffs calculated for all traded goods. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups. Manufactured products are commodities classified in SITC revision 3 sections 5-8 excluding division 68. Tariff data are primarily sourced from the World Trade Organization (WTO) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. The calculation is performed by summing the MFN rates and dividing by the total number of tariff lines. No trade-based weighting is applied. Only reported rates are included, and harmonized classifications ensure comparability across countries.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.TCOM.SM.FN.ZS","name":"Taux de droits, nation la plus favorisée, moyenne simple, produits primaires ( %)","description":"Le taux de droit moyen simple de la nation la plus favorisée est la moyenne non pondérée des taux de la nation la plus favorisée pour tous les prod...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.TCOM.SM.FN.ZS?locations=CI","methodology":"Methodology: This indicator calculates the simple (unweighted) mean of statutory most-favored-nation (MFN) tariff rates across all tariff lines for primary products. It reflects tariff rates that apply to all World Trade Organization (WTO) members on a non-discriminatory basis unless preferential agreements are in force. Simple mean most favored nation tariff rate is the unweighted average of most favored nation rates for all products subject to tariffs calculated for all traded goods. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups. Primary products are commodities classified in SITC revision 3 sections 0-4 plus division 68 (nonferrous metals). Tariff data are primarily sourced from the World Trade Organization (WTO) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. The calculation is performed by summing the MFN rates and dividing by the total number of tariff lines. No trade-based weighting is applied. Only reported rates are included, and harmonized classifications ensure comparability across countries.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.MRCH.WM.FN.ZS","name":"Taux de droits, nation la plus favorisée, moyenne pondérée, tous les produits ( %)","description":"Le tarif moyen pondéré de la nation la plus favorisée est la moyenne des taux de la nation la plus favorisée pondérée par les parts d'importation d...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.MRCH.WM.FN.ZS?locations=CI","methodology":"Methodology: This indicator represents the trade-weighted average of most-favored-nation (MFN) tariff rates across all all products tariff lines. Import values are used to weight each rate, reflecting the relative economic significance of different products in international trade. The weighted average is calculated by taking the sum of the products of MFN rates and import values, divided by the total import value. Weighted mean most favored nations tariff is the average of most favored nation rates weighted by the product import shares corresponding to each partner country. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups and import weights. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database. Tariff data are primarily sourced from the World Trade Organization (World Trade Organization (WTO)) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. Only tariff lines with both reported MFN rates and corresponding trade values are included. The WTO applies standardized concordance procedures to match trade and tariff data using harmonized product classifications.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.MANF.WM.FN.ZS","name":"Taux de droits, nation la plus favorisée, moyenne pondérée, produits manufacturés ( %)","description":"Le tarif moyen pondéré de la nation la plus favorisée est la moyenne des taux de la nation la plus favorisée pondérée par les parts d'importation d...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.MANF.WM.FN.ZS?locations=CI","methodology":"Methodology: This indicator represents the trade-weighted average of most-favored-nation (MFN) tariff rates across all manufactured products tariff lines. Import values are used to weight each rate, reflecting the relative economic significance of different products in international trade. The weighted average is calculated by taking the sum of the products of MFN rates and import values, divided by the total import value. Weighted mean most favored nations tariff is the average of most favored nation rates weighted by the product import shares corresponding to each partner country. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups and import weights. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database. Manufactured products are commodities classified in SITC revision 3 sections 5-8 excluding division 68. Tariff data are primarily sourced from the World Trade Organization (World Trade Organization (WTO)) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. Only tariff lines with both reported MFN rates and corresponding trade values are included. The WTO applies standardized concordance procedures to match trade and tariff data using harmonized product classifications.","theme":"inter","source_group":"wb"},{"code":"TM.TAX.TCOM.WM.FN.ZS","name":"Taux de droits, nation la plus favorisée, moyenne pondérée, produits primaires ( %)","description":"Le tarif moyen pondéré de la nation la plus favorisée est la moyenne des taux de la nation la plus favorisée pondérée par les parts d'importation d...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.TAX.TCOM.WM.FN.ZS?locations=CI","methodology":"Methodology: This indicator represents the trade-weighted average of most-favored-nation (MFN) tariff rates across all primary products tariff lines. Import values are used to weight each rate, reflecting the relative economic significance of different products in international trade. The weighted average is calculated by taking the sum of the products of MFN rates and import values, divided by the total import value. Weighted mean most favored nations tariff is the average of most favored nation rates weighted by the product import shares corresponding to each partner country. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups and import weights. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database. Primary products are commodities classified in SITC revision 3 sections 0-4 plus division 68 (nonferrous metals). Tariff data are primarily sourced from the World Trade Organization (World Trade Organization (WTO)) Consolidated Tariff Schedules (Consolidated Tariff Schedules (CTS)) and Integrated Database (Integrated Database (IDB)), with supplementary inputs from the United Nations Conference on Trade and Development (United Nations Conference on Trade and Development (UNCTAD)). Data are submitted by national authorities using the Harmonized System (Harmonized System (HS)) classification. The WTO Secretariat validates and harmonizes submissions to a common HS version for comparability. Data are generally updated annually or as new schedules are submitted. Due to validation and alignment processes, there is typically a one- to two-year time lag between national reporting and publication. Only tariff lines with both reported MFN rates and corresponding trade values are included. The WTO applies standardized concordance procedures to match trade and tariff data using harmonized product classifications.","theme":"inter","source_group":"wb"},{"code":"GC.TAX.TOTL.GD.ZS","name":"Recettes fiscales ( % du PIB)","description":"Les impôts sont des paiements obligatoires et sans contrepartie, en espèces ou en nature, effectués par des organismes institutionnels.\n\n\nunités en...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.TOTL.GD.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.TAX.TOTL.CN","name":"Recettes fiscales (LCU courante)","description":"Les impôts sont des paiements obligatoires et sans contrepartie, en espèces ou en nature, effectués par des organismes institutionnels.\n\n\nunités en...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.TOTL.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"NY.TAX.NIND.KN","name":"Impôts moins subventions sur les produits (UCV constantes)","description":"Les impôts moins les subventions sur la production comprennent les impôts à payer moins les subventions à recevoir sur les biens ou services produi...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.TAX.NIND.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.TAX.NIND.CN","name":"Impôts moins subventions sur les produits (LCU actuelle)","description":"Les impôts moins les subventions sur la production comprennent les impôts à payer moins les subventions à recevoir sur les biens ou services produi...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.TAX.NIND.CN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"NY.TAX.NIND.CD","name":"Impôts moins subventions sur les produits (en dollars américains courants)","description":"Les impôts moins les subventions sur la production comprennent les impôts à payer moins les subventions à recevoir sur les biens ou services produi...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.TAX.NIND.CD?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"GC.TAX.EXPT.ZS","name":"Impôts sur les exportations ( % des recettes fiscales)","description":"Les taxes à l'exportation sont des taxes sur les biens ou services qui deviennent payables au gouvernement lorsque les biens quittent le territoire...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.EXPT.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.TAX.EXPT.CN","name":"Impôts à l'exportation (LCU courante)","description":"Les taxes à l'exportation sont des taxes sur les biens ou services qui deviennent payables au gouvernement lorsque les biens quittent le territoire...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.EXPT.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.TAX.GSRV.RV.ZS","name":"Impôts sur les biens et services ( % du chiffre d'affaires)","description":"Les impôts généraux sur les biens et services sont des impôts prélevés sur la production, la location, la livraison, la vente, l'achat ou tout autr...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.GSRV.RV.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.TAX.GSRV.VA.ZS","name":"Impôts sur les biens et services (en % de la valeur ajoutée de l'industrie et des services)","description":"Les impôts généraux sur les biens et services sont des impôts prélevés sur la production, la location, la livraison, la vente, l'achat ou tout autr...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.GSRV.VA.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.TAX.GSRV.CN","name":"Impôts sur les biens et services (LCU actuelles)","description":"Les impôts généraux sur les biens et services sont des impôts prélevés sur la production, la location, la livraison, la vente, l'achat ou tout autr...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.GSRV.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.TAX.YPKG.RV.ZS","name":"Impôts sur le revenu, les bénéfices et les plus-values ( % du chiffre d'affaires)","description":"Les impôts sur le revenu, les bénéfices et les plus-values ​​sont des impôts payables sur les revenus, les bénéfices et les plus-values ​​réels ou ...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.YPKG.RV.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.TAX.YPKG.ZS","name":"Impôts sur le revenu, les bénéfices et les plus-values ( % du total des impôts)","description":"Les impôts sur le revenu, les bénéfices et les plus-values ​​sont des impôts payables sur les revenus, les bénéfices et les plus-values ​​réels ou ...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.YPKG.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.TAX.YPKG.CN","name":"Impôts sur le revenu, les bénéfices et les plus-values (LCU actuelle)","description":"Les impôts sur le revenu, les bénéfices et les plus-values ​​sont des impôts payables sur les revenus, les bénéfices et les plus-values ​​réels ou ...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.YPKG.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.TAX.INTT.RV.ZS","name":"Impôts sur le commerce international ( % du chiffre d'affaires)","description":"Les impôts sur le commerce international sont des impôts qui deviennent payables lorsque des marchandises franchissent les frontières nationales ou...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.INTT.RV.ZS?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"GC.TAX.INTT.CN","name":"Impôts sur le commerce international (LCU actuelles)","description":"Les impôts sur le commerce international sont des impôts qui deviennent payables lorsque des marchandises franchissent les frontières nationales ou...","source_link":"https://donnees.banquemondiale.org/indicateur/GC.TAX.INTT.CN?locations=CI","methodology":"Methodology: Government Finance statistics are compiled in accordance with international standards: Government Finance Statistics Manual, 2014 or 2001 editions. Specific information on how countries compile their Government Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): Government Financial Statistics are compiled within a conceptual and reporting framework suitable for analyzing and evaluating fiscal policy, especially the performance of the general government sector and the broader public sector of any economy.","theme":"finance","source_group":"wb"},{"code":"BX.GRT.TECH.CD.WD","name":"Subventions de coopération technique (BoP, dollars américains courants)","description":"Les subventions de coopération technique comprennent les subventions de coopération technique autonomes, qui sont destinées à financer le transfert...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GRT.TECH.CD.WD?locations=CI","methodology":"Technical cooperation contributions take the form mainly of the supply of human resources from donors or action directed to human resources (such as training or advice). Also included are aid for promoting development awareness and aid provided to refugees in the donor economy. Assistance specifically to facilitate a capital project is not included. Technical cooperation ncludes both grants to nationals of aid recipient countries receiving education or training at home or abroad and payments to consultants, advisers and similar personnel as well as teachers and administrators serving in recipient countries (including the cost of associated equipment).\n\nThe flows of official and private financial resources from the members of the Development Assistance Committee (DAC) of the Organisation for Economic Co-operation and Development (OECD) to developing economies are compiled by DAC, based principally on reporting by DAC members using standard questionnaires issued by the DAC Secretariat. A network of statistical correspondents collects data from aid agencies and government departments (central, state and local) on an ongoing basis. Their task is also to ensure that reporting conforms to the Reporting Directives (definitions and classifications) agreed by the DAC.\n\nThe official development assistance (ODA) estimates are published annually at the end of the calendar year in International Development Statistics (IDS) database. Data are in current U.S. dollars.","theme":"inter","source_group":"wb"},{"code":"SP.POP.TECH.RD.P6","name":"Techniciens en R&D (par million de personnes)","description":"Le nombre de techniciens ayant participé à la recherche et au développement (R&D), exprimé en millions.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.POP.TECH.RD.P6?locations=CI","methodology":"Methodology: Technicians in research and development (R&D) are persons whose main tasks require technical knowledge and experience in one or more fields of engineering, physical and life sciences, or social sciences and humanities. \n\nThe OECD's Frascati Manual defines research and experimental development as \"creative work undertaken on a systemic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications.\" R&D covers basic research, applied research, and experimental development.\n\n(1) Basic research - Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundation of phenomena and observable facts, without any particular application or use in view.\n\n(2) Applied research - Applied research is also original investigation undertaken in order to acquire new knowledge; it is, however, directed primarily towards a specific practical aim or objective.\n\n(3) Experimental development - Experimental development is systematic work, drawing on existing knowledge gained from research and/or practical experience, which is directed to producing new materials, products or devices, to installing new processes, systems and services, or to improving substantially those already produced or installed.\n\nThe fields of science and technology used to classify R&D according to the Revised Fields of Science and Technology Classification are:\n1. Natural sciences;\n2. Engineering and technology;\n3. Medical and health sciences;\n4. Agricultural sciences;\n5. Social sciences;\n6. Humanities and the arts.\n\nData are for full-time equivalent (FTE); the FTE of R&D personnel is defined as the ratio of working hours actually spent on R&D during a specific reference period (usually a calendar year) divided by the total number of hours conventionally worked in the same period by an individual or by a group. \n\nThe data are obtained through statistical surveys which are regularly conducted at national level covering R&D performing entities in the private and public sectors.","theme":"demo","source_group":"wb"},{"code":"SP.MTR.1519.ZS","name":"Mères adolescentes ( % des femmes âgées de 15 à 19 ans qui ont eu des enfants ou qui sont actuellement enceintes)","description":"Les mères adolescentes représentent le pourcentage de femmes âgées de 15 à 19 ans qui ont déjà des enfants ou sont actuellement enceintes.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.MTR.1519.ZS?locations=CI","methodology":"Methodology: The data represents the combined percentage of women aged 15-19 who are mothers and those who are pregnant with their first child. This information is gathered through individual interviews with women of reproductive age during household surveys, including Demographic and Health Surveys. For more details, please refer to the DHS website: https://dhsprogram.com/data/Guide-to-DHS-Statistics/Teenage_Pregnancy_and_Motherhood.htm","theme":"social","source_group":"wb"},{"code":"NY.TTF.GNFS.KN","name":"Ajustement des termes de l'échange (UCT constante)","description":"L’ajustement des termes de l’échange est égal à la capacité d’importer (valeur au prix courant des exportations de biens et services déflatée par l...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.TTF.GNFS.KN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"macro","source_group":"wb"},{"code":"ER.PTD.TOTL.ZS","name":"Aires protégées terrestres et marines ( % de la superficie territoriale totale)","description":"Les zones terrestres protégées sont des zones totalement ou partiellement protégées d'au moins 1 000 hectares qui sont désignées par les autorités ...","source_link":"https://donnees.banquemondiale.org/indicateur/ER.PTD.TOTL.ZS?locations=CI","methodology":"Methodology: This indicator is calculated using all the nationally designated protected areas recorded in the World Database on Protected Areas (WDPA) whose location and extent is known. The WDPA database is stored within a Geographic Information System (GIS) that stores information about protected areas such as their name, type and date of designation, documented area, geographic location (point) and/or boundary (polygon).\nA GIS analysis is used to calculate terrestrial and marine protection. For this a global protected area layer is created by combining the polygons and points recorded in the WDPA. Circular buffers are created around points based on the known extent of protected areas for which no polygon is available. Annual protected area layers are created by dissolving the global protected area layer by the known year of establishment of protected areas recorded in the WDPA. The annual protected area layers are overlaid with country/territory boundaries, coastlines and buffered coastlines (delineating the territorial waters) to obtain the absolute coverage (in square kilometers) of protected areas by country/territory per year from 1990 to present. The total area of a country's/territory's terrestrial protected areas and marine protected areas in territorial waters is divided by the total area of its land areas (including inland waters) and territorial waters to obtain the relative coverage (percentage) of protected areas.\nStatistical concept(s):","theme":"territory","source_group":"wb"},{"code":"ER.LND.PTLD.ZS","name":"Aires protégées terrestres ( % de la superficie terrestre)","description":"Les zones terrestres protégées sont des zones totalement ou partiellement protégées d'au moins 1 000 hectares qui sont désignées par les autorités ...","source_link":"https://donnees.banquemondiale.org/indicateur/ER.LND.PTLD.ZS?locations=CI","methodology":"Methodology: This indicator is calculated using all the nationally designated protected areas recorded in the World Database on Protected Areas (WDPA) whose location and extent is known. The WDPA database is stored within a Geographic Information System (GIS) that stores information about protected areas such as their name, type and date of designation, documented area, geographic location (point) and/or boundary (polygon). \nDesignating an area as protected does not mean that protection is in force. And for small countries that have only protected areas smaller than 1,000 hectares, the size limit in the definition leads to an underestimate of protected areas. Nationally protected areas are defined using the six IUCN management categories for areas of at least 1,000 hectares: scientific reserves and strict nature reserves with limited public access; national parks of national or international significance and not materially affected by human activity; natural monuments and natural landscapes with unique aspects; managed nature reserves and wildlife sanctuaries; protected landscapes (which may include cultural landscapes); and areas managed mainly for the sustainable use of natural systems to ensure long-term protection and maintenance of biological diversity. \n\n\n\n\n\n\n\n\n\n\n\nA GIS analysis is used to calculate terrestrial and marine protection. For this a global protected area layer is created by combining the polygons and points recorded in the WDPA. Circular buffers are created around points based on the known extent of protected areas for which no polygon is available. Annual protected area layers are created by dissolving the global protected area layer by the known year of establishment of protected areas recorded in the WDPA. The annual protected area layers are overlaid with country/territory boundaries, coastlines and buffered coastlines (delineating the territorial waters) to obtain the absolute coverage (in square kilometers) of protected areas by country/territory. The total area of a country's/territory's terrestrial protected areas and marine protected areas in territorial waters is divided by the total area of its land areas (including inland waters) and territorial waters to obtain the relative coverage (percentage) of protected areas.\nStatistical concept(s):","theme":"territory","source_group":"wb"},{"code":"SE.TER.TCHR.FE.ZS","name":"Enseignement supérieur, personnel universitaire ( % de femmes)","description":"Dans l'enseignement supérieur, le personnel académique (% de femmes) représente la part du personnel académique féminin dans l'enseignement supérieur.","source_link":"https://donnees.banquemondiale.org/indicateur/SE.TER.TCHR.FE.ZS?locations=CI","methodology":"Methodology: The share of female academic staffs in tertiary education is calculated by dividing the total number of female academic staffs at tertiary level of education by the total number of academic staffs at the same level, and multiplying by 100.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): The share of female teachers shows the level of gender representation in the teaching force. A value of greater than 50% indicates more opportunities or preference for women to participate in teaching activities.","theme":"education","source_group":"wb"},{"code":"NV.MNF.TXTL.ZS.UN","name":"Textiles et vêtements ( % de la valeur ajoutée dans l'industrie manufacturière)","description":"Les textiles et l'habillement font référence aux industries des divisions 17 à 19 de la CITI (rév.","source_link":"https://donnees.banquemondiale.org/indicateur/NV.MNF.TXTL.ZS.UN?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"secondary","source_group":"wb"},{"code":"IC.FRM.DURS","name":"Temps nécessaire à l'obtention d'une licence d'exploitation (jours)","description":"L'attente moyenne, en jours, pour obtenir une autorisation d'exploitation, du jour de la demande jusqu'au jour de son octroi.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.DURS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.GOV.DURS.ZS","name":"Temps consacré à l'application des exigences de la réglementation gouvernementale ( % du temps de la haute direction)","description":"Pourcentage moyen du temps de la haute direction consacré au cours d'une semaine typique à traiter les exigences imposées par les réglementations g...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.GOV.DURS.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"IC.ELC.DURS","name":"Temps d'obtention d'un raccordement électrique (jours)","description":"Attente moyenne, en jours, vécue pour obtenir un branchement électrique depuis le jour où cet établissement en a fait la demande jusqu'au jour où i...","source_link":"https://donnees.banquemondiale.org/indicateur/IC.ELC.DURS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"SH.ALC.PCAP.LI","name":"Consommation totale d'alcool par habitant (litres d'alcool pur, estimations prévues, 15 ans et +)","description":"La consommation totale d'alcool par habitant est définie comme la quantité totale (somme de l'alcool enregistré et non enregistré) d'alcool consomm...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.ALC.PCAP.LI?locations=CI","methodology":"Methodology: The estimates for the total alcohol consumption are produced by summing up the 3-year average per capita (15+) recorded alcohol consumption and an estimate of per capita (15+) unrecorded alcohol consumption for a calendar year. Tourist consumption takes into account tourists visiting the country and inhabitants visiting other countries.","theme":"sante","source_group":"wb"},{"code":"SH.ALC.PCAP.FE.LI","name":"Consommation totale d'alcool par habitant, femmes (litres d'alcool pur, estimations projetées, femmes de 15 ans et +)","description":"La consommation totale d'alcool par habitant est définie comme la quantité totale (somme de l'alcool enregistré et non enregistré) d'alcool consomm...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.ALC.PCAP.FE.LI?locations=CI","methodology":"Methodology: The estimates for the total alcohol consumption are produced by summing up the 3-year average per capita (15+) recorded alcohol consumption and an estimate of per capita (15+) unrecorded alcohol consumption for a calendar year. Tourist consumption takes into account tourists visiting the country and inhabitants visiting other countries.","theme":"sante","source_group":"wb"},{"code":"SH.ALC.PCAP.MA.LI","name":"Consommation totale d'alcool par habitant, hommes (litres d'alcool pur, estimations projetées, hommes de 15 ans et +)","description":"La consommation totale d'alcool par habitant est définie comme la quantité totale (somme de l'alcool enregistré et non enregistré) d'alcool consomm...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.ALC.PCAP.MA.LI?locations=CI","methodology":"Methodology: The estimates for the total alcohol consumption are produced by summing up the 3-year average per capita (15+) recorded alcohol consumption and an estimate of per capita (15+) unrecorded alcohol consumption for a calendar year. Tourist consumption takes into account tourists visiting the country and inhabitants visiting other countries.","theme":"sante","source_group":"wb"},{"code":"DT.TDS.DECT.EX.ZS","name":"Service total de la dette ( % des exportations de biens, de services et de revenus primaires)","description":"Service total de la dette sur les exportations de biens, de services et de revenus primaires.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.TDS.DECT.EX.ZS?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"DT.TDS.DECT.GN.ZS","name":"Service total de la dette ( % du RNB)","description":"Le service total de la dette est la somme des remboursements du principal et des intérêts effectivement payés en devises, biens ou services sur la ...","source_link":"https://donnees.banquemondiale.org/indicateur/DT.TDS.DECT.GN.ZS?locations=CI","methodology":"Methodology: Data on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"ER.FSH.PROD.MT","name":"Production totale de la pêche (en tonnes)","description":"La production halieutique totale mesure le volume d'espèces aquatiques capturées par un pays à toutes fins commerciales, industrielles, récréatives...","source_link":"https://donnees.banquemondiale.org/indicateur/ER.FSH.PROD.MT?locations=CI","methodology":"Methodology: Information on capture production is collected annually from relevant national offices concerned with fishery statistics, by means of a system of standardized forms, which list for each country the relative species items and fishing areas breakdown.\nIn the case of some \"aquatic products\", data are also obtained from trade associations or other specialized international organizations to which data are also submitted. In this way the statistics are reviewed by subject matter specialists.\nData concerning the nominal catch of certain major groups are generally reviewed in collaboration with the regional agency concerned. For example, for ISSCAAP group 36 (Tunas, bonitos and billfishes) data provided by the national correspondents are often replaced by the \"best scientific estimates\" produced by regional bodies collecting tuna catch statistics (i.e. ICCAT, IOTC, SPC and IATTC.)\nSee https://www.fao.org/fishery/en/collection/capture","theme":"primary","source_group":"wb"},{"code":"EN.GHG.TOT.ZG.AR5","name":"Émissions totales de gaz à effet de serre à l'exclusion de l'UTCATF (variation en % par rapport à 1990)","description":"Variation des émissions (en %) de l'année en cours par rapport aux émissions de l'année de référence 1990 des six gaz à effet de serre (GES) couver...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.TOT.ZG.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Uses detailed modeling, facility-level data, or continuous emissions monitoring\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.ALL.MT.CE.AR5","name":"Émissions totales de gaz à effet de serre hors UTCATF (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles des six gaz à effet de serre (GES) couverts par le Protocole de Kyoto (dioxyde de carbone (CO2), méthane (CH4), ...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.ALL.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.ALL.PC.CE.AR5","name":"Émissions totales de gaz à effet de serre par habitant, à l'exclusion de l'ATCATF (t CO2e/habitant)","description":"Émissions annuelles totales des six gaz à effet de serre (GES) couverts par le Protocole de Kyoto (dioxyde de carbone (CO2), méthane (CH4), oxyde n...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.ALL.PC.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"EN.GHG.ALL.LU.MT.CE.AR5","name":"Émissions totales de gaz à effet de serre, y compris l'ATCATF (Mt d'équivalent CO2)","description":"Une mesure des émissions annuelles des six gaz à effet de serre (GES) couverts par le Protocole de Kyoto (dioxyde de carbone (CO2), méthane (CH4), ...","source_link":"https://donnees.banquemondiale.org/indicateur/EN.GHG.ALL.LU.MT.CE.AR5?locations=CI","methodology":"Methodology: EDGAR compiles data from multiple authoritative sources, including: International Energy Agency (IEA) – Energy consumption data, United Nations Framework Convention on Climate Change (UNFCCC) – National GHG inventories, Food and Agriculture Organization (FAO) – Agricultural emissions, World Bank & National Statistics Offices – Socioeconomic and industrial data, Scientific Literature & IPCC Guidelines – Emission factors and methodologies. \n\nEDGAR follows the IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories to estimate emissions. The core equation is:\n\n?? =??×????\n\nWhere:\n\nE = Total emissions (kg, tons, or CO2-equivalent)\nA = Activity data (e.g., fuel consumption, production levels)\nEF = Emission factor (kg of pollutant per unit of activity)\n\nDepending on the pollutant, different tiers of complexity are used:\n\nTier 1 – Default IPCC emission factors (simple estimation)\nTier 2 – Country/region-specific emission factors\nTier 3 – Detailed process-based models (highest accuracy)","theme":"territory","source_group":"wb"},{"code":"NY.GDP.TOTL.RT.ZS","name":"Rentes totales des ressources naturelles ( % du PIB)","description":"Les rentes totales des ressources naturelles sont la somme des rentes pétrolières, des rentes du gaz naturel, des rentes du charbon (dur et doux), ...","source_link":"https://donnees.banquemondiale.org/indicateur/NY.GDP.TOTL.RT.ZS?locations=CI","methodology":"Methodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).","theme":"primary","source_group":"wb"},{"code":"FI.RES.TOTL.DT.ZS","name":"Total des réserves (en % de la dette extérieure totale)","description":"Les actifs de réserve sont des actifs externes, y compris l'or monétaire, qui sont facilement accessibles et contrôlés par les autorités monétaires...","source_link":"https://donnees.banquemondiale.org/indicateur/FI.RES.TOTL.DT.ZS?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FI.RES.TOTL.CD","name":"Réserves totales, y compris l'or (en dollars américains courants)","description":"Les actifs de réserve sont des actifs externes, y compris l'or monétaire, qui sont facilement accessibles et contrôlés par les autorités monétaires...","source_link":"https://donnees.banquemondiale.org/indicateur/FI.RES.TOTL.CD?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FI.RES.TOTL.MO","name":"Réserves totales en mois d'importations","description":"Les actifs de réserve sont des actifs externes, y compris l'or monétaire, qui sont facilement accessibles et contrôlés par les autorités monétaires...","source_link":"https://donnees.banquemondiale.org/indicateur/FI.RES.TOTL.MO?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"FI.RES.XGLD.CD","name":"Réserves totales, hors or (en dollars américains courants)","description":"Cette série comprend les actifs extérieurs (à l'exclusion de l'or monétaire) qui sont facilement accessibles et contrôlés par les autorités monétai...","source_link":"https://donnees.banquemondiale.org/indicateur/FI.RES.XGLD.CD?locations=CI","methodology":"Methodology: Monetary and Financial statistics are compiled in accordance with international standards: Monetary and Financial Statistics Manual, 2018 or 2004 versions. Specific information on how countries compile their Monetary and Finance statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual framework comes from the Monetary and Financial Statistic Manual which outlines the analytical presentation of monetary statistics, which provide critical inputs for monetary policy formulation and monitoring. The statistics covered in this Manual also support the assessment of financial system stability.","theme":"macro","source_group":"wb"},{"code":"NE.TRD.GNFS.ZS","name":"Commerce ( % du PIB)","description":"Le commerce est la somme des exportations et des importations de biens et de services.","source_link":"https://donnees.banquemondiale.org/indicateur/NE.TRD.GNFS.ZS?locations=CI","methodology":"Methodology: National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.","theme":"inter","source_group":"wb"},{"code":"BG.GSR.NFSV.GD.ZS","name":"Commerce des services (en % du PIB)","description":"Le commerce total des services comprend les services fournis par les résidents aux non-résidents ainsi que les services fournis par les non-résiden...","source_link":"https://donnees.banquemondiale.org/indicateur/BG.GSR.NFSV.GD.ZS?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"IP.TMK.NRCT","name":"Demandes d'enregistrement de marques de commerce, non-résidents, en nombre","description":"Une marque est un signe capable de distinguer les produits ou services d’une entreprise de ceux d’autres entreprises.","source_link":"https://donnees.banquemondiale.org/indicateur/IP.TMK.NRCT?locations=CI","methodology":"Methodology: Information about the World Intellectual Property Organization (WIPO) data collection can be accessed on the WIPO website: https://www.wipo.int/en/web/ip-statistics/about\nStatistical concept(s): Trademark: A sign used to distinguish the goods or services of one undertaking from those of another. A trademark may consist of words and combinations of words (for instance, names or slogans), logos, figures and images, letters, numbers, sounds, or, in rare instances, smells or moving images, or a combination thereof. The procedures for registering trademarks are governed by the legislation and procedures of national and regional IP offices and WIPO. Trademark rights are limited to the jurisdiction of the IP office that registers the trademark. Trademarks can be registered by filing an application at the relevant national or regional office(s), or by filing an international application through the Madrid System.\n\nNon-resident application refers to an application filed with the IP office of or acting on behalf of a state or jurisdiction in which the first-named applicant in the application is not domiciled.\n\nClass count: The number of classes specified in a trademark application or registration. In the international trademark system, and at certain national and regional offices, an applicant can file a trademark application specifying one or more of the 45 goods and services classes of the Nice Classification. Offices use either a multi-class or a single filing system. For example, the offices of Japan, the Republic of Korea and the United States of America (US), as well as many European IP offices, have multi-class filing systems. On the other hand, the offices of Brazil, Mexico, and South Africa follow a single-class filing system, requiring a separate application for each class in which an applicant seeks trademark protection. To capture the differences in application and registration numbers across offices, it is useful to compare their respective application and registration class counts.","theme":"business","source_group":"wb"},{"code":"IP.TMK.RSCT","name":"Demandes d'enregistrement de marques de commerce, résidents, par nombre","description":"Une marque est un signe capable de distinguer les produits ou services d’une entreprise de ceux d’autres entreprises.","source_link":"https://donnees.banquemondiale.org/indicateur/IP.TMK.RSCT?locations=CI","methodology":"Methodology: Information about the World Intellectual Property Organization (WIPO) data collection can be accessed on the WIPO website: https://www.wipo.int/en/web/ip-statistics/about\nStatistical concept(s): Trademark: A sign used to distinguish the goods or services of one undertaking from those of another. A trademark may consist of words and combinations of words (for instance, names or slogans), logos, figures and images, letters, numbers, sounds, or, in rare instances, smells or moving images, or a combination thereof. The procedures for registering trademarks are governed by the legislation and procedures of national and regional IP offices and WIPO. Trademark rights are limited to the jurisdiction of the IP office that registers the trademark. Trademarks can be registered by filing an application at the relevant national or regional office(s), or by filing an international application through the Madrid System.\n\nFor statistical purposes, a resident application refers to an application filed with the IP office of, or acting for, the state or jurisdiction in which the first named applicant in the application is resident. For example, an application filed with the Japan Patent Office (JPO) by a resident of Japan is considered a resident application from the perspective of the JPO. Resident applications are sometimes referred to as “domestic applications.” A resident grant/registration is an IP right issued on the basis of a resident application.\n\nClass count: The number of classes specified in a trademark application or registration. In the international trademark system, and at certain national and regional offices, an applicant can file a trademark application specifying one or more of the 45 goods and services classes of the Nice Classification. Offices use either a multi-class or a single filing system. For example, the offices of Japan, the Republic of Korea and the United States of America (US), as well as many European IP offices, have multi-class filing systems. On the other hand, the offices of Brazil, Mexico, and South Africa follow a single-class filing system, requiring a separate application for each class in which an applicant seeks trademark protection. To capture the differences in application and registration numbers across offices, it is useful to compare their respective application and registration class counts.","theme":"business","source_group":"wb"},{"code":"SE.SEC.TCAQ.LO.ZS","name":"Enseignants formés dans le premier cycle de l'enseignement secondaire (en % du nombre total d'enseignants)","description":"Les enseignants formés dans l’enseignement secondaire inférieur représentent le pourcentage d’enseignants du premier cycle du secondaire qui ont re...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.TCAQ.LO.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.SEC.TCAQ.LO.FE.ZS","name":"Enseignantes formées dans le premier cycle de l'enseignement secondaire, femmes ( % d'enseignantes)","description":"Les enseignants formés dans l’enseignement secondaire inférieur représentent le pourcentage d’enseignants du premier cycle du secondaire qui ont re...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.TCAQ.LO.FE.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.SEC.TCAQ.LO.MA.ZS","name":"Enseignants formés dans le premier cycle de l'enseignement secondaire, hommes ( % d'enseignants masculins)","description":"Les enseignants formés dans l’enseignement secondaire inférieur représentent le pourcentage d’enseignants du premier cycle du secondaire qui ont re...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.TCAQ.LO.MA.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.PRE.TCAQ.ZS","name":"Enseignants formés dans l'enseignement préprimaire ( % du nombre total d'enseignants)","description":"Les enseignants formés dans l’enseignement préscolaire représentent le pourcentage d’enseignants du préscolaire qui ont reçu la formation pédagogiq...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRE.TCAQ.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.PRE.TCAQ.FE.ZS","name":"Enseignantes formées dans l'enseignement préprimaire, femmes ( % d'enseignantes)","description":"Les enseignants formés dans l’enseignement préscolaire représentent le pourcentage d’enseignants du préscolaire qui ont reçu la formation pédagogiq...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRE.TCAQ.FE.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.PRE.TCAQ.MA.ZS","name":"Enseignants formés dans l'enseignement préprimaire, hommes ( % d'enseignants masculins)","description":"Les enseignants formés dans l’enseignement préscolaire représentent le pourcentage d’enseignants du préscolaire qui ont reçu la formation pédagogiq...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRE.TCAQ.MA.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.PRM.TCAQ.ZS","name":"Enseignants formés dans l'enseignement primaire ( % du nombre total d'enseignants)","description":"Les enseignants formés dans l’enseignement primaire représentent le pourcentage d’enseignants du primaire qui ont reçu la formation pédagogique org...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.TCAQ.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.PRM.TCAQ.FE.ZS","name":"Enseignantes formées dans l'enseignement primaire, femmes ( % d'enseignantes)","description":"Les enseignants formés dans l’enseignement primaire représentent le pourcentage d’enseignants du primaire qui ont reçu la formation pédagogique org...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.TCAQ.FE.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.PRM.TCAQ.MA.ZS","name":"Enseignants formés dans l'enseignement primaire, hommes ( % d'enseignants masculins)","description":"Les enseignants formés dans l’enseignement primaire représentent le pourcentage d’enseignants du primaire qui ont reçu la formation pédagogique org...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.PRM.TCAQ.MA.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.SEC.TCAQ.ZS","name":"Enseignants formés dans l'enseignement secondaire ( % du total des enseignants)","description":"Les enseignants formés dans l’enseignement secondaire représentent le pourcentage d’enseignants du secondaire qui ont reçu la formation pédagogique...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.TCAQ.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.SEC.TCAQ.FE.ZS","name":"Enseignants formés dans l'enseignement secondaire, femmes ( % d'enseignantes)","description":"Les enseignants formés dans l’enseignement secondaire représentent le pourcentage d’enseignants du secondaire qui ont reçu la formation pédagogique...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.TCAQ.FE.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.SEC.TCAQ.MA.ZS","name":"Enseignants formés dans l'enseignement secondaire, hommes ( % d'enseignants masculins)","description":"Les enseignants formés dans l’enseignement secondaire représentent le pourcentage d’enseignants du secondaire qui ont reçu la formation pédagogique...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.TCAQ.MA.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.SEC.TCAQ.UP.ZS","name":"Enseignants formés dans le deuxième cycle de l'enseignement secondaire (en % du nombre total d'enseignants)","description":"Les enseignants formés dans l’enseignement secondaire supérieur représentent le pourcentage d’enseignants du deuxième cycle de l’enseignement secon...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.TCAQ.UP.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.SEC.TCAQ.UP.FE.ZS","name":"Enseignants formés dans le deuxième cycle de l'enseignement secondaire, femmes ( % d'enseignantes)","description":"Les enseignants formés dans l’enseignement secondaire supérieur représentent le pourcentage d’enseignants du deuxième cycle de l’enseignement secon...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.TCAQ.UP.FE.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.\nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"SE.SEC.TCAQ.UP.MA.ZS","name":"Enseignants formés dans le deuxième cycle de l'enseignement secondaire, hommes ( % d'enseignants masculins)","description":"Les enseignants formés dans l’enseignement secondaire supérieur représentent le pourcentage d’enseignants du deuxième cycle de l’enseignement secon...","source_link":"https://donnees.banquemondiale.org/indicateur/SE.SEC.TCAQ.UP.MA.ZS?locations=CI","methodology":"Methodology: Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100. \nData on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. \nThe reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).\nStatistical concept(s): This indicator quantifies the proportion of educators within the teaching workforce who have received comprehensive pedagogical training. A high percentage signifies that a substantial majority of students are instructed by teachers equipped with the necessary pedagogical skills and training to teach effectively. The role of teachers is pivotal in upholding the standard of education delivered. Optimal educational outcomes are achieved when all teachers are provided with sufficient, pertinent, and targeted pedagogical training, enabling them to teach at their designated educational level. Moreover, it is crucial that teachers possess the academic qualifications required to competently cover the subject matter they are tasked with teaching.","theme":"education","source_group":"wb"},{"code":"TX.VAL.TRAN.ZS.WT","name":"Services de transport ( % des exportations de services commerciaux)","description":"Le transport est le processus de transport de personnes et d'objets d'un endroit à un autre ainsi que les services de soutien et auxiliaires associés.","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.TRAN.ZS.WT?locations=CI","methodology":"Methodology: International trade in services statistics are compiled in accordance with international standards: Manual on Statistics of International Trade in Services 2010. Specific information on how countries compile their trade in service statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of international trade in services covers trade in services in the conventional sense of transactions (exports and imports) between residents and non-residents. In addition, it covers services delivered through enterprises that are locally established but foreign-controlled and cases where individuals are temporarily present abroad for the purpose of supplying a service.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.TRAN.ZS.WT","name":"Services de transport ( % des importations de services commerciaux)","description":"Le transport est le processus de transport de personnes et d'objets d'un endroit à un autre ainsi que les services de soutien et auxiliaires associés.","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.TRAN.ZS.WT?locations=CI","methodology":"Methodology: International trade in services statistics are compiled in accordance with international standards: Manual on Statistics of International Trade in Services 2010. Specific information on how countries compile their trade in service statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of international trade in services covers trade in services in the conventional sense of transactions (exports and imports) between residents and non-residents. In addition, it covers services delivered through enterprises that are locally established but foreign-controlled and cases where individuals are temporarily present abroad for the purpose of supplying a service.","theme":"inter","source_group":"wb"},{"code":"BX.GSR.TRAN.ZS","name":"Services de transport ( % des exportations de services, balance des charges)","description":"Les services de transport couvrent le processus de transport de personnes et d'objets d'un endroit à un autre ainsi que les services de soutien et ...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GSR.TRAN.ZS?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BM.GSR.TRAN.ZS","name":"Services de transport ( % des importations de services, BoP)","description":"Les services de transport couvrent le processus de transport de personnes et d'objets d'un endroit à un autre ainsi que les services de soutien et ...","source_link":"https://donnees.banquemondiale.org/indicateur/BM.GSR.TRAN.ZS?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"TX.VAL.TRVL.ZS.WT","name":"Services de voyage ( % des exportations de services commerciaux)","description":"Les services de voyage couvrent les biens et services destinés à leur propre usage ou à offrir, acquis dans une économie par des non-résidents lors...","source_link":"https://donnees.banquemondiale.org/indicateur/TX.VAL.TRVL.ZS.WT?locations=CI","methodology":"Methodology: International trade in services statistics are compiled in accordance with international standards: Manual on Statistics of International Trade in Services 2010. Specific information on how countries compile their trade in service statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of international trade in services covers trade in services in the conventional sense of transactions (exports and imports) between residents and non-residents. In addition, it covers services delivered through enterprises that are locally established but foreign-controlled and cases where individuals are temporarily present abroad for the purpose of supplying a service.","theme":"inter","source_group":"wb"},{"code":"TM.VAL.TRVL.ZS.WT","name":"Services de voyage ( % des importations de services commerciaux)","description":"Les services de voyage couvrent les biens et services destinés à leur propre usage ou à offrir, acquis dans une économie par des non-résidents lors...","source_link":"https://donnees.banquemondiale.org/indicateur/TM.VAL.TRVL.ZS.WT?locations=CI","methodology":"Methodology: International trade in services statistics are compiled in accordance with international standards: Manual on Statistics of International Trade in Services 2010. Specific information on how countries compile their trade in service statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of international trade in services covers trade in services in the conventional sense of transactions (exports and imports) between residents and non-residents. In addition, it covers services delivered through enterprises that are locally established but foreign-controlled and cases where individuals are temporarily present abroad for the purpose of supplying a service.","theme":"inter","source_group":"wb"},{"code":"BX.GSR.TRVL.ZS","name":"Services de voyage ( % des exportations de services, BdP)","description":"Les services de voyage couvrent les biens et services destinés à leur propre usage ou à offrir, acquis dans une économie par des non-résidents lors...","source_link":"https://donnees.banquemondiale.org/indicateur/BX.GSR.TRVL.ZS?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"BM.GSR.TRVL.ZS","name":"Services de voyage ( % des importations de services, BdP)","description":"Les services de voyage couvrent les biens et services destinés à leur propre usage ou à offrir, acquis dans une économie par des non-résidents lors...","source_link":"https://donnees.banquemondiale.org/indicateur/BM.GSR.TRVL.ZS?locations=CI","methodology":"Methodology: Balance of payments statistics are compiled in accordance with international standards: Balance of Payments and International Investment Position Manual, 6th or 5th editions. Specific information on how countries compile their balance of payments statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The international accounts for an economy summarize the economic relationships between residents of that economy and nonresidents. They comprise the following:\n\n(a) the international investment position (IIP)—a statement that shows at a point in time the value of: financial assets of residents of an economy that are claims on nonresidents or are gold bullion held as reserve assets; and the liabilities of residents of an economy to nonresidents;\n\n(b) the balance of payments—a statement that summarizes economic transactions between residents and nonresidents during a specific time period; and\n\n(c) the other changes in financial assets and liabilities accounts—a statement that shows other flows, such as valuation changes, that reconciles the balance of payments and IIP for a specific period, by showing changes due to economic events other than transactions between residents and nonresidents.","theme":"inter","source_group":"wb"},{"code":"SH.TBS.DTEC.ZS","name":"Taux de détection des cas de tuberculose ( %, toutes formes confondues)","description":"Le taux de détection des cas de tuberculose (toutes formes confondues) correspond au nombre de cas nouveaux et de rechutes de tuberculose notifiés ...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.TBS.DTEC.ZS?locations=CI","methodology":"Methodology: The number of new and relapse TB cases diagnosed and treated in national TB control  programmes and notified to WHO, divided by WHO's estimate of the number of incident TB cases for the same year, expressed as a percentage.\nStatistical concept(s): Tuberculosis is one of the main causes of adult deaths from a single infectious agent in developing countries. This indicator shows the tuberculosis detection rate for all detection methods. Editions before 2010 included the tuberculosis detection rates by DOTS, the internationally recommended strategy for tuberculosis control. Thus data on the case detection rate from 2010 onward cannot be compared with data in previous editions.","theme":"sante","source_group":"wb"},{"code":"SH.TBS.CURE.ZS","name":"Taux de réussite du traitement de la tuberculose ( % des nouveaux cas)","description":"Le taux de réussite du traitement de la tuberculose est le pourcentage de tous les nouveaux cas de tuberculose (ou des cas nouveaux et de rechute p...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.TBS.CURE.ZS?locations=CI","methodology":"Methodology: The proportion of cases registered in a given year (excluding cases placed on a second-line drug regimen) that successfully completed treatment without bacteriological evidence of failure. All registered cases fall into one of the following five mutually exclusive categories: treatment success, failure, death, lost to follow-up, not evaluated (missing data on the outcome of treatment).\nStatistical concept(s): Tuberculosis is one of the main causes of adult deaths from a single infectious agent in developing countries. Data on the success rate of tuberculosis treatment are provided for countries that have submitted data to the WHO. The treatment success rate for tuberculosis provides a useful indicator of the quality of health services. A low rate suggests that infectious patients may not be receiving adequate treatment. An important complement to the tuberculosis treatment success rate is the case detection rate, which indicates whether there is adequate coverage by the recommended case detection and treatment strategy.","theme":"sante","source_group":"wb"},{"code":"SH.UHC.SRVS.CV.XD","name":"Indice de couverture des services de la CSU","description":"Indice de couverture des services de santé essentiels (basé sur des interventions de suivi qui incluent la santé reproductive, maternelle, néonatal...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.UHC.SRVS.CV.XD?locations=CI","methodology":"Methodology: For each country, the most recent value for each tracer indicators is taken from WHO or other international agencies. The index is computed using geometric means of the tracer indicators.\nStatistical concept(s): The Service Coverage Index used to track SDG 3.8.1 includes four indicator categories, namely (1) reproductive, manternal and newborn and child health, (2) infectious diseases, (3) non-communicable diseases and (4) service capacity and access. Each category contains several tracers. The index is constructed from geometric means of the tracer indicators; first, within each of the four categories, and then across the four category-specific means to obtain the final summary index. See Source for details about methodology.","theme":"sante","source_group":"wb"},{"code":"SL.UEM.ADVN.ZS","name":"Chômage des diplômés de l'enseignement supérieur (en % de la population active totale ayant fait des études supérieures)","description":"Le pourcentage de la population active ayant un niveau d’éducation avancé et qui est au chômage.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.ADVN.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The unemployment rate conveys the number of persons who are unemployed as a percent of the labour force (i.e., the employed plus the unemployed). The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.ADVN.FE.ZS","name":"Chômage des femmes ayant fait des études supérieures ( % de la main-d'œuvre féminine ayant fait des études supérieures)","description":"Le pourcentage de la population active ayant un niveau d’éducation avancé et qui est au chômage.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.ADVN.FE.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The unemployment rate conveys the number of persons who are unemployed as a percent of the labour force (i.e., the employed plus the unemployed). The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.ADVN.MA.ZS","name":"Chômage des hommes ayant fait des études supérieures ( % de la main-d'œuvre masculine ayant fait des études supérieures)","description":"Le pourcentage de la population active ayant un niveau d’éducation avancé et qui est au chômage.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.ADVN.MA.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The unemployment rate conveys the number of persons who are unemployed as a percent of the labour force (i.e., the employed plus the unemployed). The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.BASC.ZS","name":"Chômage avec l'éducation de base ( % de la population active totale avec l'éducation de base)","description":"Le pourcentage de la population active ayant un niveau d’éducation de base et qui est au chômage.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.BASC.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The unemployment rate conveys the number of persons who are unemployed as a percent of the labour force (i.e., the employed plus the unemployed). The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.BASC.FE.ZS","name":"Chômage des femmes dans l'enseignement de base ( % de la main-d'œuvre féminine dans l'enseignement de base)","description":"Le pourcentage de la population active ayant un niveau d’éducation de base et qui est au chômage.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.BASC.FE.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The unemployment rate conveys the number of persons who are unemployed as a percent of the labour force (i.e., the employed plus the unemployed). The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.BASC.MA.ZS","name":"Chômage chez les hommes ( % de la main-d'œuvre masculine dans l'éducation de base)","description":"Le pourcentage de la population active ayant un niveau d’éducation de base et qui est au chômage.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.BASC.MA.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The unemployment rate conveys the number of persons who are unemployed as a percent of the labour force (i.e., the employed plus the unemployed). The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.INTM.ZS","name":"Chômage dans l'enseignement intermédiaire ( % de la population active totale dans l'enseignement intermédiaire)","description":"Le pourcentage de la population active ayant un niveau d’éducation intermédiaire qui est au chômage.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.INTM.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The unemployment rate conveys the number of persons who are unemployed as a percent of the labour force (i.e., the employed plus the unemployed). The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.INTM.FE.ZS","name":"Chômage des femmes ayant un niveau d'éducation intermédiaire ( % de la main-d'œuvre féminine ayant un niveau d'éducation intermédiaire)","description":"Le pourcentage de la population active ayant un niveau d’éducation intermédiaire qui est au chômage.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.INTM.FE.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The unemployment rate conveys the number of persons who are unemployed as a percent of the labour force (i.e., the employed plus the unemployed). The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.INTM.MA.ZS","name":"Chômage des hommes ayant un niveau d'éducation intermédiaire ( % de la main-d'œuvre masculine ayant un niveau d'éducation intermédiaire)","description":"Le pourcentage de la population active ayant un niveau d’éducation intermédiaire qui est au chômage.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.INTM.MA.ZS?locations=CI","methodology":"Methodology: Labor force surveys are the preferred source of statistics on employment by educational attainment, since they provide information on both the labor market situation of individuals and their level of educational attainment. Such surveys can be designed to cover virtually the entire non- institutional population of a given country, all branches of economic activity, all sectors of the economy and all categories of workers, including the self-employed, contributing family workers, casual workers and multiple jobholders. In addition, such surveys generally provide an opportunity for the simultaneous measurement of the employed, the unemployed and persons outside the labor force (and thus, the working-age population) in a coherent framework. Other types of household surveys and population censuses could also be used as sources of data on employment by educational attainment. The information obtained from such sources may however be less reliable since they do not typically allow for detailed probing on the labor market activities of the respondents.\nStatistical concept(s): The unemployment rate conveys the number of persons who are unemployed as a percent of the labour force (i.e., the employed plus the unemployed). The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED.","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.TOTL.FE.ZS","name":"Chômage des femmes ( % de la population active féminine) (estimation modélisée de l'OIT)","description":"Le chômage fait référence à la part de la population active qui est sans travail mais disponible et à la recherche d'un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.TOTL.FE.ZS?locations=CI","methodology":"Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).\n\nThe working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.TOTL.FE.NE.ZS","name":"Chômage des femmes ( % de la population active féminine) (estimation nationale)","description":"Le chômage fait référence à la part de la population active qui est sans travail mais disponible et à la recherche d'un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.TOTL.FE.NE.ZS?locations=CI","methodology":"Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed. \n\nHousehold labor force surveys are generally the most comprehensive and comparable sources for unemployment statistics. Other possible sources include population censuses and official estimates. Administrative records such as employment office records and social insurance statistics are also sources of unemployment statistics; however, coverage in such sources is limited to “registered unemployed” only.\nStatistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).\n\nThe working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.TOTL.MA.ZS","name":"Chômage masculin ( % de la population active masculine) (estimation modélisée de l'OIT)","description":"Le chômage fait référence à la part de la population active qui est sans travail mais disponible et à la recherche d'un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.TOTL.MA.ZS?locations=CI","methodology":"Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).\n\nThe working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.TOTL.MA.NE.ZS","name":"Chômage masculin ( % de la population active masculine) (estimation nationale)","description":"Le chômage fait référence à la part de la population active qui est sans travail mais disponible et à la recherche d'un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.TOTL.MA.NE.ZS?locations=CI","methodology":"Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed. \n\nHousehold labor force surveys are generally the most comprehensive and comparable sources for unemployment statistics. Other possible sources include population censuses and official estimates. Administrative records such as employment office records and social insurance statistics are also sources of unemployment statistics; however, coverage in such sources is limited to “registered unemployed” only.\nStatistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.\n\n\n\n\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).\n\n\n\nThe working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.TOTL.ZS","name":"Chômage, total ( % de la population active totale) (estimation modélisée de l'OIT)","description":"Le chômage fait référence à la part de la population active qui est sans travail mais disponible et à la recherche d'un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.TOTL.ZS?locations=CI","methodology":"Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed. \n\n\n\n\n\n\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.\n\n\n\n\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).\n\n\n\nThe working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.TOTL.NE.ZS","name":"Chômage, total ( % de la population active totale) (estimation nationale)","description":"Le chômage fait référence à la part de la population active qui est sans travail mais disponible et à la recherche d'un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.TOTL.NE.ZS?locations=CI","methodology":"Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed. \n\nHousehold labor force surveys are generally the most comprehensive and comparable sources for unemployment statistics. Other possible sources include population censuses and official estimates. Administrative records such as employment office records and social insurance statistics are also sources of unemployment statistics; however, coverage in such sources is limited to “registered unemployed” only.\nStatistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).\n\nThe working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.1524.FE.ZS","name":"Chômage, jeunes femmes ( % de la main-d'œuvre féminine âgée de 15 à 24 ans) (estimation modélisée de l'OIT)","description":"Le chômage des jeunes fait référence à la part de la population active âgée de 15 à 24 ans sans travail mais disponible et à la recherche d'un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.1524.FE.ZS?locations=CI","methodology":"Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available.\nStatistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.\n\n\n\n\n\n\n\n\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).\n\n\n\n\n\nThe working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.1524.FE.NE.ZS","name":"Chômage, jeunes femmes ( % de la population active féminine âgée de 15 à 24 ans) (estimation nationale)","description":"Le chômage des jeunes fait référence à la part de la population active âgée de 15 à 24 ans sans travail mais disponible et à la recherche d'un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.1524.FE.NE.ZS?locations=CI","methodology":"Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed. \n\nHousehold labor force surveys are generally the most comprehensive and comparable sources for unemployment statistics. Other possible sources include population censuses and official estimates. Administrative records such as employment office records and social insurance statistics are also sources of unemployment statistics; however, coverage in such sources is limited to “registered unemployed” only.\nStatistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).\n\nThe working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.1524.MA.ZS","name":"Chômage, jeunes hommes ( % de la population active masculine âgée de 15 à 24 ans) (estimation modélisée de l'OIT)","description":"Le chômage des jeunes fait référence à la part de la population active âgée de 15 à 24 ans sans travail mais disponible et à la recherche d'un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.1524.MA.ZS?locations=CI","methodology":"Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).\n\nThe working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.1524.MA.NE.ZS","name":"Chômage, jeunes hommes ( % de la population active masculine âgée de 15 à 24 ans) (estimation nationale)","description":"Le chômage des jeunes fait référence à la part de la population active âgée de 15 à 24 ans sans travail mais disponible et à la recherche d'un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.1524.MA.NE.ZS?locations=CI","methodology":"Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed. \n\nHousehold labor force surveys are generally the most comprehensive and comparable sources for unemployment statistics. Other possible sources include population censuses and official estimates. Administrative records such as employment office records and social insurance statistics are also sources of unemployment statistics; however, coverage in such sources is limited to “registered unemployed” only.\nStatistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).\n\nThe working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.1524.ZS","name":"Chômage, total des jeunes ( % de la population active totale âgée de 15 à 24 ans) (estimation modélisée de l'OIT)","description":"Le chômage des jeunes fait référence à la part de la population active âgée de 15 à 24 ans sans travail mais disponible et à la recherche d'un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.1524.ZS?locations=CI","methodology":"Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.\n\n\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).\n\nThe working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).","theme":"emploi","source_group":"wb"},{"code":"SL.UEM.1524.NE.ZS","name":"Chômage, total des jeunes ( % de la population active totale âgée de 15 à 24 ans) (estimation nationale)","description":"Le chômage des jeunes fait référence à la part de la population active âgée de 15 à 24 ans sans travail mais disponible et à la recherche d'un emploi.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.UEM.1524.NE.ZS?locations=CI","methodology":"Methodology: The unemployment rate is calculated by expressing the number of unemployed persons as a percentage of the total number of persons in the labor force. The labor force (formerly known as the economically active population) is the sum of the number of persons employed and the number of persons unemployed. \n\nHousehold labor force surveys are generally the most comprehensive and comparable sources for unemployment statistics. Other possible sources include population censuses and official estimates. Administrative records such as employment office records and social insurance statistics are also sources of unemployment statistics; however, coverage in such sources is limited to “registered unemployed” only.\nStatistical concept(s): The unemployed comprise all persons of working age who were: a) without work during the reference period, i.e. were not in paid employment or self-employment; b) currently available for work, i.e. were available for paid employment or self-employment during the reference period; and c) seeking work, i.e. had taken specific steps in a specified recent period to seek paid employment or self-employment. Future starters, that is, persons who did not look for work but have a future labor market stake (made arrangements for a future job start) are also counted as unemployed, as are participants in skills training or retraining schemes within employment promotion programs, who on that basis, were “not in employment”, not “currently available” and did not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months. The unemployed also include persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.\n\nEmployment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).\n\nThe working-age population is the population above the legal working age, but for statistical purposes it comprises all persons above a specified minimum age threshold for which an inquiry on economic activity is made. To promote international comparability, the working-age population is often defined as all persons aged 15 and older, but this may vary from country to country based on national laws and practices (some countries also apply an upper age limit).","theme":"emploi","source_group":"wb"},{"code":"SP.UWT.TFRT","name":"Besoins non satisfaits en matière de contraception ( % des femmes mariées âgées de 15 à 49 ans)","description":"Le besoin non satisfait en matière de contraception correspond au pourcentage de femmes fertiles et mariées en âge de procréer qui ne souhaitent pa...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.UWT.TFRT?locations=CI","methodology":"Methodology: Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.\nMany couples in developing countries want to limit or postpone childbearing but are not using effective contraception. These couples have an unmet need for contraception. Common reasons are lack of knowledge about contraceptive methods and concerns about possible side effects. This indicator excludes women not exposed to the risk of unintended pregnancy because of menopause, infertility, or postpartum anovulation.","theme":"sante","source_group":"wb"},{"code":"AG.LND.TOTL.UR.K2","name":"Superficie des terres urbaines (km²)","description":"Superficie urbaine en kilomètres carrés, basée sur une combinaison de chiffres de population (personnes), de points d'habitation et de présence d'é...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.TOTL.UR.K2?locations=CI","methodology":"Methodology: The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) urban extent grid distinguishes urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights . Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons. This dataset is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (CIAT)","theme":"primary","source_group":"wb"},{"code":"AG.LND.EL5M.UR.ZS","name":"Superficie urbaine dont l'altitude est inférieure à 5 mètres ( % de la superficie totale du terrain)","description":"La superficie des terres urbaines inférieure à 5 m correspond au pourcentage de la superficie totale des terres dont l'élévation des terres urbaine...","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.EL5M.UR.ZS?locations=CI","methodology":"Methodology: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).","theme":"primary","source_group":"wb"},{"code":"AG.LND.EL5M.UR.K2","name":"Superficie urbaine dont l'altitude est inférieure à 5 mètres (km²)","description":"La superficie urbaine inférieure à 5 m correspond à la superficie urbaine totale en kilomètres carrés dont l'élévation est de 5 mètres ou moins.","source_link":"https://donnees.banquemondiale.org/indicateur/AG.LND.EL5M.UR.K2?locations=CI","methodology":"Methodology: Elevation data used to generate the low elevation coastal zones come from the SRTM3 Enhanced Global Map developed by ISCIENCES. The ISCIENCES digital elevation model was created using NASA’s Jet Propulsion Laboratory Shuttle Radar Topography Mission data processed to 3 arc-seconds (SRTM3).","theme":"primary","source_group":"wb"},{"code":"SP.URB.TOTL","name":"Population urbaine","description":"La population urbaine fait référence aux personnes vivant dans les zones urbaines telles que définies par les bureaux nationaux de statistique.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.URB.TOTL?locations=CI","methodology":"Methodology: The indicator is calculated using World Bank's total population estimates and urban ratios from the United Nations World Urbanization Prospects.\nStatistical concept(s): Urban population refers to people living in urban areas as defined by national statistical offices. Particular caution should be used in interpreting the figures for percentage urban for different countries. Countries differ in the way they classify population as \"urban\" or \"rural.\" The population of a city or metropolitan area depends on the boundaries chosen.","theme":"demo","source_group":"wb"},{"code":"SP.URB.TOTL.IN.ZS","name":"Population urbaine ( % de la population totale)","description":"La population urbaine fait référence aux personnes vivant dans les zones urbaines telles que définies par les bureaux nationaux de statistique.","source_link":"https://donnees.banquemondiale.org/indicateur/SP.URB.TOTL.IN.ZS?locations=CI","methodology":"Methodology: Percentages urban are the numbers of persons residing in an area defined as ''urban'' per 100 total population.\nStatistical concept(s): Urban population refers to people living in urban areas as defined by national statistical offices. Particular caution should be used in interpreting the figures for percentage urban for different countries. Countries differ in the way they classify population as \"urban\" or \"rural.\" The population of a city or metropolitan area depends on the boundaries chosen.","theme":"demo","source_group":"wb"},{"code":"SP.URB.GROW","name":"Croissance de la population urbaine ( % annuel)","description":"Le taux de croissance annuel de la population urbaine pour l’année t est le taux exponentiel de croissance de la population urbaine en milieu d’ann...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.URB.GROW?locations=CI","methodology":"Methodology: The indicator is calculated from urban population estimates. The urban population estimates are calulcated using World Bank's total population estimates and urban ratios from the United Nations World Urbanization Prospects.\nThe growth rate is computed using the exponential growth formula:\nr = ln(pn/p0)/n, \nwhere r is the exponential rate of growth, ln() is the natural logarithm, pn is the end period population, p0 is the beginning period population, and n is the number of years in between. Note that this is not the geometric growth rate used to compute compound growth over discrete periods.\nStatistical concept(s): Urban population refers to people living in urban areas as defined by national statistical offices. Particular caution should be used in interpreting the figures for percentage urban for different countries. Countries differ in the way they classify population as \"urban\" or \"rural.\" The population of a city or metropolitan area depends on the boundaries chosen.","theme":"demo","source_group":"wb"},{"code":"EN.POP.EL5M.UR.ZS","name":"Population urbaine vivant dans des zones où l'altitude est inférieure à 5 mètres ( % de la population totale)","description":"La population urbaine de moins de 5 m est le pourcentage de la population totale vivant dans des zones où l'altitude est de 5 mètres ou moins.","source_link":"https://donnees.banquemondiale.org/indicateur/EN.POP.EL5M.UR.ZS?locations=CI","methodology":"Methodology: Population counts in low elevation zones in the year 1990 as described by GRUMPv1 input estimates allocated into 3 arc second grid cells. Population counts in low elevation zones in the year 2000 as described by GRUMPv1 input estimates allocated into 3 arc second grid cells. Population counts in low elevation zones in the year 2010 derived from the application of United Nations 2000-2010 national growth rates to year 2000 population data from GRUMPv1 ( see documentation for full description of methodologies ).","theme":"demo","source_group":"wb"},{"code":"DT.DOD.DIMF.CD","name":"Utilisation du crédit du FMI (DOD, dollars américains courants)","description":"Utilisation du crédit du FMI : Les données relatives aux opérations du FMI sont fournies par le Département du Trésorier du FMI.","source_link":"https://donnees.banquemondiale.org/indicateur/DT.DOD.DIMF.CD?locations=CI","methodology":"Methodology: Data related to the operations of the IMF come from the IMF Treasurer's Department and are converted from special drawing rights (SDRs) into dollars using end-of-period exchange rates for stocks and average over the period exchange rates for converting flows. DOD refers to disbursed and outstanding debt; data are in current U.S. dollars.\n\nData on external debt are gathered through the World Bank's Debtor Reporting System (DRS). Long term debt data are compiled using the countries report on public and publicly guaranteed borrowing on a loan-by-loan basis and private non guaranteed borrowing on an aggregate basis. These data are supplemented by information from major multilateral banks and official lending agencies in major creditor countries. Short-term debt data are gathered from the Quarterly External Debt Statistics (QEDS) database, jointly developed by the World Bank and the IMF and from creditors through the reporting systems of the Bank for International Settlements. Debt data are reported in the currency of repayment and compiled and published in U.S. dollars. End-of-period exchange rates are used for the compilation of stock figures (amount of debt outstanding), and projected debt service and annual average exchange rates are used for the flows. Exchange rates are taken from the IMF's International Financial Statistics. Debt repayable in multiple currencies, goods, or services and debt with a provision for maintenance of the value of the currency of repayment are shown at book value.","theme":"finance","source_group":"wb"},{"code":"SH.MLR.NETS.ZS","name":"Utilisation de moustiquaires imprégnées d'insecticide ( % de la population de moins de 5 ans)","description":"L'utilisation de moustiquaires imprégnées d'insecticide fait référence au pourcentage d'enfants de moins de cinq ans qui ont dormi sous une moustiq...","source_link":"https://donnees.banquemondiale.org/indicateur/SH.MLR.NETS.ZS?locations=CI","methodology":"Methodology: Malaria is endemic to the poorest countries in the world, mainly in tropical and subtropical regions of Africa, Asia, and the Americas. Insecticide-treated nets, properly used and maintained, are one of the most important malaria-preventive strategies to limit human-mosquito contact.","theme":"sante","source_group":"wb"},{"code":"IC.FRM.OUTG.ZS","name":"Valeur perdue en raison de pannes d'électricité ( % du chiffre d'affaires des entreprises touchées)","description":"Pertes dues aux pannes d'électricité, en pourcentage du chiffre d'affaires annuel total.","source_link":"https://donnees.banquemondiale.org/indicateur/IC.FRM.OUTG.ZS?locations=CI","methodology":"Firm-level surveys have been conducted since the 1990's by different units within the World Bank. Since 2005-06, most data collection efforts have been centralized within the Enterprise Analysis Unit. Surveys implemented by the Enterprise Analysis Unit follow the Global Methodology.\n\nPrivate contractors conduct the Enterprise Surveys on behalf of the World Bank. Due to sensitive survey questions addressing business-government relations and bribery-related topics, private contractors, rather than any government agency or an organization/institution associated with government, are hired by the World Bank to collect the data.\n\nConfidentiality of the survey respondents and the sensitive information they provide is necessary to ensure the greatest degree of survey participation, integrity and confidence in the quality of the data. Surveys are usually carried out in cooperation with business organizations and government agencies promoting job creation and economic growth, but confidentiality is never compromised.\n\nThe Enterprise Survey is answered by business owners and top managers. Sometimes the survey respondent calls company accountants and human resource managers into the interview to answer questions in the sales and labor sections of the survey. Typically 1200-1800 interviews are conducted in larger economies, 360 interviews are conducted in medium-sized economies, and for smaller economies, 150 interviews take place.\n\nThe manufacturing and services sectors are the primary business sectors of interest. This corresponds to firms classified with ISIC codes 15-37, 45, 50-52, 55, 60-64, and 72 (ISIC Rev.3.1). Formal (registered) companies with 5 or more employees are targeted for interview. Services firms include construction, retail, wholesale, hotels, restaurants, transport, storage, communications, and IT. Firms with 100% government/state ownership are not eligible to participate in an Enterprise Survey. Occasionally, for a few surveyed countries, other sectors are included in the companies surveyed such as education or health-related businesses. In each country, businesses in the cities/regions of major economic activity are interviewed.\n\nIn some countries, other surveys, which depart from the usual Enterprise Survey methodology, are conducted. Examples include 1) Informal Surveys- surveys of informal (unregistered) enterprises, 2) Micro Surveys- surveys fielded to registered firms with less than five employees, and 3) Financial Crisis Assessment Surveys- short surveys administered by telephone to assess the effects of the global financial crisis of 2008-09.\n\nThe Enterprise Surveys Unit uses two instruments: the Manufacturing Questionnaire and the Services Questionnaire. Although many questions overlap, some are only applicable to one type of business. For example, retail firms are not asked about production and nonproduction workers.\n\nThe standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures.\n\nOver 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance. The mode of data collection is face-to-face interviews.","theme":"business","source_group":"wb"},{"code":"SN.ITK.VITA.ZS","name":"Taux de couverture de la supplémentation en vitamine A ( % des enfants âgés de 6 à 59 mois)","description":"Le taux de couverture de la supplémentation en vitamine A fait référence au pourcentage d’enfants âgés de 6 à 59 mois recevant deux suppléments de ...","source_link":"https://donnees.banquemondiale.org/indicateur/SN.ITK.VITA.ZS?locations=CI","methodology":"Methodology: Household Surveys including DHS, MICS and other national surveys\nStatistical concept(s): The World Health Organization has classified vitamin A deficiency as a public health problem affecting many children ages 6-59 months, with the highest rates in sub-Saharan Africa and South Asia.","theme":"sante","source_group":"wb"},{"code":"VA.EST","name":"Voix et responsabilité : estimation","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/VA.EST?locations=CI","methodology":"","theme":"politique","source_group":"wb"},{"code":"VA.NO.SRC","name":"Voix et responsabilité : nombre de sources","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/VA.NO.SRC?locations=CI","methodology":"Methodology: The WGI are composite governance indicators based on over 30 underlying data sources. \n\nThe WGI compile and summarize information from over 30 existing data sources that report the views and experiences of citizens, entrepreneurs, and experts in the public, private and NGO sectors from around the world, on the quality of various aspects of governance.\n\n•\tThe data sources must provide subjective perceptions of relevant dimensions of governance, as the WGI are based exclusively on this type of data.\n•\tThe sources must provide original primary data produced using a well-defined methodology.\n•\tThe data sources must cover multiple countries, so that cross-country comparisons are possible.\n•\tThe data sources must be updated regularly, ideally every year, although some WGI data sources are updated once every two or three years.\n\nThe WGI draw on four different types of source data:\n\n•\tSurveys of households and firms, including the Afrobarometer surveys, Gallup World Poll, and Global Competitiveness Report survey,\n•\tCommercial business information providers, including the Economist Intelligence Unit, S&P Global, and Political Risk Services,\n•\tNon-governmental organizations, including Global Integrity, Freedom House, Reporters Without Borders, and\n•\tPublic sector organizations, including the Country Policy and Institutional Assessments (CPIA) assessments of World Bank and regional development banks.\n\nFor the detailed list of sources, please refer to: https://www.worldbank.org/en/publication/worldwide-governance-indicators/documentation#2  \n\nStatistical concept(s): Number of sources indicates the number of underlying data sources on which the aggregate estimate is based.\n\nVariables from the data sources are assigned to each of these six governance dimensions.  For example, an assessment of the quality of the bureaucracy would be assigned to Government Effectiveness, a question about confidence in the police or the courts would be assigned to Rule of Law, and a question about the perceived likelihood of having to pay a bribe would be assigned to Control of Corruption.  In some cases, a single data source will have multiple questions that can be assigned to the same dimension.  In this case, the WGI use the average across all relevant questions from that data source. In addition each question from each data source is assigned to only one of the six governance dimensions, selecting the dimension that best matches the content of the question.","theme":"politique","source_group":"wb"},{"code":"VA.PER.RNK","name":"Voix et responsabilité : rang centile","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/VA.PER.RNK?locations=CI","methodology":"","theme":"politique","source_group":"wb"},{"code":"VA.PER.RNK.LOWER","name":"Voix et responsabilité : rang centile, limite inférieure de l'intervalle de confiance à 90 %","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/VA.PER.RNK.LOWER?locations=CI","methodology":"Methodology: A key feature of the WGI is that all country scores are accompanied by standard errors. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether.\n\nThe standard deviations are essential to the interpretation of the WGI.  It often is more appropriate to think of the WGI methodology as identifying a statistically likely range of values for the unobserved “true” level of governance in a country.  For example, the assumption of normality tells us that there is a 90 percent probability that the true unobserved level of governance conditional on the available data for a country is in a range given by plus or minus 1.64 standard deviations around the estimate of governance. These confidence intervals are informally referred to as the “margin of error” around the estimates of governance.\n\nThese 90 percent confidence interval are also reported in percentile rank terms (the percentile rank among all country estimates of governance, of the upper and lower bounds of the 90 percent confidence interval for each country).\nStatistical concept(s): Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank.  Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.  \n\nPercentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.","theme":"politique","source_group":"wb"},{"code":"VA.PER.RNK.UPPER","name":"Voix et responsabilité : rang centile, limite supérieure de l'intervalle de confiance à 90 %","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/VA.PER.RNK.UPPER?locations=CI","methodology":"Methodology: A key feature of the WGI is that all country scores are accompanied by standard errors. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether.\n\nThe standard deviations are essential to the interpretation of the WGI.  It often is more appropriate to think of the WGI methodology as identifying a statistically likely range of values for the unobserved “true” level of governance in a country.  For example, the assumption of normality tells us that there is a 90 percent probability that the true unobserved level of governance conditional on the available data for a country is in a range given by plus or minus 1.64 standard deviations around the estimate of governance. These confidence intervals are informally referred to as the “margin of error” around the estimates of governance.\n\nThese 90 percent confidence interval are also reported in percentile rank terms (the percentile rank among all country estimates of governance, of the upper and lower bounds of the 90 percent confidence interval for each country).\nStatistical concept(s): Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. \n\nPercentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.","theme":"politique","source_group":"wb"},{"code":"VA.STD.ERR","name":"Voix et responsabilité : l'erreur type","description":"Les Indicateurs mondiaux de gouvernance (WGI) sont un ensemble de données de recherche résumant les opinions sur la qualité de la gouvernance fourn...","source_link":"https://donnees.banquemondiale.org/indicateur/VA.STD.ERR?locations=CI","methodology":"Methodology: The WGI are composite governance indicators based on over 30 underlying data sources. These data sources are rescaled and combined to create the six aggregate indicators using a statistical methodology known as an Unobserved Components Model (UCM). The six aggregate indicators are reported in two ways : (1) in their standard normal units, ranging from approximately -2.5 to 2.5, and (2) in percentile rank terms from 0 to 100, with higher values corresponding to better outcomes.\n\nA key feature of the WGI is that all country scores are accompanied by standard errors. These margins of error need to be taken into account when making comparisons across countries and over time. These standard errors reflect the number of sources available for a country and the extent to which these sources agree with each other (with more sources and more agreement leading to smaller standard errors). These standard errors reflect the reality that governance is difficult to measure using any kind of data. In most measures of governance or the investment climate they are however left implicit or ignored altogether. \n\nPlease see more information at: https://www.worldbank.org/en/publication/worldwide-governance-indicators/documentation#1\nStatistical concept(s): Standard error indicates the precision of the estimate of governance. Larger values of the standard error indicate less precise estimates. A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.","theme":"politique","source_group":"wb"},{"code":"SL.EMP.VULN.FE.ZS","name":"Emploi vulnérable, femmes ( % de l'emploi féminin) (estimation modélisée de l'OIT)","description":"L’emploi vulnérable concerne les travailleurs familiaux et les travailleurs indépendants en pourcentage de l’emploi total.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.VULN.FE.ZS?locations=CI","methodology":"Methodology: The proportion of vulnerable employment to the total employed is calculated as follows: (Contributing family workers + own-account workers)/Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.VULN.MA.ZS","name":"Emploi vulnérable, hommes ( % de l'emploi masculin) (estimation modélisée de l'OIT)","description":"L’emploi vulnérable concerne les travailleurs familiaux et les travailleurs indépendants en pourcentage de l’emploi total.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.VULN.MA.ZS?locations=CI","methodology":"Methodology: The proportion of vulnerable employment to the total employed is calculated as follows: (Contributing family workers + own-account workers)/Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.VULN.ZS","name":"Emploi vulnérable, total ( % de l'emploi total) (estimation modélisée de l'OIT)","description":"L’emploi vulnérable concerne les travailleurs familiaux et les travailleurs indépendants en pourcentage de l’emploi total.","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.VULN.ZS?locations=CI","methodology":"Methodology: The proportion of vulnerable employment to the total employed is calculated as follows: (Contributing family workers + own-account workers)/Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.WORK.FE.ZS","name":"Salariés, femmes ( % de l'emploi féminin) (estimation modélisée de l'OIT)","description":"Les travailleurs salariés (employés) sont les travailleurs qui occupent le type d'emplois définis comme des « emplois rémunérés », dans lesquels le...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.WORK.FE.ZS?locations=CI","methodology":"Methodology: The proportion of wage and salaried workers to the total employed is calculated as follows: Wage and salaried workers /Total employment x 100. \n\n\n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.WORK.MA.ZS","name":"Salariés masculins ( % de l'emploi masculin) (estimation modélisée de l'OIT)","description":"Les travailleurs salariés (employés) sont les travailleurs qui occupent le type d'emplois définis comme des « emplois rémunérés », dans lesquels le...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.WORK.MA.ZS?locations=CI","methodology":"Methodology: The proportion of wage and salaried workers to the total employed is calculated as follows: Wage and salaried workers /Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SL.EMP.WORK.ZS","name":"Salariés (en % de l'emploi total) (estimation modélisée de l'OIT)","description":"Les travailleurs salariés (employés) sont les travailleurs qui occupent le type d'emplois définis comme des « emplois rémunérés », dans lesquels le...","source_link":"https://donnees.banquemondiale.org/indicateur/SL.EMP.WORK.ZS?locations=CI","methodology":"Methodology: The proportion of wage and salaried workers to the total employed is calculated as follows: Wage and salaried workers /Total employment x 100. \n\nThe series is part of the \"ILO modeled estimates database,\" including nationally reported observations and imputed data for countries with missing data, primarily to capture regional and global trends with consistent country coverage. Country-reported microdata is based mainly on nationally representative labor force surveys, with other sources (e.g., household surveys and population censuses) considering differences in the data source, the scope of coverage, methodology, and other country-specific factors. Country analysis requires caution where limited nationally reported data are available. A series of models are also applied to impute missing observations and make projections. However, imputed observations are not based on national data, are subject to high uncertainty, and should not be used for country comparisons or rankings. For more information: https://ilostat.ilo.org/resources/concepts-and-definitions/ilo-modelled-estimates/\nStatistical concept(s): The status in employment distinguishes between two categories of the total employed: (a) wage and salaried workers (also known as employees); and (b) self-employed workers, with the subcategories: (i) self-employed workers with employees (employers), (ii) self-employed workers without employees (own-account workers), and (iii) members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of (ii) own-account workers and (iii) contributing family workers.","theme":"emploi","source_group":"wb"},{"code":"SP.DYN.WFRT","name":"Taux de fécondité souhaité (naissances par femme)","description":"L’indice de fécondité souhaitée est une estimation de ce que serait l’indice synthétique de fécondité si toutes les naissances non désirées étaient...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.DYN.WFRT?locations=CI","methodology":"Methodology: The data is calculated by summing the seven age-specific wanted fertility rates, multiplying the result by five, and dividing by 1000.   A birth is considered wanted if the number of living children at the time of conception is less than the ideal number of children as reported by the respondent. Special responses such as \"don't know,\" \"up to God,\" or other non-numeric responses for the ideal number of children are assumed to indicate a high ideal number of children. For more details, please refer to the DHS website: https://dhsprogram.com/data/Guide-to-DHS-Statistics/Wanted_Fertility.htm","theme":"demo","source_group":"wb"},{"code":"ER.GDP.FWTL.M3.KD","name":"Productivité de l'eau, totale (PIB en dollars américains constants de 2015 par mètre cube de prélèvement total d'eau douce)","description":"La productivité de l’eau est calculée comme le PIB en prix constants divisé par le prélèvement total annuel d’eau.","source_link":"https://donnees.banquemondiale.org/indicateur/ER.GDP.FWTL.M3.KD?locations=CI","methodology":"Methodology: Water productivity is an indication only of the efficiency by which each country uses its water resources. Given the different economic structure of each country, these indicators should be used carefully, taking into account a country's sectorial activities and natural resource endowments. GDP data are from World Bank's national accounts files\nWater withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where water reuse is significant. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including for cooling thermoelectric plants).\nStatistical concept(s):","theme":"territory","source_group":"wb"},{"code":"FP.WPI.TOTL","name":"Indice des prix de gros (2010 = 100)","description":"Indice des prix d'un mélange de biens agricoles et industriels à différents stades de production et de distribution, y compris les droits d'importa...","source_link":"https://donnees.banquemondiale.org/indicateur/FP.WPI.TOTL?locations=CI","methodology":"Methodology: Wholesale Prices Indices are compiled in accordance with international standards: Producer Price Index Manual, 2004 version. Specific information on how countries compile their WPI statistics can be found on the IMF website: https://dsbb.imf.org/\nStatistical concept(s): The conceptual basis of a wholesale price index series is to measure the rate at which prices of goods and services are changing from one period to another, for products that flow from a wholesaler to a retailer.","theme":"macro","source_group":"wb"},{"code":"SG.LAW.INDX","name":"Indice des femmes d'affaires et du droit (échelle de 1 à 100)","description":"L’indice mesure l’impact des lois et réglementations sur les opportunités économiques des femmes.","source_link":"https://donnees.banquemondiale.org/indicateur/SG.LAW.INDX?locations=CI","methodology":"Methodology: Thirty-five data points are scored across eight indicators (Mobility, Workplace, Pay, Marriage, Parenthood, Entrepreneurship, Assets and Pension) of four or five binary questions, with each indicator representing a different phase of a woman’s career. Indicator-level scores are obtained by calculating the unweighted average of the questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking the average of each indicator, with 100 representing the highest possible score.\nStatistical concept(s): Women, Business and the Law tracks progress toward legal equality between men and women in 190 economies. Data are collected with standardized questionnaires to ensure comparability across economies. Questionnaires are administered to over 2,000 respondents with expertise in family, labor, and violence against women legislation, including lawyers, judges, academics, and members of civil society organizations working on gender issues. Respondents provide responses to the questionnaires and references to relevant laws and regulations. The Women, Business and the Law team collects the texts of these codified sources of national law - constitutions, codes, laws, statutes, rules, regulations, and procedures - and checks questionnaire responses for accuracy.","theme":"social","source_group":"wb"},{"code":"SG.DMK.SRCR.FN.ZS","name":"Femmes prenant leurs propres décisions éclairées concernant les relations sexuelles, l'utilisation de contraceptifs et les soins de santé reproductive ( % de femmes âgées de 15 à 49 ans)","description":"Proportion de femmes âgées de 15 à 49 ans (mariées ou en union) qui prennent leur propre décision dans les trois domaines sélectionnés, c'est-à-dir...","source_link":"https://donnees.banquemondiale.org/indicateur/SG.DMK.SRCR.FN.ZS?locations=CI","methodology":"Methodology: Numerator of the indicator is number of married or in union women ages 15-49 who have been interviewed and satisfy all three empowerment criteria: 1)who can say 'no' to sex; and 2)for whom the decision on contraception is not mainly made by the husband/partner; and 3) for whom decision on health care for themselves ins not usually made by the husband/partner or someone else.  Denominator of the indicator is the total number of women ages 15-49 who are married or in union and who have been interviewed.  \n\n\n\n\n\n\n\n\n\n\n\n\n\nThe data for this indicator are primarily sourced from nationally representative Demographic and Health Surveys (DHS).\nStatistical concept(s): A woman is deemed to possess autonomy in reproductive health decision-making and to be empowered to assert her reproductive rights when she has the ability to: (1) make decisions regarding her own health care, independently or in conjunction with her husband or partner, (2) determine the use or non-use of contraception, on her own or together with her husband or partner, and (3) refuse sexual relations with her husband or partner if she chooses.","theme":"social","source_group":"wb"},{"code":"SG.DMK.ALLD.FN.ZS","name":"Les femmes participent aux trois décisions (soins de santé propres, achats importants du ménage et visites à la famille) ( % des femmes âgées de 15 à 49 ans)","description":"Les femmes participant aux trois décisions (soins de santé, achats importants du ménage et visites à la famille) représentent le pourcentage de fem...","source_link":"https://donnees.banquemondiale.org/indicateur/SG.DMK.ALLD.FN.ZS?locations=CI","methodology":"Methodology: Women participating in the three decisions (own health care, major household purchases, and visiting family) is the number of currently married women aged 15-49 who say they alone or jointly have the final say in the three decisions, expressed as percentage of currently married women age 15-49 who have been interviewed and It’s derived by dividing the number of currently married women aged 15-49 who responded they alone or jointly have the final say in the three decisions by total number of currently married women age 15-49 who have been interviewed.\nStatistical concept(s): This indicator assesses the level of women's participation in household decision-making. It emphasizes the importance of decisions regarding their own health care, which are deemed essential to women's self-interest. The indicator also evaluates women's involvement in making substantial economic decisions, such as those related to significant purchases, to gauge their economic decision-making power within the household. Additionally, it measures women's autonomy in deciding on visits to family or friends, which can indicate their freedom of movement and the ability to engage with their birth family.","theme":"social","source_group":"wb"},{"code":"SG.VAW.REAS.ZS","name":"Femmes qui croient qu'un mari a raison de battre sa femme (l'une des cinq raisons) ( %)","description":"Pourcentage de femmes âgées de 15 à 49 ans qui pensent qu'un mari/partenaire est justifié de frapper ou de battre sa femme/partenaire pour l'une de...","source_link":"https://donnees.banquemondiale.org/indicateur/SG.VAW.REAS.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by dividing the number of women ages 15-49 who agree that a husband is justified in hitting or beating his wife when she burns the food by total number of women ages 15-49 who have been interviewed.  The data for this indicator are sourced from Demographic and Health Surveys (DHS).\nStatistical concept(s): This indicator is one of the sets of attitude questions concerning justifications of a husband beating his wife in Demographic and Health Surveys. These questions aim to understand women's perspectives on gender equality.  Acceptance of wife beating indicates an underlying acceptance of a lower status for women.","theme":"social","source_group":"wb"},{"code":"SG.VAW.ARGU.ZS","name":"Femmes qui croient qu'un mari a raison de battre sa femme lorsqu'elle se dispute avec lui ( %)","description":"Pourcentage de femmes âgées de 15 à 49 ans qui pensent qu'un mari/partenaire a raison de frapper ou de battre sa femme/partenaire lorsqu'elle se di...","source_link":"https://donnees.banquemondiale.org/indicateur/SG.VAW.ARGU.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by dividing the number of women ages 15-49 who agree that a husband is justified in hitting or beating his wife when she burns the food by total number of women ages 15-49 who have been interviewed.  The data for this indicator are sourced from Demographic and Health Surveys (DHS).\nStatistical concept(s): This indicator is one of the sets of attitude questions concerning justifications of a husband beating his wife in Demographic and Health Surveys. These questions aim to understand women's perspectives on gender equality.  Acceptance of wife beating indicates an underlying acceptance of a lower status for women.","theme":"social","source_group":"wb"},{"code":"SG.VAW.BURN.ZS","name":"Femmes qui pensent qu'un mari a raison de battre sa femme lorsqu'elle brûle la nourriture ( %)","description":"Pourcentage de femmes âgées de 15 à 49 ans qui pensent qu'un mari/partenaire est justifié de frapper ou de battre sa femme/partenaire lorsqu'elle b...","source_link":"https://donnees.banquemondiale.org/indicateur/SG.VAW.BURN.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by dividing the number of women ages 15-49 who agree that a husband is justified in hitting or beating his wife when she burns the food by total number of women ages 15-49 who have been interviewed.  The data for this indicator are sourced from Demographic and Health Surveys (DHS).\nStatistical concept(s): This indicator is one of the sets of attitude questions concerning justifications of a husband beating his wife in Demographic and Health Surveys. These questions aim to understand women's perspectives on gender equality.  Acceptance of wife beating indicates an underlying acceptance of a lower status for women.","theme":"social","source_group":"wb"},{"code":"SG.VAW.GOES.ZS","name":"Femmes qui croient qu'un mari a raison de battre sa femme lorsqu'elle sort sans le lui dire ( %)","description":"Pourcentage de femmes âgées de 15 à 49 ans qui pensent qu'un mari/partenaire est justifié de frapper ou de battre sa femme/partenaire lorsqu'elle s...","source_link":"https://donnees.banquemondiale.org/indicateur/SG.VAW.GOES.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by dividing the number of women ages 15-49 who agree that a husband is justified in hitting or beating his wife when she burns the food by total number of women ages 15-49 who have been interviewed.  The data for this indicator are sourced from Demographic and Health Surveys (DHS).\nStatistical concept(s): This indicator is one of the sets of attitude questions concerning justifications of a husband beating his wife in Demographic and Health Surveys. These questions aim to understand women's perspectives on gender equality.  Acceptance of wife beating indicates an underlying acceptance of a lower status for women.","theme":"social","source_group":"wb"},{"code":"SG.VAW.NEGL.ZS","name":"Femmes qui pensent qu'un mari a raison de battre sa femme lorsqu'elle néglige les enfants ( %)","description":"Pourcentage de femmes âgées de 15 à 49 ans qui pensent qu'un mari/partenaire est justifié de frapper ou de battre sa femme/partenaire lorsqu'elle n...","source_link":"https://donnees.banquemondiale.org/indicateur/SG.VAW.NEGL.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by dividing the number of women ages 15-49 who agree that a husband is justified in hitting or beating his wife when she burns the food by total number of women ages 15-49 who have been interviewed.  The data for this indicator are sourced from Demographic and Health Surveys (DHS).\nStatistical concept(s): This indicator is one of the sets of attitude questions concerning justifications of a husband beating his wife in Demographic and Health Surveys. These questions aim to understand women's perspectives on gender equality.  Acceptance of wife beating indicates an underlying acceptance of a lower status for women.","theme":"social","source_group":"wb"},{"code":"SG.VAW.REFU.ZS","name":"Femmes qui pensent qu'un mari a raison de battre sa femme lorsqu'elle refuse d'avoir des rapports sexuels avec lui ( %)","description":"Pourcentage de femmes âgées de 15 à 49 ans qui pensent qu'un mari/partenaire est justifié de frapper ou de battre sa femme/partenaire lorsqu'elle r...","source_link":"https://donnees.banquemondiale.org/indicateur/SG.VAW.REFU.ZS?locations=CI","methodology":"Methodology: This indicator is calculated by dividing the number of women ages 15-49 who agree that a husband is justified in hitting or beating his wife when she burns the food by total number of women ages 15-49 who have been interviewed.  The data for this indicator are sourced from Demographic and Health Surveys (DHS).\nStatistical concept(s): This indicator is one of the sets of attitude questions concerning justifications of a husband beating his wife in Demographic and Health Surveys. These questions aim to understand women's perspectives on gender equality.  Acceptance of wife beating indicates an underlying acceptance of a lower status for women.","theme":"social","source_group":"wb"},{"code":"SP.M15.2024.FE.ZS","name":"Femmes mariées pour la première fois à l'âge de 15 ans ( % des femmes âgées de 20 à 24 ans)","description":"Les femmes mariées pour la première fois à l’âge de 15 ans font référence au pourcentage de femmes âgées de 20 à 24 ans qui se sont mariées pour la...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.M15.2024.FE.ZS?locations=CI","methodology":"Methodology: Number of women aged 20-24 who were first married or in union before age 15 divided by the total number of women aged 20-24 in the population multiplied by 100. The primary sources for this indicator are the Multiple Indicator Cluster Surveys (MICS) and the Demographic and Health Surveys (DHS). Additionally, other national household surveys and censuses contribute to the data. These figures are compiled by UNICEF, which coordinates with countries to gather the information.\nStatistical concept(s): This indicator includes both formal marriages and informal cohabiting relationships. Informal relationships are usually defined as those where a couple lives together with the intention of a long-term relationship but without a formal civil or religious ceremony. The incidence of child marriage is assessed retrospectively among women who are past the risk of marrying as children. The age range of 20 to 24 years is conventionally used to reflect the current prevalence of child marriage.","theme":"social","source_group":"wb"},{"code":"SP.M18.2024.FE.ZS","name":"Femmes mariées pour la première fois à l'âge de 18 ans ( % des femmes âgées de 20 à 24 ans)","description":"Les femmes mariées pour la première fois à 18 ans font référence au pourcentage de femmes âgées de 20 à 24 ans qui se sont mariées pour la première...","source_link":"https://donnees.banquemondiale.org/indicateur/SP.M18.2024.FE.ZS?locations=CI","methodology":"Methodology: Number of women aged 20-24 who were first married or in union before age 18 divided by the total number of women aged 20-24 in the population multiplied by 100. The primary sources for this indicator are the Multiple Indicator Cluster Surveys (MICS) and the Demographic and Health Surveys (DHS). Additionally, other national household surveys and censuses contribute to the data. These figures are compiled by UNICEF, which coordinates with countries to gather the information.\nStatistical concept(s): This indicator includes both formal marriages and informal cohabiting relationships. Informal relationships are usually defined as those where a couple lives together with the intention of a long-term relationship but without a formal civil or religious ceremony. The incidence of child marriage is assessed retrospectively among women who are past the risk of marrying as children. The age range of 20 to 24 years is conventionally used to reflect the current prevalence of child marriage.","theme":"social","source_group":"wb"},{"code":"SH.DYN.AIDS.FE.ZS","name":"Part des femmes dans la population âgée de 15 ans et + vivant avec le VIH ( %)","description":"La prévalence du VIH est le pourcentage de personnes infectées par le VIH.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.DYN.AIDS.FE.ZS?locations=CI","methodology":"Methodology: HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable.\nData on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates.","theme":"sante","source_group":"wb"},{"code":"SH.HIV.INCD.YG","name":"Jeunes (âgés de 15 à 24 ans) nouvellement infectés par le VIH","description":"Nombre de jeunes (âgés de 15 à 24 ans) nouvellement infectés par le VIH.","source_link":"https://donnees.banquemondiale.org/indicateur/SH.HIV.INCD.YG?locations=CI","methodology":"Methodology: Methods for monitoring HIV incidence vary depending on the epidemic setting and are typically categorized as either direct or indirect measures. Direct measurement at a population level is preferred but often difficult to obtain. Consequently, most countries rely on indirect measures or a combination of both.\nDirect measurement strategies include longitudinal follow-up and repeat testing among individuals without HIV infection, as well as estimation using laboratory tests for recent HIV infection and clinical data. However, longitudinal monitoring is costly and complex, requiring nationally representative population-based surveys.\nIndirect methods frequently rely on estimates constructed from mathematical modeling tools, such as Spectrum or the AIDS Epidemic Model. These models incorporate geographical and population-specific HIV surveys, surveillance, case reporting, mortality, program and clinical data, and sometimes assumptions about risk behavior and HIV transmission. Countries may also triangulate these data with other sources, such as serial population-based HIV prevalence estimates or estimates of HIV prevalence in young, recently exposed populations.\nIt is important to note that case-based surveillance systems capturing newly reported HIV infections should not be used as a direct source for estimating the number of new infections in the reporting year due to reporting delays and underdiagnosis. However, this information can be useful for triangulation or validation purposes, especially when combined with tests for the recency of HIV infection.","theme":"sante","source_group":"wb"},{"code":"NAT.tofe.recettes_et_dons","name":"Recettes et dons (TOFE)","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Total des recettes budgétaires et dons reçus par l'État","theme":"finance","source_group":"national"},{"code":"NAT.tofe.recettes_totales","name":"Recettes totales (TOFE)","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Recettes totales de l'État hors dons","theme":"finance","source_group":"national"},{"code":"NAT.tofe.recettes_fiscales","name":"Recettes fiscales (TOFE)","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Total des recettes fiscales collectées par l'État (impôts directs, TVA, droits de douane, etc.)","theme":"finance","source_group":"national"},{"code":"NAT.tofe.impots_directs","name":"Impôts directs","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Impôts sur le revenu des personnes physiques et morales","theme":"finance","source_group":"national"},{"code":"NAT.tofe.impots_biens_services","name":"Impôts sur les biens et services","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"TVA intérieure et taxes sur les biens et services","theme":"finance","source_group":"national"},{"code":"NAT.tofe.droits_importation","name":"Droits et taxes à l'importation","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Droits de douane et taxes perçus sur les importations","theme":"finance","source_group":"national"},{"code":"NAT.tofe.taxes_exportation","name":"Taxes à l'exportation","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Droit Unique de Sortie et autres taxes à l'exportation","theme":"finance","source_group":"national"},{"code":"NAT.tofe.recettes_non_fiscales","name":"Recettes non fiscales","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Revenus non fiscaux de l'État (dividendes, redevances, etc.)","theme":"finance","source_group":"national"},{"code":"NAT.tofe.dons","name":"Dons reçus","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Dons et appuis budgétaires reçus des partenaires internationaux","theme":"finance","source_group":"national"},{"code":"NAT.tofe.depenses_totales","name":"Dépenses totales et prêts nets (TOFE)","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Total des dépenses publiques incluant fonctionnement, investissement et prêts nets","theme":"finance","source_group":"national"},{"code":"NAT.tofe.remuneration_salaries","name":"Rémunération des salariés (État)","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Masse salariale de la fonction publique","theme":"finance","source_group":"national"},{"code":"NAT.tofe.subventions_transferts","name":"Subventions et transferts","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Subventions aux entreprises publiques et transferts sociaux","theme":"finance","source_group":"national"},{"code":"NAT.tofe.depenses_fonctionnement","name":"Dépenses de fonctionnement","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Dépenses courantes de fonctionnement de l'État","theme":"finance","source_group":"national"},{"code":"NAT.tofe.interets_dette","name":"Intérêts de la dette publique","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Charge d'intérêts sur la dette intérieure et extérieure","theme":"finance","source_group":"national"},{"code":"NAT.tofe.depenses_investissement","name":"Dépenses d'investissement (TOFE)","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Dépenses en capital financées sur ressources intérieures et extérieures","theme":"finance","source_group":"national"},{"code":"NAT.tofe.solde_budgetaire","name":"Solde budgétaire global","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Différence entre recettes totales (y.c. dons) et dépenses totales","theme":"finance","source_group":"national"},{"code":"NAT.tofe.financement_interieur","name":"Financement intérieur du déficit","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Financement du déficit par émission de titres publics sur le marché intérieur","theme":"finance","source_group":"national"},{"code":"NAT.tofe.financement_exterieur","name":"Financement extérieur du déficit","unit":"Mds FCFA","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Financement du déficit par emprunts extérieurs","theme":"finance","source_group":"national"},{"code":"NAT.tofe.pression_fiscale","name":"Pression fiscale (% du PIB)","unit":"%","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Ratio des recettes fiscales rapportées au PIB nominal. Indicateur clé de mobilisation des ressources internes.","theme":"finance","source_group":"national"},{"code":"NAT.tofe.solde_budgetaire_pct_pib","name":"Solde budgétaire (% du PIB)","unit":"%","source":"Ministère des Finances et du Budget (MFB)","source_link":"","methodology":"Données issues du Tableau des Opérations Financières de l'État (TOFE), publié par le Ministère en charge des Finances. Le TOFE retrace l'ensemble des recettes et dépenses du budget de l'État ainsi que le solde budgétaire global.","description":"Solde budgétaire global rapporté au PIB nominal. Un solde négatif indique un déficit budgétaire.","theme":"finance","source_group":"national"},{"code":"NAT.douanes.imports_caf","name":"Importations CAF","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur totale des importations en Coût, Assurance et Fret","theme":"inter","source_group":"national"},{"code":"NAT.douanes.exports_fob","name":"Exportations FOB","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur totale des exportations Free On Board","theme":"inter","source_group":"national"},{"code":"NAT.douanes.solde_commercial","name":"Solde commercial (Douanes)","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Différence entre exportations FOB et importations CAF","theme":"inter","source_group":"national"},{"code":"NAT.douanes.taux_couverture","name":"Taux de couverture commerciale","unit":"%","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Ratio exportations/importations. Un taux > 100% signifie un excédent commercial.","theme":"inter","source_group":"national"},{"code":"NAT.douanes.export_europe","name":"Exportations vers l'Europe","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des exportations à destination de l'Europe","theme":"inter","source_group":"national"},{"code":"NAT.douanes.export_afrique","name":"Exportations vers l'Afrique","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des exportations à destination du continent africain (CEDEAO, UEMOA, etc.)","theme":"inter","source_group":"national"},{"code":"NAT.douanes.export_asie","name":"Exportations vers l'Asie","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des exportations à destination de l'Asie","theme":"inter","source_group":"national"},{"code":"NAT.douanes.export_amerique","name":"Exportations vers les Amériques","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des exportations à destination des Amériques","theme":"inter","source_group":"national"},{"code":"NAT.douanes.export_agri_industrielle","name":"Exports agriculture industrielle","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Exportations de produits de l'agriculture industrielle (cacao, café, coton, etc.)","theme":"inter","source_group":"national"},{"code":"NAT.douanes.export_premiere_transfo","name":"Exports 1ère transformation","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Exportations de produits de première transformation","theme":"inter","source_group":"national"},{"code":"NAT.douanes.export_manufactures","name":"Exports produits manufacturés","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Exportations de produits manufacturés","theme":"inter","source_group":"national"},{"code":"NAT.douanes.export_miniers","name":"Exports produits miniers","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Exportations de produits miniers (or, manganèse, etc.)","theme":"inter","source_group":"national"},{"code":"NAT.douanes.recettes_brutes","name":"Recettes douanières brutes","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Total des recettes collectées par la Douane (base brute)","theme":"inter","source_group":"national"},{"code":"NAT.base_eco.pib_primaire_pct","name":"Part du secteur primaire dans le PIB","unit":"%","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Contribution du secteur primaire (agriculture, élevage, pêche, forêt) au PIB","theme":"primary","source_group":"national"},{"code":"NAT.base_eco.pib_secondaire_pct","name":"Part du secteur secondaire dans le PIB","unit":"%","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Contribution du secteur secondaire (industrie, BTP, énergie, mines) au PIB","theme":"secondary","source_group":"national"},{"code":"NAT.base_eco.pib_tertiaire_pct","name":"Part du secteur tertiaire dans le PIB","unit":"%","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Contribution du secteur tertiaire (services, commerce, transports, télécoms) au PIB","theme":"tertiary","source_group":"national"},{"code":"NAT.base_eco.pib_manufacturier_pct","name":"Part des industries manufacturières dans le PIB","unit":"%","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Contribution des industries manufacturières au PIB","theme":"secondary","source_group":"national"},{"code":"NAT.base_eco.pib_btp_pct","name":"Part du BTP dans le PIB","unit":"%","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Contribution du Bâtiment et Travaux Publics au PIB","theme":"secondary","source_group":"national"},{"code":"NAT.base_eco.pib_extractives_pct","name":"Part des industries extractives dans le PIB","unit":"%","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Contribution des industries extractives (pétrole, gaz, mines) au PIB","theme":"secondary","source_group":"national"},{"code":"NAT.base_eco.pib_commerce_pct","name":"Part du commerce dans le PIB","unit":"%","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Contribution du secteur commerce au PIB","theme":"tertiary","source_group":"national"},{"code":"NAT.base_eco.pib_transports_pct","name":"Part des transports dans le PIB","unit":"%","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Contribution du secteur transports au PIB","theme":"tertiary","source_group":"national"},{"code":"NAT.base_eco.croissance_pib_reel","name":"Taux de croissance du PIB réel (DGE)","unit":"%","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Taux de croissance annuel du PIB en termes réels, source DGE","theme":"macro","source_group":"national"},{"code":"NAT.base_eco.pib_nominal_mxof","name":"PIB nominal (millions XOF)","unit":"Millions XOF","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Produit intérieur brut à prix courants en millions de francs CFA","theme":"macro","source_group":"national"},{"code":"NAT.base_eco.fbcf_mxof","name":"Formation Brute de Capital Fixe","unit":"Millions XOF","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Investissements en capital fixe (constructions, équipements, etc.)","theme":"macro","source_group":"national"},{"code":"NAT.base_eco.taux_investissement","name":"Taux d'investissement","unit":"%","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Ratio FBCF/PIB. Mesure l'effort d'investissement de l'économie.","theme":"macro","source_group":"national"},{"code":"NAT.base_eco.ide_total_mds","name":"Investissements Directs Étrangers reçus","unit":"Mds FCFA","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Flux nets d'IDE reçus par la Côte d'Ivoire","theme":"inter","source_group":"national"},{"code":"NAT.base_eco.cacao_production","name":"Production de cacao","unit":"Tonnes","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Production annuelle de cacao fèves en Côte d'Ivoire (1er producteur mondial)","theme":"primary","source_group":"national"},{"code":"NAT.base_eco.cacao_transforme","name":"Quantité de cacao transformée","unit":"Tonnes","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Volume de cacao transformé localement (broyage)","theme":"primary","source_group":"national"},{"code":"NAT.base_eco.cacao_taux_transfo","name":"Taux de transformation du cacao","unit":"%","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Part de la production de cacao transformée localement","theme":"primary","source_group":"national"},{"code":"NAT.base_eco.dette_stock_total","name":"Stock total de la dette publique","unit":"Mds FCFA","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Encours total de la dette publique (intérieure + extérieure)","theme":"finance","source_group":"national"},{"code":"NAT.base_eco.dette_pct_pib","name":"Dette publique en % du PIB (DGE)","unit":"% du PIB","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Ratio dette publique / PIB nominal","theme":"finance","source_group":"national"},{"code":"NAT.base_eco.dette_exterieure_mds","name":"Dette extérieure","unit":"Mds FCFA","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Encours de la dette extérieure","theme":"finance","source_group":"national"},{"code":"NAT.base_eco.dette_interieure_mds","name":"Dette intérieure","unit":"Mds FCFA","source":"Direction Générale de l'Économie (DGE) / ANStat","source_link":"","methodology":"Données compilées à partir de la base de données économiques de la DGE, incluant les comptes nationaux, la structure du PIB, les effectifs employés, les IDE, la production agro-industrielle et l'encours de la dette publique. Sources primaires indiquées sous chaque tableau du classeur.","description":"Encours de la dette intérieure","theme":"finance","source_group":"national"},{"code":"NAT.financements.dette_pct_pib","name":"Dette du gouvernement central (% PIB)","unit":"% du PIB","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Ratio dette du gouvernement central / PIB selon la DGF","theme":"finance","source_group":"national"},{"code":"NAT.financements.interets_pct_recettes","name":"Intérêts de la dette (% des recettes)","unit":"%","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Charge d'intérêts rapportée aux recettes budgétaires","theme":"finance","source_group":"national"},{"code":"NAT.financements.interets_pct_pib","name":"Intérêts de la dette (% du PIB)","unit":"%","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Charge d'intérêts rapportée au PIB","theme":"finance","source_group":"national"},{"code":"NAT.financements.taux_interet_moyen","name":"Taux d'intérêt moyen pondéré de la dette","unit":"%","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Taux d'intérêt moyen pondéré sur l'ensemble du portefeuille de dette","theme":"finance","source_group":"national"},{"code":"NAT.financements.duree_vie_moyenne","name":"Durée de vie moyenne de la dette","unit":"Années","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Durée de vie moyenne jusqu'à échéance du portefeuille de dette","theme":"finance","source_group":"national"},{"code":"NAT.financements.dette_ct_pct","name":"Part de la dette à court terme","unit":"%","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Proportion de la dette arrivant à échéance dans moins d'un an","theme":"finance","source_group":"national"},{"code":"NAT.financements.dette_devises_pct","name":"Part de la dette en devises étrangères","unit":"%","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Proportion de la dette libellée en devises (risque de change)","theme":"finance","source_group":"national"},{"code":"NAT.financements.service_dette_total","name":"Service total de la dette","unit":"Mds FCFA","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Total des remboursements de principal et paiements d'intérêts","theme":"finance","source_group":"national"},{"code":"NAT.financements.remboursement_principal","name":"Remboursement du principal","unit":"Mds FCFA","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Amortissement du principal de la dette","theme":"finance","source_group":"national"},{"code":"NAT.financements.paiement_interets","name":"Paiement des intérêts","unit":"Mds FCFA","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Paiements d'intérêts sur la dette","theme":"finance","source_group":"national"},{"code":"NAT.financements.service_ext_bilateral","name":"Service dette ext. - Bilatéraux","unit":"Mds FCFA","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Service de la dette extérieure dû aux créanciers bilatéraux","theme":"finance","source_group":"national"},{"code":"NAT.financements.service_ext_multilateral","name":"Service dette ext. - Multilatéraux","unit":"Mds FCFA","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Service de la dette extérieure dû aux créanciers multilatéraux","theme":"finance","source_group":"national"},{"code":"NAT.financements.service_ext_obligations","name":"Service dette ext. - Obligations","unit":"Mds FCFA","source":"Direction Générale des Financements (DGF)","source_link":"https://www.dgf.gouv.ci/publications/bulletins-statistiques","methodology":"Données provenant des bulletins statistiques de la Direction Générale des Financements. Couvrent l'encours de la dette publique, le service de la dette (intérieure et extérieure), les ratios d'endettement et les indicateurs de viabilité.","description":"Service de la dette extérieure sur les euro-obligations","theme":"finance","source_group":"national"},{"code":"NAT.douanes.top_export_0","name":"Top export #1: Cacao fèves","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des exportations du produit: Cacao fèves","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_import_0","name":"Top import #1: Pétrole brut","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des importations du produit: Pétrole brut","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_export_1","name":"Top export #2: Cacao transformé","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des exportations du produit: Cacao transformé","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_import_1","name":"Top import #2: Produits pétroliers autres que le pétrole brut","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des importations du produit: Produits pétroliers autres que le pétrole brut","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_export_2","name":"Top export #3: Or brut","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des exportations du produit: Or brut","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_import_2","name":"Top import #3: Machines mécaniques","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des importations du produit: Machines mécaniques","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_export_3","name":"Top export #4: Produits pétroliers autres que le pétrole brut","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des exportations du produit: Produits pétroliers autres que le pétrole brut","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_import_3","name":"Top import #4: Fer, fonte, acier et ouvrages en ces métaux","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des importations du produit: Fer, fonte, acier et ouvrages en ces métaux","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_export_4","name":"Top export #5: Caoutchouc naturel","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des exportations du produit: Caoutchouc naturel","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_import_4","name":"Top import #5: Poisson frais","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des importations du produit: Poisson frais","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_export_5","name":"Top export #6: Noix de cajou","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des exportations du produit: Noix de cajou","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_import_5","name":"Top import #6: Matériels de transport routier sauf véhicules de tourisme","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des importations du produit: Matériels de transport routier sauf véhicules de tourisme","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_export_6","name":"Top export #7: Appareils de navigation maritime et aérienne","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des exportations du produit: Appareils de navigation maritime et aérienne","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_import_6","name":"Top import #7: Riz","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des importations du produit: Riz","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_export_7","name":"Top export #8: Pétrole brut","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des exportations du produit: Pétrole brut","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_import_7","name":"Top import #8: Matières plastiques et ouvrage en ces matières","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. Les importations sont en valeur CAF (Coût, Assurance et Fret) et les exportations en valeur FOB (Free On Board).","description":"Valeur des importations du produit: Matières plastiques et ouvrage en ces matières","theme":"inter","source_group":"national"},{"code":"NAT.douanes.top_export_8","name":"Top export #9: Huiles essentielles et extraits végétaux","unit":"Mds FCFA","source":"Direction Générale des Douanes","source_link":"https://www.douanes.ci/sites/default/files/annuaire_statistique_douanes_ivoiriennes_asdi_2024.pdf","methodology":"Données extraites de l'Annuaire Statistique des Douanes Ivoiriennes (ASDI) 2024. 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Licence : Licence ouverte du portail data.gouv.ci.","description":"Répartition des localités par district et région administrative RGPH 2021","region":"Gôh-Djiboua","var":"datagouvci:23","theme":"demo","source_group":"national"},{"code":"NAT.od.datagouvci.5qv85h6d8oxwg8rj-9vnnkso.localites_urbaines.Grands_Ponts","name":"Répartition des localités par district et région administrative RGPH 2021 — Localités urbaines — Grands-Ponts","unit":"","source":"INS / ANStat (RGPH) (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/repartition-des-localites-par-district-et-region-administrative-rgph-2021","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.17_18_INDUSTRIES_DU_PAPIER_ET_DU_CARTON_","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 17-18 — INDUSTRIES DU PAPIER ET DU CARTON, IMPRIMERIE ET REPRODUCTION D’ENREGISTREMENT","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.17_FABRICATION_DU_PAPIER_ET_DU_CARTON","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 17 — FABRICATION DU PAPIER ET DU CARTON","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.18_IMPRIMERIE_ET_REPRODUCTION_D_ENREGIST","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 18 — IMPRIMERIE ET REPRODUCTION D'ENREGISTREMENTS","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.19_INDUSTRIES_DE_TRANSFORMATION_DE_PRODU","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 19 — INDUSTRIES DE TRANSFORMATION DE PRODUITS PETROLIERS","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.29_30_INDUSTRIE_AUTOMOBILES_ET_DE_MATERI","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 29-30 — INDUSTRIE AUTOMOBILES ET DE MATÉRIELS DE TRANSPORTS","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.29_CONSTRUCTION_DE_VEHICULES_AUTOMOBILES","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 29 — CONSTRUCTION DE VÉHICULES AUTOMOBILES","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.30_FABRICATION_D_AUTRES_MATERIELS_DE_TRA","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 30 — FABRICATION D'AUTRES MATÉRIELS DE TRANSPORT","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.31_33_AUTRES_INDUSTRIES_MANUFACTURIERES","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 31-33 — AUTRES INDUSTRIES MANUFACTURIÈRES","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.31_FABRICATION_DE_MEUBLES_ET_MATELAS","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 31 — FABRICATION DE MEUBLES ET MATELAS","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.32_AUTRES_INDUSTRIES_MANUFACTURIERES","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 32 — AUTRES INDUSTRIES MANUFACTURIERES","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.33_REPARATION_ET_INSTALLATION_DE_MACHINE","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 33 — REPARATION ET INSTALLATION DE MACHINES ET D'EQUIPEMENTS","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.35_36_INDUSTRIES_DE_PRODUCTION_ET_DE_DIS","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 35-36 — INDUSTRIES DE PRODUCTION ET DE DISTRIBUTION D’ÉLECTRICITÉ, DE GAZ ET D’EAU","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.35_PRODUCTION_ET_DISTRIBUTION_D_ELECTRIC","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 35 — PRODUCTION ET DISTRIBUTION D'ÉLECTRICITÉ ET DE GAZ,","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.36_CAPTAGE_TRAITEMENT_ET_DISTRIBUTION_D_","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 36 — CAPTAGE, TRAITEMENT ET DISTRIBUTION D'EAU","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Licence ouverte du portail data.gouv.ci.","description":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022","region":"","var":"datagouvci:106","theme":"macro","source_group":"national"},{"code":"NAT.od.datagouvci.indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie.Indice.37_39_INDUSTRIES_ENVIRONNEMENTALES","name":"Indice du Chiffre d'Affaires (ICA) Industrie par type d'Industrie de mars 2021 à mars 2022 — Indice — 37-39 — INDUSTRIES ENVIRONNEMENTALES","unit":"","source":"INS / ANStat (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/indice-du-chiffre-daffaires-industrie-ica-industrie-par-type-dindustrie","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Licence ouverte du portail data.gouv.ci.","description":"Interpellés et déférés en 2014 et 2015","region":"","var":"datagouvci:107","theme":"social","source_group":"national"},{"code":"NAT.od.datagouvci.interpelles-et-deferes-en-2014-2015.Valeur.Fevrier_Interpelles_apres_une_plainte","name":"Interpellés et déférés en 2014 et 2015 — Février — Interpellés après une plainte","unit":"","source":"Producteur non précisé (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/interpelles-et-deferes-en-2014-2015","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Interpellés et déférés en 2014 et 2015","region":"","var":"datagouvci:107","theme":"social","source_group":"national"},{"code":"NAT.od.datagouvci.interpelles-et-deferes-en-2014-2015.Valeur.Janvier_Deferes","name":"Interpellés et déférés en 2014 et 2015 — Janvier — Déférés","unit":"","source":"Producteur non précisé (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/interpelles-et-deferes-en-2014-2015","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Licence ouverte du portail data.gouv.ci.","description":"Interpellés et déférés en 2014 et 2015","region":"","var":"datagouvci:107","theme":"social","source_group":"national"},{"code":"NAT.od.datagouvci.interpelles-et-deferes-en-2014-2015.Valeur.Janvier_Deferes_apres_une_plainte","name":"Interpellés et déférés en 2014 et 2015 — Janvier — Déférés après une plainte","unit":"","source":"Producteur non précisé (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/interpelles-et-deferes-en-2014-2015","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Licence ouverte du portail data.gouv.ci.","description":"Interpellés et déférés en 2014 et 2015","region":"","var":"datagouvci:107","theme":"social","source_group":"national"},{"code":"NAT.od.datagouvci.interpelles-et-deferes-en-2014-2015.Valeur.Janvier_Interpelles","name":"Interpellés et déférés en 2014 et 2015 — Janvier — Interpellés","unit":"","source":"Producteur non précisé (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/interpelles-et-deferes-en-2014-2015","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Licence ouverte du portail data.gouv.ci.","description":"Interpellés et déférés en 2014 et 2015","region":"","var":"datagouvci:107","theme":"social","source_group":"national"},{"code":"NAT.od.datagouvci.interpelles-et-deferes-en-2014-2015.Valeur.Mai_Interpelles","name":"Interpellés et déférés en 2014 et 2015 — Mai — Interpellés","unit":"","source":"Producteur non précisé (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/interpelles-et-deferes-en-2014-2015","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Licence ouverte du portail data.gouv.ci.","description":"Structure par âge moyen et rapport de dépendance par région administrative – RGPH 2021","region":"Zanzan","var":"datagouvci:110","theme":"demo","source_group":"national"},{"code":"NAT.od.datagouvci.kubzrtciwpeadf3ibtza3u0w.indice_jeunesse.Bafing","name":"Structure par âge moyen et rapport de dépendance par région administrative – RGPH 2021 — Indice de jeunesse — Bafing","unit":"","source":"INS / ANStat (RGPH) (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/structure-par-age-age-moyen-et-rapport-de-dependance-par-region-administrative-rgph-2021","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Licence ouverte du portail data.gouv.ci.","description":"Structure par âge moyen et rapport de dépendance par région administrative – RGPH 2021","region":"Comoé","var":"datagouvci:111","theme":"demo","source_group":"national"},{"code":"NAT.od.datagouvci.kubzrtciwpeadf3ibtza3u0w.indice_jeunesse.Denguele","name":"Structure par âge moyen et rapport de dépendance par région administrative – RGPH 2021 — Indice de jeunesse — Denguélé","unit":"","source":"INS / ANStat (RGPH) (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/structure-par-age-age-moyen-et-rapport-de-dependance-par-region-administrative-rgph-2021","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Licence ouverte du portail data.gouv.ci.","description":"Production totale et moyenne de lait par région selon l'espèce (en litres) en 2024","region":"Gontougo","var":"datagouvci:148","theme":"primary","source_group":"national"},{"code":"NAT.od.datagouvci.rb07nb9nxbrgpr7b1lnc8mg6.lait_bovin_litres.Grands_Ponts","name":"Production totale et moyenne de lait par région selon l'espèce (en litres) en 2024 — Lait bovin (litres) — Grands-Ponts","unit":"","source":"Producteur non précisé (via data.gouv.ci)","source_link":"https://data.gouv.ci/datasets/production-totale-et-moyenne-de-lait-par-region-selon-lespece-en-litres-en-2024","methodology":"Jeux de données publiés sur le portail national data.gouv.ci, convertis automatiquement en séries annuelles (une série par variable numérique et par catégorie). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Indice synthétique de fécondité 15-49","region":"Denguélé","var":"dhs:251","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTR_W_TFR.Goh_Djiboua","name":"Indice synthétique de fécondité 15-49 — Goh-Djiboua (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program) — EDS régional","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Indice synthétique de fécondité 15-49","region":"Goh-Djiboua","var":"dhs:251","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTR_W_TFR.Lacs","name":"Indice synthétique de fécondité 15-49 — ..Lacs (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program) — EDS régional","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Indice synthétique de fécondité 15-49","region":"Lacs","var":"dhs:251","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTR_W_TFR.Lagunes","name":"Indice synthétique de fécondité 15-49 — Lagunes (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program) — EDS régional","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Indice synthétique de fécondité 15-49","region":"Lagunes","var":"dhs:251","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTR_W_TFR.Montagnes","name":"Indice synthétique de fécondité 15-49 — Montagnes (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program) — EDS régional","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Indice synthétique de fécondité 15-49","region":"Montagnes","var":"dhs:251","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTR_W_TFR.Nord_Ouest","name":"Indice synthétique de fécondité 15-49 — Nord-Ouest (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program) — EDS régional","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Indice synthétique de fécondité 15-49","region":"Nord-Ouest","var":"dhs:251","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTR_W_TFR.Sassandra_Marahoue","name":"Indice synthétique de fécondité 15-49 — Sassandra-Marahoué (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program) — EDS régional","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Indice synthétique de fécondité 15-49","region":"Sassandra-Marahoué","var":"dhs:251","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTR_W_TFR.Savanes","name":"Indice synthétique de fécondité 15-49 — Savanes (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program) — EDS régional","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Indice synthétique de fécondité 15-49","region":"Savanes","var":"dhs:251","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTR_W_TFR.Vallee_du_Bandama","name":"Indice synthétique de fécondité 15-49 — Vallée du Bandama (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program) — EDS régional","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Indice synthétique de fécondité 15-49","region":"Vallée du Bandama","var":"dhs:251","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTR_W_TFR.Woroba","name":"Indice synthétique de fécondité 15-49 — Woroba (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program) — EDS régional","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Indice synthétique de fécondité 15-49","region":"Woroba","var":"dhs:251","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTR_W_TFR.Yamoussoukro","name":"Indice synthétique de fécondité 15-49 — ..Yamoussoukro (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program) — EDS régional","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Indice synthétique de fécondité 15-49","region":"Yamoussoukro","var":"dhs:251","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTR_W_TFR.Zanzan","name":"Indice synthétique de fécondité 15-49 — Zanzan (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program) — EDS régional","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Indice synthétique de fécondité 15-49","region":"Zanzan","var":"dhs:251","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTT_W_A10","name":"Taux de fécondité par âge : 10-14 ans (périodes de cinq ans) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Taux de fécondité par âge : 15-19 ans (périodes de cinq ans)","region":"","var":"dhs:250","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTT_W_A20","name":"Taux de fécondité par âge : 20-24 ans (périodes de cinq ans) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Taux de fécondité par âge : 20-24 ans (périodes de cinq ans)","region":"","var":"dhs:250","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTT_W_A25","name":"Taux de fécondité par âge : 25-29 ans (périodes de cinq ans) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Taux de fécondité par âge : 25-29 ans (périodes de cinq ans)","region":"","var":"dhs:250","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTT_W_A30","name":"Taux de fécondité par âge : 30-34 ans (périodes de cinq ans) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Taux de fécondité par âge : 30-34 ans (périodes de cinq ans)","region":"","var":"dhs:250","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTT_W_A35","name":"Taux de fécondité par âge : 35-39 ans (périodes de cinq ans) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Taux de fécondité par âge : 35-39 ans (périodes de cinq ans)","region":"","var":"dhs:250","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTT_W_A40","name":"Taux de fécondité par âge : 40-44 ans (périodes de cinq ans) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Taux de fécondité par âge : 40-44 ans (périodes de cinq ans)","region":"","var":"dhs:250","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTT_W_A45","name":"Taux de fécondité par âge : 45-49 ans (périodes de cinq ans) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Taux de fécondité par âge : 45-49 ans (périodes de cinq ans)","region":"","var":"dhs:250","theme":"demo","source_group":"dhs"},{"code":"NAT.od.dhs.FE_FRTY_W_MNC","name":"Fécondité accomplie des femmes de 40-49 ans (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Connaissance d'au moins une méthode moderne de contraception (toutes les femmes)","region":"","theme":"sante","source_group":"dhs"},{"code":"NAT.od.dhs.FP_KMTA_W_MST","name":"Connaissance de la stérilisation masculine (toutes les femmes) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Nombre moyen de méthodes contraceptives connues (hommes mariés de 15-49 ans)","region":"","theme":"sante","source_group":"dhs"},{"code":"NAT.od.dhs.FP_KMTM_M_MOD","name":"Connaissance d'au moins une méthode moderne de contraception (hommes en union) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Connaissance d'au moins une méthode moderne de contraception (hommes en union)","region":"","theme":"sante","source_group":"dhs"},{"code":"NAT.od.dhs.FP_KMTM_M_MST","name":"Connaissance de la stérilisation masculine (hommes en union) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Connaissance de la stérilisation masculine (hommes en union)","region":"","theme":"sante","source_group":"dhs"},{"code":"NAT.od.dhs.FP_KMTM_M_OMD","name":"Connaissance d'autres méthodes modernes (hommes en union) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Connaissance d'autres méthodes modernes (hommes en union)","region":"","theme":"sante","source_group":"dhs"},{"code":"NAT.od.dhs.FP_KMTM_M_OTR","name":"Connaissance d'autres méthodes traditionnelles (hommes en union) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Connaissance de l'abstinence périodique (hommes en union)","region":"","theme":"sante","source_group":"dhs"},{"code":"NAT.od.dhs.FP_KMTM_M_STD","name":"Connaissance de la méthode des jours fixes (hommes en union) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Connaissance de la mousse ou de la gelée (femmes en union)","region":"","theme":"sante","source_group":"dhs"},{"code":"NAT.od.dhs.FP_KMTM_W_FST","name":"Connaissance de la stérilisation féminine (femmes en union) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Connaissance des injectables (femmes en union)","region":"","theme":"sante","source_group":"dhs"},{"code":"NAT.od.dhs.FP_KMTM_W_IUD","name":"Connaissance du DIU (femmes en union) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Connaissance de la méthode de l'allaitement maternel et de l'aménorrhée (MAMA) (femmes en union)","region":"","theme":"sante","source_group":"dhs"},{"code":"NAT.od.dhs.FP_KMTM_W_MCN","name":"Connaissance du condom masculin (femmes en union) (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Femmes déclarant une IST","region":"","theme":"sante","source_group":"dhs"},{"code":"NAT.od.dhs.HC_AGON_H_ANM","name":"Ménages possédant des animaux d'élevage (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages possédant des animaux d'élevage","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_AGON_H_LND","name":"Ménages possédant des terres agricoles (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages possédant des terres agricoles","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_H_AGR","name":"Ménages cuisinant avec des résidus de cultures agricoles (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec des résidus de cultures agricoles","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_H_CHR","name":"Ménages cuisinant au charbon de bois (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant au charbon de bois","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_H_CLN","name":"Ménages utilisant des combustibles propres pour la cuisson  (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages utilisant des combustibles propres pour la cuisson","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_H_COL","name":"Ménages cuisinant au charbon, lignite (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant au charbon, lignite","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_H_ELC","name":"Ménages cuisinant à l'électricité (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant à l'électricité","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_H_GAS","name":"Ménages cuisinant à l'essence (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant à l'essence","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_H_LPG","name":"Ménages cuisinant au GPL/gaz naturel/biogaz (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Ménages ne faisant pas la cuisine dans le ménage","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_H_OTH","name":"Ménages cuisinant avec d'autres types de combustible (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec d'autres types de combustible","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_H_SLD","name":"Ménages utilisant des combustibles solides pour la cuisson  (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages utilisant des combustibles solides pour la cuisson","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_H_STR","name":"Ménages cuisinant avec de la paille/des arbustes/de l'herbe (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec de la paille/des arbustes/de l'herbe","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_H_WOD","name":"Ménages cuisinant au bois (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant au bois","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_P_CHR","name":"Population cuisinant au charbon de bois (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant au charbon de bois","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_P_CLN","name":"Population utilisant des combustibles propres pour la cuisson  (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant au charbon, lignite","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_P_ELC","name":"Population cuisinant à l'électricité (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant à l'électricité","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_P_LPG","name":"Population cuisinant au GPL/gaz naturel/biogaz (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Population utilisant des combustibles solides pour la cuisson","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_P_STR","name":"Population cuisinant à la paille/aux arbustes/à l'herbe (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant à la paille/aux arbustes/à l'herbe","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKFL_P_WOD","name":"Population cuisinant au bois (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant dans le logement, dans une pièce/cuisine séparée","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKPL_P_NFD","name":"Population ne cuisinant aucun aliment dans le ménage (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant dans le logement, sans pièce/cuisine séparée","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKPL_P_OTH","name":"Population cuisinant dans d'autres lieux (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant dans d'autres lieux","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKPL_P_OUT","name":"Population cuisinant à l'extérieur (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant à l'extérieur","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKPL_P_SEP","name":"Population cuisinant dans un bâtiment séparé (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant dans un bâtiment séparé","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_3SO","name":"Ménages cuisinant avec un foyer à trois pierres/feu ouvert (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec un foyer à trois pierres/feu ouvert","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_BIO","name":"Ménages cuisinant avec un réchaud à biogaz (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec un réchaud à biogaz","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_CFT","name":"Ménages cuisinant avec des combustibles et technologies propres (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec des combustibles et technologies propres","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_ELC","name":"Ménages cuisinant avec une cuisinière électrique (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec une cuisinière électrique","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_LFN","name":"Ménages cuisinant avec un réchaud à combustible liquide n'utilisant pas d'alcool/éthanol (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec un réchaud à combustible liquide n'utilisant pas d'alcool/éthanol","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_LPG","name":"Ménages cuisinant avec un réchaud au GPL/gaz naturel (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec un réchaud au GPL/gaz naturel","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_MSC","name":"Ménages cuisinant avec un réchaud manufacturé à combustible solide avec cheminée (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec un réchaud manufacturé à combustible solide avec cheminée","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_MSF","name":"Ménages cuisinant avec un réchaud manufacturé à combustible solide (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec un réchaud manufacturé à combustible solide","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_MSW","name":"Ménages cuisinant avec un réchaud manufacturé à combustible solide sans cheminée (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec un réchaud manufacturé à combustible solide sans cheminée","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_NAT","name":"Ménages cuisinant avec un réchaud au gaz naturel canalisé (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec un réchaud au gaz naturel canalisé","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_NFD","name":"Ménages sans aliments cuisinés dans le ménage (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages sans aliments cuisinés dans le ménage","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_OFT","name":"Ménages cuisinant avec d'autres combustibles et technologies (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec d'autres combustibles et technologies","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_OTH","name":"Ménages cuisinant avec autre chose (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec autre chose","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_SOL","name":"Ménages cuisinant avec un cuiseur solaire (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec un cuiseur solaire","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_TSC","name":"Ménages cuisinant avec un réchaud traditionnel à combustible solide avec cheminée (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec un réchaud traditionnel à combustible solide avec cheminée","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_TSF","name":"Ménages cuisinant avec un réchaud traditionnel à combustible solide (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec un réchaud traditionnel à combustible solide","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_H_TSW","name":"Ménages cuisinant avec un réchaud traditionnel à combustible solide sans cheminée (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages cuisinant avec un réchaud traditionnel à combustible solide sans cheminée","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_P_3SO","name":"Population cuisinant avec un foyer à trois pierres/feu ouvert (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant avec un foyer à trois pierres/feu ouvert","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_P_BIO","name":"Population cuisinant avec un réchaud à biogaz (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant avec un réchaud à biogaz","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_P_CFT","name":"Population cuisinant avec des combustibles et technologies propres (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant avec des combustibles et technologies propres","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_P_ELC","name":"Population cuisinant avec une cuisinière électrique (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant avec une cuisinière électrique","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_P_LFN","name":"Population cuisinant avec un réchaud à combustible liquide n'utilisant ni alcool ni éthanol (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant avec un réchaud à combustible liquide n'utilisant ni alcool ni éthanol","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_P_LPG","name":"Population cuisinant avec une cuisinière au GPL/gaz naturel (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant avec une cuisinière au GPL/gaz naturel","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_P_MSC","name":"Population cuisinant avec un réchaud à combustible solide manufacturé avec cheminée (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant avec un réchaud à combustible solide manufacturé avec cheminée","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_P_MSF","name":"Population cuisinant avec un réchaud à combustible solide manufacturé (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant avec un réchaud à combustible solide manufacturé","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_P_MSW","name":"Population cuisinant avec un réchaud à combustible solide manufacturé sans cheminée (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant avec un réchaud à combustible solide manufacturé sans cheminée","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_P_NAT","name":"Population cuisinant avec une cuisinière à gaz naturel canalisé (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population cuisinant avec une cuisinière à gaz naturel canalisé","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_CKTC_P_NFD","name":"Population cuisinant sans qu'aucun aliment ne soit cuit dans le ménage (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Ménages avec autre type de sol","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_H_PLM","name":"Ménages avec sol en palmier/bambou (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages avec sol en palmier/bambou","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_H_PQT","name":"Ménages avec sol en parquet ou bois poli (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages avec sol en parquet ou bois poli","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_H_RUD","name":"Ménages avec sol rudimentaire (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages avec sol rudimentaire","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_H_VIN","name":"Ménages avec sol en bandes de vinyle ou d'asphalte (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages avec sol en bandes de vinyle ou d'asphalte","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_H_WDP","name":"Ménages avec sol en planches de bois (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Ménages avec sol en planches de bois","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_P_CEM","name":"Population dont le sol est en ciment (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population dont le sol est en ciment","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_P_CER","name":"Population dont le sol est en carreaux de céramique (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population dont le sol est en carreaux de céramique","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_P_CPT","name":"Population dont le sol est recouvert de moquette (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population dont le sol est recouvert de moquette","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_P_DNG","name":"Population dont le sol est en bouse (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population dont le sol est en bouse","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_P_ETH","name":"Population dont le sol est en terre/sable (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population dont le sol est en terre/sable","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_P_FIN","name":"Population dont le sol est fini (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population dont le sol est fini","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_P_NAT","name":"Population dont le sol est naturel (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Données publiques du DHS Program (citation requise).","description":"Population dont le sol est d'un autre type","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_P_PLM","name":"Population dont le sol est en palme/bambou (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population dont le sol est en palme/bambou","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_P_PQT","name":"Population dont le sol est en parquet ou en bois poli (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Données publiques du DHS Program (citation requise).","description":"Population dont le sol est en parquet ou en bois poli","region":"","theme":"territory","source_group":"dhs"},{"code":"NAT.od.dhs.HC_FLRM_P_RUD","name":"Population dont le sol est rudimentaire (EDS)","unit":"","source":"Enquêtes démographiques et de santé (EDS – DHS Program)","source_link":"https://www.statcompiler.com/","methodology":"Indicateurs des EDS de Côte d'Ivoire (1994, 1998-99, 2005 AIS, 2011-12, 2021) réalisées par l'ANStat avec ICF. Valeurs d'enquête : une observation par année d'enquête. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Domaine public (USAID / FEWS NET).","description":"Prix moyen annuel sur le marché de Man.","region":"Man","var":"fewsnet:367","theme":"social","source_group":"fewsnet"},{"code":"NAT.od.fewsnet.Rice_Milled.kg.Retail.Ouangolodougou","name":"Prix : Riz (usiné) — marché de Ouangolodougou (FCFA/kg)","unit":"FCFA/kg","source":"FEWS NET (prix sur les marchés) — Prix des marchés","source_link":"https://fews.net/west-africa","methodology":"Prix de détail relevés sur les marchés de Côte d'Ivoire (source primaire : ANStat), en FCFA. Valeur annuelle = moyenne des relevés mensuels. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Domaine public (USAID / FEWS NET).","description":"Prix moyen annuel sur le marché de Ferkessedougou.","region":"Ferkessedougou","var":"fewsnet:368","theme":"social","source_group":"fewsnet"},{"code":"NAT.od.fewsnet.Yams.kg.Retail.Korhogo","name":"Prix : Ignames — marché de Korhogo (FCFA/kg)","unit":"FCFA/kg","source":"FEWS NET (prix sur les marchés) — Prix des marchés","source_link":"https://fews.net/west-africa","methodology":"Prix de détail relevés sur les marchés de Côte d'Ivoire (source primaire : ANStat), en FCFA. Valeur annuelle = moyenne des relevés mensuels. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Commerce international de marchandises (FMI, base IMTS) : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Burkina Faso — XG — FOB ","region":"","var":"imf_sdmx:396","theme":"inter","source_group":"imf"},{"code":"NAT.od.imf_sdmx.IMTS.XG_FOB_USD.BGD.6.XG.FOB.USD.M.OL","name":"Commerce international de marchandises : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Bangladesh","unit":"Millions de dollars US","source":"FMI (portail de données SDMX) — Commerce international de marchandises","source_link":"https://data.imf.org/","methodology":"Séries annuelles des bases thématiques du FMI (ex-IFS : prix, change, BOP, commerce). Données récupérées automatiquement via l'API le 2026-11-01. 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Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Commerce international de marchandises (FMI, base IMTS) : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Chine, République popula","region":"","var":"imf_sdmx:396","theme":"inter","source_group":"imf"},{"code":"NAT.od.imf_sdmx.IMTS.XG_FOB_USD.CMR.6.XG.FOB.USD.M.OL","name":"Commerce international de marchandises : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Cameroun","unit":"Millions de dollars US","source":"FMI (portail de données SDMX) — Commerce international de marchandises","source_link":"https://data.imf.org/","methodology":"Séries annuelles des bases thématiques du FMI (ex-IFS : prix, change, BOP, commerce). Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Commerce international de marchandises (FMI, base IMTS) : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Cameroun — XG — FOB — M ","region":"","var":"imf_sdmx:396","theme":"inter","source_group":"imf"},{"code":"NAT.od.imf_sdmx.IMTS.XG_FOB_USD.COD.6.XG.FOB.USD.M.OL","name":"Commerce international de marchandises : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Congo, République démocratique du","unit":"Millions de dollars US","source":"FMI (portail de données SDMX) — Commerce international de marchandises","source_link":"https://data.imf.org/","methodology":"Séries annuelles des bases thématiques du FMI (ex-IFS : prix, change, BOP, commerce). Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Commerce international de marchandises (FMI, base IMTS) : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Congo, République démocr","region":"","var":"imf_sdmx:396","theme":"inter","source_group":"imf"},{"code":"NAT.od.imf_sdmx.IMTS.XG_FOB_USD.COG.6.XG.FOB.USD.M.OL","name":"Commerce international de marchandises : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Congo, République du","unit":"Millions de dollars US","source":"FMI (portail de données SDMX) — Commerce international de marchandises","source_link":"https://data.imf.org/","methodology":"Séries annuelles des bases thématiques du FMI (ex-IFS : prix, change, BOP, commerce). Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Commerce international de marchandises (FMI, base IMTS) : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Congo, République du — X","region":"","var":"imf_sdmx:396","theme":"inter","source_group":"imf"},{"code":"NAT.od.imf_sdmx.IMTS.XG_FOB_USD.COL.6.XG.FOB.USD.M.OL","name":"Commerce international de marchandises : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Colombie","unit":"Millions de dollars US","source":"FMI (portail de données SDMX) — Commerce international de marchandises","source_link":"https://data.imf.org/","methodology":"Séries annuelles des bases thématiques du FMI (ex-IFS : prix, change, BOP, commerce). Données récupérées automatiquement via l'API le 2026-11-01. 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Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Commerce international de marchandises (FMI, base IMTS) : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Türkiye, République de —","region":"","var":"imf_sdmx:396","theme":"inter","source_group":"imf"},{"code":"NAT.od.imf_sdmx.IMTS.XG_FOB_USD.TWN.6.XG.FOB.USD.M.OL","name":"Commerce international de marchandises : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Province chinoise de Taïwan","unit":"Millions de dollars US","source":"FMI (portail de données SDMX) — Commerce international de marchandises","source_link":"https://data.imf.org/","methodology":"Séries annuelles des bases thématiques du FMI (ex-IFS : prix, change, BOP, commerce). Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Commerce international de marchandises (FMI, base IMTS) : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Province chinoise de Taï","region":"","var":"imf_sdmx:396","theme":"inter","source_group":"imf"},{"code":"NAT.od.imf_sdmx.IMTS.XG_FOB_USD.TX126.6.XG.FOB.USD.M.OL","name":"Commerce international de marchandises : Exportations de biens, franco à bord (FAB), dollar des États-Unis — Belgique-Luxembourg","unit":"Millions de dollars US","source":"FMI (portail de données SDMX) — Commerce international de marchandises","source_link":"https://data.imf.org/","methodology":"Séries annuelles des bases thématiques du FMI (ex-IFS : prix, change, BOP, commerce). Données récupérées automatiquement via l'API le 2026-11-01. 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Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.GGRXG_GDP","name":"Recettes publiques, hors dons (% du PIB)","unit":"% du PIB","source":"FMI (DataMapper / World Economic Outlook) — AFRREO","source_link":"https://www.imf.org/external/datamapper/GGRXG_GDP@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Recettes publiques, hors dons (en pourcentage du PIB)","region":"","theme":"finance","source_group":"imf"},{"code":"NAT.od.imf_weo.GGR_G01_GDP_PT","name":"Recettes","unit":"% du PIB","source":"FMI (DataMapper / World Economic Outlook)","source_link":"https://www.imf.org/external/datamapper/GGR_G01_GDP_PT@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Recettes","region":"","theme":"finance","source_group":"imf"},{"code":"NAT.od.imf_weo.GGXCNLXG_GDP","name":"Solde budgétaire global, hors dons (% du PIB)","unit":"% du PIB","source":"FMI (DataMapper / World Economic Outlook) — AFRREO","source_link":"https://www.imf.org/external/datamapper/GGXCNLXG_GDP@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Solde budgétaire global, hors dons (en pourcentage du PIB)","region":"","theme":"finance","source_group":"imf"},{"code":"NAT.od.imf_weo.GGXCNL_G01_GDP_PT","name":"Capacité/besoin de financement net (aussi appelé solde global)","unit":"% du PIB","source":"FMI (DataMapper / World Economic Outlook)","source_link":"https://www.imf.org/external/datamapper/GGXCNL_G01_GDP_PT@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Défini comme la différence entre les recettes et les dépenses totales, selon l'édition 2014 du Manuel de statistiques de finances publiques du FMI (MS","region":"","theme":"finance","source_group":"imf"},{"code":"NAT.od.imf_weo.GGXCNL_GDP","name":"Solde budgétaire global, dons compris (% du PIB)","unit":"% du PIB","source":"FMI (DataMapper / World Economic Outlook) — AFRREO","source_link":"https://www.imf.org/external/datamapper/GGXCNL_GDP@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Solde budgétaire global, dons compris (en pourcentage du PIB)","region":"","theme":"finance","source_group":"imf"},{"code":"NAT.od.imf_weo.GGXCNL_NGDP","name":"Capacité/besoin de financement des administrations publiques (% du PIB)","unit":"% du PIB","source":"FMI (DataMapper / World Economic Outlook) — WEO","source_link":"https://www.imf.org/external/datamapper/GGXCNL_NGDP@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Le prêt net (+) / emprunt net (−) est calculé comme la différence entre les recettes et les dépenses totales. Il s'agit d'un solde essentiel des stati","region":"","theme":"finance","source_group":"imf"},{"code":"NAT.od.imf_weo.GGXONLB_G01_GDP_PT","name":"Capacité/besoin de financement primaire (aussi appelé solde primaire)","unit":"% du PIB","source":"FMI (DataMapper / World Economic Outlook)","source_link":"https://www.imf.org/external/datamapper/GGXONLB_G01_GDP_PT@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Solde global hors paiements nets d'intérêts (charges d'intérêts moins recettes d'intérêts).","region":"","theme":"finance","source_group":"imf"},{"code":"NAT.od.imf_weo.GGXWDG_GDP","name":"Dette publique (% du PIB)","unit":"% du PIB","source":"FMI (DataMapper / World Economic Outlook) — AFRREO","source_link":"https://www.imf.org/external/datamapper/GGXWDG_GDP@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Dette publique (en pourcentage du PIB)","region":"","theme":"finance","source_group":"imf"},{"code":"NAT.od.imf_weo.GGXWDG_NGDP","name":"Dette brute des administrations publiques (% du PIB)","unit":"% du PIB","source":"FMI (DataMapper / World Economic Outlook) — WEO","source_link":"https://www.imf.org/external/datamapper/GGXWDG_NGDP@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"La dette brute comprend tous les engagements qui exigent le paiement, en une ou plusieurs dates futures, d'intérêts et/ou du principal par le débiteur","region":"","theme":"finance","source_group":"imf"},{"code":"NAT.od.imf_weo.GGX_GDP","name":"Dépenses publiques (% du PIB)","unit":"% du PIB","source":"FMI (DataMapper / World Economic Outlook) — AFRREO","source_link":"https://www.imf.org/external/datamapper/GGX_GDP@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Dépenses publiques (en pourcentage du PIB)","region":"","theme":"finance","source_group":"imf"},{"code":"NAT.od.imf_weo.GII_TC","name":"Indice d'inégalité de genre (IIG), cohérent dans le temps","unit":"Indice","source":"FMI (DataMapper / World Economic Outlook) — GD","source_link":"https://www.imf.org/external/datamapper/GII_TC@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"L'IIG (indice d'inégalité de genre) varie généralement de 0 à 1, des valeurs plus élevées signifiant une plus grande inégalité\n<b>Note</b> : Les graph","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.GRB_dummy","name":"Indicateur de budgétisation sensible au genre","unit":"Indice","source":"FMI (DataMapper / World Economic Outlook) — GD","source_link":"https://www.imf.org/external/datamapper/GRB_dummy@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"BSG : budgétisation sensible au genre (gender budgeting)\n3 - Pays pratiquant de façon marquée la BSG et couverts par les enquêtes\n2 - Autres pays prat","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.G_XWDG_G01_GDP_PT","name":"Position d'endettement brut","unit":"% du PIB","source":"FMI (DataMapper / World Economic Outlook)","source_link":"https://www.imf.org/external/datamapper/G_XWDG_G01_GDP_PT@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Ensemble des engagements qui exigent le paiement futur d'intérêts et/ou du principal par le débiteur au créancier. Il s'agit notamment des engagements","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.G_X_G01_GDP_PT","name":"Dépenses","unit":"% du PIB","source":"FMI (DataMapper / World Economic Outlook)","source_link":"https://www.imf.org/external/datamapper/G_X_G01_GDP_PT@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Dépenses","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.HCLMP","name":"Capital humain et politiques du marché du travail","unit":"Indice","source":"FMI (DataMapper / World Economic Outlook) — AIPI","source_link":"https://www.imf.org/external/datamapper/HCLMP@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Capital humain et politiques du marché du travail","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.IEI","name":"Innovation et intégration économique","unit":"Indice","source":"FMI (DataMapper / World Economic Outlook) — AIPI","source_link":"https://www.imf.org/external/datamapper/IEI@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"Innovation et intégration économique","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.Ka_bo","name":"Indice d'ouverture aux obligations (1 = entièrement libéralisé)","unit":"Unités","source":"FMI (DataMapper / World Economic Outlook) — CL","source_link":"https://www.imf.org/external/datamapper/Ka_bo@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"L'indice d'ouverture aux obligations mesure la capacité d'effectuer des opérations sur des obligations ou d'autres titres de créance (billets et oblig","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.Ka_cc","name":"Indice d'ouverture du crédit commercial (1 = entièrement libéralisé)","unit":"Unités","source":"FMI (DataMapper / World Economic Outlook) — CL","source_link":"https://www.imf.org/external/datamapper/Ka_cc@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"L'indice d'ouverture au crédit commercial mesure la capacité d'effectuer des opérations directement liées à des transactions commerciales internationa","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.Ka_ci","name":"Indice d'ouverture aux placements collectifs (1 = entièrement libéralisé)","unit":"Unités","source":"FMI (DataMapper / World Economic Outlook) — CL","source_link":"https://www.imf.org/external/datamapper/Ka_ci@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"L'indice d'ouverture aux placements collectifs mesure la capacité d'effectuer des opérations sur des parts et des inscriptions en registre ou d'autres","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.Ka_di","name":"Indice d'ouverture à l'investissement direct (1 = entièrement libéralisé)","unit":"Unités","source":"FMI (DataMapper / World Economic Outlook) — CL","source_link":"https://www.imf.org/external/datamapper/Ka_di@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"L'indice d'ouverture aux investissements directs mesure la capacité d'effectuer des investissements visant à établir des relations économiques durable","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.Ka_dr","name":"Indice d'ouverture aux instruments dérivés (1 = entièrement libéralisé)","unit":"Unités","source":"FMI (DataMapper / World Economic Outlook) — CL","source_link":"https://www.imf.org/external/datamapper/Ka_dr@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"L'indice d'ouverture aux produits dérivés mesure la capacité d'effectuer des opérations sur des droits, des bons de souscription, des options financiè","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.Ka_eq","name":"Indice d'ouverture aux actions (1 = entièrement libéralisé)","unit":"Unités","source":"FMI (DataMapper / World Economic Outlook) — CL","source_link":"https://www.imf.org/external/datamapper/Ka_eq@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"L'indice d'ouverture aux actions mesure la capacité d'effectuer des transactions portant sur des actions et d'autres titres de nature participative, à","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.Ka_fc","name":"Indice d'ouverture du crédit financier (1 = entièrement libéralisé)","unit":"Unités","source":"FMI (DataMapper / World Economic Outlook) — CL","source_link":"https://www.imf.org/external/datamapper/Ka_fc@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"L'indice d'ouverture au crédit financier mesure la capacité d'effectuer des opérations de crédit autres que les crédits commerciaux, accordés par tous","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.Ka_gu","name":"Indice d'ouverture aux garanties (1 = entièrement libéralisé)","unit":"Unités","source":"FMI (DataMapper / World Economic Outlook) — CL","source_link":"https://www.imf.org/external/datamapper/Ka_gu@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"L'indice d'ouverture aux garanties mesure la capacité d'effectuer des opérations par le biais de garanties, de cautionnements et de facilités de souti","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.Ka_mm","name":"Indice d'ouverture du marché monétaire (1 = entièrement libéralisé)","unit":"Unités","source":"FMI (DataMapper / World Economic Outlook) — CL","source_link":"https://www.imf.org/external/datamapper/Ka_mm@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"L'indice d'ouverture au marché monétaire mesure la capacité d'effectuer des opérations sur des titres d'une échéance initiale inférieure ou égale à un","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.LP","name":"Population (millions)","unit":"Millions de personnes","source":"FMI (DataMapper / World Economic Outlook) — WEO","source_link":"https://www.imf.org/external/datamapper/LP@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. 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Licence : Conditions d'utilisation du FMI (réutilisation libre avec citation).","description":"","region":"","theme":"macro","source_group":"imf"},{"code":"NAT.od.imf_weo.NGDPXO_RPCH","name":"Croissance du PIB réel hors pétrole","unit":"Variation annuelle en pourcentage","source":"FMI (DataMapper / World Economic Outlook) — AFRREO","source_link":"https://www.imf.org/external/datamapper/NGDPXO_RPCH@WEO/CIV","methodology":"Séries du FMI (World Economic Outlook, Fiscal Monitor, etc.). Les dernières années sont des PROJECTIONS du FMI. Données récupérées automatiquement via l'API le 2026-11-01. 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Licence : Conditions FMI PortWatch (citation requise).","description":"Volume importé par voie maritime, cumul annuel, Port de San Pedro.","region":"San Pedro","var":"portwatch:418","theme":"inter","source_group":"imf"},{"code":"NAT.od.portwatch.import.Total","name":"Volume importé par voie maritime — tous les ports ivoiriens (FMI PortWatch)","unit":"tonnes","source":"FMI (PortWatch – activité portuaire)","source_link":"https://portwatch.imf.org/","methodology":"Escales et volumes de marchandises estimés à partir des signaux AIS des navires (FMI / Université d'Oxford). Cumul par année civile complète, par port et pour l'ensemble du pays. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Conditions FMI PortWatch (citation requise).","description":"Volume importé par voie maritime, cumul annuel, tous les ports ivoiriens.","region":"","var":"portwatch:418","theme":"inter","source_group":"imf"},{"code":"NAT.od.portwatch.portcalls.Abidjan","name":"Escales de navires — Port d'Abidjan (FMI PortWatch)","unit":"escales","source":"FMI (PortWatch – activité portuaire)","source_link":"https://portwatch.imf.org/","methodology":"Escales et volumes de marchandises estimés à partir des signaux AIS des navires (FMI / Université d'Oxford). Cumul par année civile complète, par port et pour l'ensemble du pays. Données récupérées automatiquement via l'API le 2026-11-03. Licence : Conditions FMI PortWatch (citation requise).","description":"Escales de navires, cumul annuel, Port d'Abidjan.","region":"Abidjan","var":"portwatch:419","theme":"inter","source_group":"imf"},{"code":"NAT.od.portwatch.portcalls.San_Pedro","name":"Escales de navires — Port de San Pedro (FMI PortWatch)","unit":"escales","source":"FMI (PortWatch – activité portuaire)","source_link":"https://portwatch.imf.org/","methodology":"Escales et volumes de marchandises estimés à partir des signaux AIS des navires (FMI / Université d'Oxford). Cumul par année civile complète, par port et pour l'ensemble du pays. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Eurostat (réutilisation libre), IRENA (citation), HCR (CC BY 4.0).","description":"Importations de l’UE en provenance de Côte d’Ivoire, chapitre SH 15 (Eurostat Comext).","region":"","var":"trade_energy:420","theme":"inter","source_group":"eurostat"},{"code":"NAT.od.trade_energy.EU.1.18","name":"Importations de l’UE en provenance de Côte d’Ivoire — cacao et préparations (millions €)","unit":"millions EUR","source":"Eurostat, IRENA et HCR — Eurostat Comext","source_link":"https://ec.europa.eu/eurostat/comext/newxtweb/","methodology":"Commerce de l'Union européenne avec la Côte d'Ivoire (Eurostat, en millions d'euros), capacités et production d'électricité renouvelable (IRENA), réfugiés et demandeurs d'asile (HCR). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Eurostat (réutilisation libre), IRENA (citation), HCR (CC BY 4.0).","description":"Importations de l’UE en provenance de Côte d’Ivoire, chapitre SH 18 (Eurostat Comext).","region":"","var":"trade_energy:420","theme":"inter","source_group":"eurostat"},{"code":"NAT.od.trade_energy.EU.1.27","name":"Importations de l’UE en provenance de Côte d’Ivoire — combustibles minéraux, pétrole (millions €)","unit":"millions EUR","source":"Eurostat, IRENA et HCR — Eurostat Comext","source_link":"https://ec.europa.eu/eurostat/comext/newxtweb/","methodology":"Commerce de l'Union européenne avec la Côte d'Ivoire (Eurostat, en millions d'euros), capacités et production d'électricité renouvelable (IRENA), réfugiés et demandeurs d'asile (HCR). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Eurostat (réutilisation libre), IRENA (citation), HCR (CC BY 4.0).","description":"Importations de l’UE en provenance de Côte d’Ivoire, chapitre SH 27 (Eurostat Comext).","region":"","var":"trade_energy:420","theme":"inter","source_group":"eurostat"},{"code":"NAT.od.trade_energy.EU.1.40","name":"Importations de l’UE en provenance de Côte d’Ivoire — Caoutchouc (millions €)","unit":"millions EUR","source":"Eurostat, IRENA et HCR — Eurostat Comext","source_link":"https://ec.europa.eu/eurostat/comext/newxtweb/","methodology":"Commerce de l'Union européenne avec la Côte d'Ivoire (Eurostat, en millions d'euros), capacités et production d'électricité renouvelable (IRENA), réfugiés et demandeurs d'asile (HCR). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Eurostat (réutilisation libre), IRENA (citation), HCR (CC BY 4.0).","description":"Importations de l’UE en provenance de Côte d’Ivoire, chapitre SH 40 (Eurostat Comext).","region":"","var":"trade_energy:420","theme":"inter","source_group":"eurostat"},{"code":"NAT.od.trade_energy.EU.1.44","name":"Importations de l’UE en provenance de Côte d’Ivoire — Bois (millions €)","unit":"millions EUR","source":"Eurostat, IRENA et HCR — Eurostat Comext","source_link":"https://ec.europa.eu/eurostat/comext/newxtweb/","methodology":"Commerce de l'Union européenne avec la Côte d'Ivoire (Eurostat, en millions d'euros), capacités et production d'électricité renouvelable (IRENA), réfugiés et demandeurs d'asile (HCR). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Eurostat (réutilisation libre), IRENA (citation), HCR (CC BY 4.0).","description":"Importations de l’UE en provenance de Côte d’Ivoire, chapitre SH 44 (Eurostat Comext).","region":"","var":"trade_energy:420","theme":"inter","source_group":"eurostat"},{"code":"NAT.od.trade_energy.EU.1.TOTAL","name":"Importations de l’UE en provenance de Côte d’Ivoire — Tous produits (millions €)","unit":"millions EUR","source":"Eurostat, IRENA et HCR — Eurostat Comext","source_link":"https://ec.europa.eu/eurostat/comext/newxtweb/","methodology":"Commerce de l'Union européenne avec la Côte d'Ivoire (Eurostat, en millions d'euros), capacités et production d'électricité renouvelable (IRENA), réfugiés et demandeurs d'asile (HCR). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Eurostat (réutilisation libre), IRENA (citation), HCR (CC BY 4.0).","description":"Importations de l’UE en provenance de Côte d’Ivoire, chapitre SH TOTAL (Eurostat Comext).","region":"","var":"trade_energy:420","theme":"inter","source_group":"eurostat"},{"code":"NAT.od.trade_energy.EU.2.03","name":"Exportations de l’UE vers la Côte d’Ivoire — Poissons (millions €)","unit":"millions EUR","source":"Eurostat, IRENA et HCR — Eurostat Comext","source_link":"https://ec.europa.eu/eurostat/comext/newxtweb/","methodology":"Commerce de l'Union européenne avec la Côte d'Ivoire (Eurostat, en millions d'euros), capacités et production d'électricité renouvelable (IRENA), réfugiés et demandeurs d'asile (HCR). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Eurostat (réutilisation libre), IRENA (citation), HCR (CC BY 4.0).","description":"Exportations de l’UE vers la Côte d’Ivoire, chapitre SH 03 (Eurostat Comext).","region":"","var":"trade_energy:421","theme":"inter","source_group":"eurostat"},{"code":"NAT.od.trade_energy.EU.2.08","name":"Exportations de l’UE vers la Côte d’Ivoire — fruits (dont noix de cajou, bananes) (millions €)","unit":"millions EUR","source":"Eurostat, IRENA et HCR — Eurostat Comext","source_link":"https://ec.europa.eu/eurostat/comext/newxtweb/","methodology":"Commerce de l'Union européenne avec la Côte d'Ivoire (Eurostat, en millions d'euros), capacités et production d'électricité renouvelable (IRENA), réfugiés et demandeurs d'asile (HCR). Données récupérées automatiquement via l'API le 2026-11-03. Licence : Eurostat (réutilisation libre), IRENA (citation), HCR (CC BY 4.0).","description":"Exportations de l’UE vers la Côte d’Ivoire, chapitre SH 08 (Eurostat Comext).","region":"","var":"trade_energy:421","theme":"inter","source_group":"eurostat"},{"code":"NAT.od.trade_energy.EU.2.15","name":"Exportations de l’UE vers la Côte d’Ivoire — huiles (dont huile de palme) (millions €)","unit":"millions EUR","source":"Eurostat, IRENA et HCR — Eurostat Comext","source_link":"https://ec.europa.eu/eurostat/comext/newxtweb/","methodology":"Commerce de l'Union européenne avec la Côte d'Ivoire (Eurostat, en millions d'euros), capacités et production d'électricité renouvelable (IRENA), réfugiés et demandeurs d'asile (HCR). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Eurostat (réutilisation libre), IRENA (citation), HCR (CC BY 4.0).","description":"Exportations de l’UE vers la Côte d’Ivoire, chapitre SH 18 (Eurostat Comext).","region":"","var":"trade_energy:421","theme":"inter","source_group":"eurostat"},{"code":"NAT.od.trade_energy.EU.2.27","name":"Exportations de l’UE vers la Côte d’Ivoire — combustibles minéraux, pétrole (millions €)","unit":"millions EUR","source":"Eurostat, IRENA et HCR — Eurostat Comext","source_link":"https://ec.europa.eu/eurostat/comext/newxtweb/","methodology":"Commerce de l'Union européenne avec la Côte d'Ivoire (Eurostat, en millions d'euros), capacités et production d'électricité renouvelable (IRENA), réfugiés et demandeurs d'asile (HCR). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Eurostat (réutilisation libre), IRENA (citation), HCR (CC BY 4.0).","description":"Exportations de l’UE vers la Côte d’Ivoire, chapitre SH 40 (Eurostat Comext).","region":"","var":"trade_energy:421","theme":"inter","source_group":"eurostat"},{"code":"NAT.od.trade_energy.EU.2.44","name":"Exportations de l’UE vers la Côte d’Ivoire — Bois (millions €)","unit":"millions EUR","source":"Eurostat, IRENA et HCR — Eurostat Comext","source_link":"https://ec.europa.eu/eurostat/comext/newxtweb/","methodology":"Commerce de l'Union européenne avec la Côte d'Ivoire (Eurostat, en millions d'euros), capacités et production d'électricité renouvelable (IRENA), réfugiés et demandeurs d'asile (HCR). Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : Conditions d’utilisation des données de l’ONU (citation de la source).","description":"Indicateur ODD 17.16.1. Nombre de pays faisant état de progrès dans les cadres multipartites de suivi de l'efficacité du développement à l'appui de la","region":"","theme":"social","source_group":"un"},{"code":"NAT.od.un_sdg.SG_PLN_RECNDI","name":"Proportion d'objectifs de projets, dans les nouvelles interventions de développement, tirés des cadres de résultats définis par les pays – données par bénéficiaire (%)","unit":"%","source":"ONU (Base mondiale des indicateurs ODD) — ODD 17.15.1","source_link":"https://unstats.un.org/sdgs/dataportal/database?series=SG_PLN_RECNDI","methodology":"Indicateurs des Objectifs de développement durable compilés par la Division de statistique de l'ONU à partir des agences dépositaires. Série « total » retenue lorsque l'indicateur est désagrégé. Données récupérées automatiquement via l'API le 2026-11-01. 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Licence : Conditions d’utilisation des données de l’ONU (citation de la source).","description":"Indicateur ODD 17.19.2. Pays dont les données d'enregistrement des naissances sont complètes à au moins 90 % (1 = OUI ; 0 = NON)","region":"","theme":"demo","source_group":"un"},{"code":"NAT.od.un_sdg.SG_REG_CENSUSN","name":"Pays ayant réalisé au moins un recensement de la population et de l'habitat au cours des 10 dernières années (1 = OUI ; 0 = NON)","unit":"Nombre","source":"ONU (Base mondiale des indicateurs ODD) — ODD 17.19.2","source_link":"https://unstats.un.org/sdgs/dataportal/database?series=SG_REG_CENSUSN","methodology":"Indicateurs des Objectifs de développement durable compilés par la Division de statistique de l'ONU à partir des agences dépositaires. Série « total » retenue lorsque l'indicateur est désagrégé. Données récupérées automatiquement via l'API le 2026-11-01. 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Licence : Conditions d’utilisation des données de l’ONU (citation de la source).","description":"Indicateur ODD 5.6.2. (S.1.C.3) Mesure dans laquelle les pays disposent de lois et de règlements garantissant aux femmes et aux hommes âgés de 15 ans ","region":"","theme":"sante","source_group":"un"},{"code":"NAT.od.un_sdg.SH_LGR_ACSRHEC4","name":"(S.1.C.4) Mesure dans laquelle les pays disposent de lois et de règlements garantissant aux femmes et aux hommes âgés de 15 ans et plus un accès complet et égal aux soins, à l'information et à l'éducation en matière de santé sexuelle et reproductive : Composante 4 : Soins après avortement (%)","unit":"%","source":"ONU (Base mondiale des indicateurs ODD) — ODD 5.6.2","source_link":"https://unstats.un.org/sdgs/dataportal/database?series=SH_LGR_ACSRHEC4","methodology":"Indicateurs des Objectifs de développement durable compilés par la Division de statistique de l'ONU à partir des agences dépositaires. 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Taux de chômage, par sexe et âge - 19e CIST (%)","region":"","theme":"emploi","source_group":"un"},{"code":"NAT.od.un_sdg.SM_DTH_MIGR","name":"Nombre total de décès et disparitions enregistrés lors de migrations (nombre)","unit":"Nombre","source":"ONU (Base mondiale des indicateurs ODD) — ODD 10.7.3","source_link":"https://unstats.un.org/sdgs/dataportal/database?series=SM_DTH_MIGR","methodology":"Indicateurs des Objectifs de développement durable compilés par la Division de statistique de l'ONU à partir des agences dépositaires. Série « total » retenue lorsque l'indicateur est désagrégé. Données récupérées automatiquement via l'API le 2026-11-01. Licence : Conditions d’utilisation des données de l’ONU (citation de la source).","description":"Indicateur ODD 10.7.3. 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Licence : CC BY 3.0 IGO.","description":"Rapport de dépendance des enfants","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_DPR_OLD","name":"Rapport de dépendance des personnes âgées","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_DPR_OLD/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Rapport de dépendance des personnes âgées","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_DPR_TOT","name":"Rapport de dépendance total","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_DPR_TOT/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Rapport de dépendance total","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_FRATE_TOT","name":"Indice synthétique de fécondité","unit":"Nombre","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_FRATE_TOT/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Indice synthétique de fécondité","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_LIFE_EXP","name":"Espérance de vie","unit":"Années","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_LIFE_EXP/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Espérance de vie","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_NET_MG_RATE","name":"Taux de migration nette (pour 1 000 habitants)","unit":"Nombre","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_NET_MG_RATE/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Taux de migration nette (pour 1 000 habitants)","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_POP_15TO24","name":"Population jeune de 15 à 24 ans","unit":"Personnes","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_POP_15TO24/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Population jeune de 15 à 24 ans","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_POP_ADLCNT","name":"Population adolescente (10-19 ans)","unit":"Personnes","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_POP_ADLCNT/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Population adolescente (10-19 ans)","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_POP_ADLCNT_PROP","name":"Population adolescente en proportion de la population totale (%)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_POP_ADLCNT_PROP/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Population adolescente en proportion de la population totale (%)","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_POP_CHILD_PROP","name":"Population d'enfants en proportion de la population totale (%)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_POP_CHILD_PROP/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Population d'enfants en proportion de la population totale (%)","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_POP_GRT","name":"Taux de croissance annuel de la population","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_POP_GRT/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Taux de croissance annuel de la population","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_POP_TOT","name":"Population totale","unit":"Personnes","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_POP_TOT/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Population totale","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_POP_U18","name":"Population de moins de 18 ans","unit":"Personnes","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_POP_U18/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Population de moins de 18 ans","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.DM_POP_U5","name":"Population de moins de 5 ans","unit":"Personnes","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/DM_POP_U5/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Population de moins de 5 ans","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.ECD_CHLD_24-59M_ADLT_SRC","name":"Pourcentage d'enfants (24-59 mois) avec lesquels un adulte du ménage a pratiqué 4 activités ou plus de stimulation précoce et de soins attentifs au cours des 3 derniers jours","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/ECD_CHLD_24-59M_ADLT_SRC/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage d'enfants (24-59 mois) avec lesquels un adulte du ménage a pratiqué 4 activités ou plus de stimulation précoce et de soins attentifs au co","region":"","theme":"education","source_group":"unicef"},{"code":"NAT.od.unicef.ECD_CHLD_36-59M_EDU-PGM","name":"Pourcentage d'enfants de 36-59 mois fréquentant un programme d'éducation de la petite enfance","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/ECD_CHLD_36-59M_EDU-PGM/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage d'enfants de 36-59 mois fréquentant un programme d'éducation de la petite enfance","region":"","theme":"education","source_group":"unicef"},{"code":"NAT.od.unicef.ECD_CHLD_LMPSL","name":"Proportion d'enfants de 24-59 mois dont le développement est en bonne voie en matière de santé, d'apprentissage et de bien-être psychosocial, par sexe","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/ECD_CHLD_LMPSL/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Proportion d'enfants de 24-59 mois dont le développement est en bonne voie en matière de santé, d'apprentissage et de bien-être psychosocial, par sexe","region":"","theme":"education","source_group":"unicef"},{"code":"NAT.od.unicef.ECD_CHLD_U5_BKS-HM","name":"Pourcentage d'enfants de moins de 5 ans possédant 3 livres pour enfants ou plus","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/ECD_CHLD_U5_BKS-HM/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage d'enfants de moins de 5 ans possédant 3 livres pour enfants ou plus","region":"","theme":"education","source_group":"unicef"},{"code":"NAT.od.unicef.ECD_CHLD_U5_LFT-ALN","name":"Pourcentage d'enfants de moins de 5 ans laissés seuls ou sous la surveillance d'un autre enfant de moins de 10 ans pendant plus d'une heure au moins une fois au cours de la dernière semaine","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/ECD_CHLD_U5_LFT-ALN/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage d'enfants de moins de 5 ans laissés seuls ou sous la surveillance d'un autre enfant de moins de 10 ans pendant plus d'une heure au moins u","region":"","theme":"education","source_group":"unicef"},{"code":"NAT.od.unicef.ECD_CHLD_U5_PLYTH-HM","name":"Pourcentage d'enfants de moins de 5 ans jouant avec 2 types de jouets ou plus","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/ECD_CHLD_U5_PLYTH-HM/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage d'enfants de moins de 5 ans jouant avec 2 types de jouets ou plus","region":"","theme":"education","source_group":"unicef"},{"code":"NAT.od.unicef.ECON_GVT_EDU_EXP_PTEXP","name":"Dépenses publiques d'éducation (% du budget de l'État)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/ECON_GVT_EDU_EXP_PTEXP/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Dépenses publiques d'éducation (% du PIB)","region":"","theme":"macro","source_group":"unicef"},{"code":"NAT.od.unicef.ECON_GVT_EXP_PTGDP","name":"Dépenses publiques (% du PIB)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/ECON_GVT_EXP_PTGDP/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Dépenses publiques (% du PIB)","region":"","theme":"macro","source_group":"unicef"},{"code":"NAT.od.unicef.ECON_GVT_HLTH_EXP_PTEXP","name":"Dépenses publiques de santé (% du budget de l'État)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/ECON_GVT_HLTH_EXP_PTEXP/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Dépenses publiques de santé (% du PIB)","region":"","theme":"macro","source_group":"unicef"},{"code":"NAT.od.unicef.ECON_GVT_REV_PTGDP","name":"Recettes publiques (% du PIB)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/ECON_GVT_REV_PTGDP/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Adolescentes avec une anémie quelconque","region":"","theme":"social","source_group":"unicef"},{"code":"NAT.od.unicef.GN_ED_ATTN","name":"Niveau d'instruction de la population (25 ans et plus)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/GN_ED_ATTN/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Niveau d'instruction de la population (25 ans et plus)","region":"","theme":"social","source_group":"unicef"},{"code":"NAT.od.unicef.GN_FB_BNK_ACCSS","name":"Proportion d'adolescents et d'adultes (15 ans et plus) titulaires d'un compte dans une institution financière ou auprès d'un prestataire de services d'argent mobile","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/GN_FB_BNK_ACCSS/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Proportion de personnes possédant un téléphone mobile","region":"","theme":"social","source_group":"unicef"},{"code":"NAT.od.unicef.GN_LF_PTCPN","name":"Taux d'activité","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/GN_LF_PTCPN/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Taux d'activité","region":"","theme":"social","source_group":"unicef"},{"code":"NAT.od.unicef.GN_MTNTY_LV_BNFTS","name":"Prestations de congé de maternité","unit":"Nombre de décès","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/GN_MTNTY_LV_BNFTS/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Pourcentage de nourrissons survivants ayant reçu la première dose du vaccin contenant la valence DTC","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_DTP3","name":"Pourcentage de nourrissons survivants ayant reçu la troisième dose du vaccin contenant la valence DTC","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_DTP3/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage de nourrissons survivants ayant reçu la troisième dose du vaccin contenant la valence DTC","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_HEPB3","name":"Pourcentage de nourrissons survivants ayant reçu la troisième dose du vaccin contenant l'hépatite B","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_HEPB3/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage de nourrissons survivants ayant reçu la troisième dose du vaccin contenant l'hépatite B","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_HEPBB","name":"Pourcentage de naissances vivantes ayant reçu le vaccin contenant l'hépatite B dans les 24 heures suivant la naissance","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_HEPBB/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage de naissances vivantes ayant reçu le vaccin contenant l'hépatite B dans les 24 heures suivant la naissance","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_HIB3","name":"Pourcentage de nourrissons survivants ayant reçu la troisième dose du vaccin contenant Hib","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_HIB3/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage de nourrissons survivants ayant reçu la troisième dose du vaccin contenant Hib","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_HPV","name":"Pourcentage de femmes ayant reçu la dernière dose du vaccin contre le papillomavirus humain (VPH) selon le calendrier national","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_HPV/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage de femmes ayant reçu la dernière dose du vaccin contre le papillomavirus humain (VPH) selon le calendrier national","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_IPV1","name":"Pourcentage de nourrissons survivants ayant reçu la première dose du vaccin contenant le poliovirus inactivé","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_IPV1/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage de nourrissons survivants ayant reçu la première dose du vaccin contenant le poliovirus inactivé","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_IPVC","name":"VPI, dernière dose","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_IPVC/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"VPI, dernière dose","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_MCV1","name":"Pourcentage de nourrissons survivants ayant reçu la première dose du vaccin contenant la valence rougeole","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_MCV1/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage de nourrissons survivants ayant reçu la première dose du vaccin contenant la valence rougeole","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_MCV2","name":"Pourcentage d'enfants ayant reçu la 2e dose du vaccin contenant la valence rougeole, selon le calendrier national","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_MCV2/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage d'enfants ayant reçu la 2e dose du vaccin contenant la valence rougeole, selon le calendrier national","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_MENGA","name":"Pourcentage de nourrissons survivants ayant reçu le vaccin antiméningococcique A conjugué","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_MENGA/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage de nourrissons survivants ayant reçu le vaccin antiméningococcique A conjugué","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_PAB","name":"Pourcentage de nouveau-nés protégés à la naissance contre le tétanos par l'anatoxine tétanique","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_PAB/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage de nouveau-nés protégés à la naissance contre le tétanos par l'anatoxine tétanique","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_PCVC","name":"Dernière dose de VPC (vaccin antipneumococcique conjugué)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_PCVC/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Dernière dose de VPC (vaccin antipneumococcique conjugué)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_RCV1","name":"Pourcentage de nourrissons survivants ayant reçu la première dose du vaccin contenant la valence rubéole","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_RCV1/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Pourcentage de nourrissons survivants ayant reçu la dernière dose du vaccin contenant le rotavirus (2e ou 3e dose selon le vaccin utilisé)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.IM_YFV","name":"Pourcentage de nourrissons survivants ayant reçu le vaccin contenant la fièvre jaune (pour les pays à risque et où le vaccin figure dans le calendrier national)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/IM_YFV/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage de nourrissons survivants ayant reçu le vaccin contenant la fièvre jaune (pour les pays à risque et où le vaccin figure dans le calendrier","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MG_INTERNAL_DISP_PERS","name":"Personnes déplacées internes (PDI)","unit":"Personnes","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MG_INTERNAL_DISP_PERS/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Personnes déplacées internes (PDI)","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.MG_INTNL_MG_CNTRY_DEST","name":"Migrants internationaux, par pays de destination","unit":"Personnes","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MG_INTNL_MG_CNTRY_DEST/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Migrants internationaux, par pays de destination","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.MG_NEW_INTERNAL_DISP","name":"Nouveaux déplacements internes","unit":"Nombre","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MG_NEW_INTERNAL_DISP/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Nouveaux déplacements internes","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.MG_RFGS_CNTRY_ASYLM","name":"Réfugiés, par pays d'asile","unit":"Personnes","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MG_RFGS_CNTRY_ASYLM/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Réfugiés, par pays d'asile","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.MG_RFGS_CNTRY_ASYLM_PER1000","name":"Réfugiés par pays d'accueil, pour 1 000 habitants","unit":"Pour 1 000","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MG_RFGS_CNTRY_ASYLM_PER1000/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Réfugiés par pays d'accueil, pour 1 000 habitants","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.MG_RFGS_CNTRY_ASYLM_PER_USD_GNI","name":"Réfugiés par pays d'accueil, pour 1 dollar US de RNB par habitant","unit":"pour 1 USD de RNB par habitant","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MG_RFGS_CNTRY_ASYLM_PER_USD_GNI/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Réfugiés par pays d'accueil, pour 1 dollar US de RNB par habitant","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.MG_RFGS_CNTRY_ORIGIN","name":"Réfugiés, par pays d'origine","unit":"Personnes","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MG_RFGS_CNTRY_ORIGIN/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Réfugiés, par pays d'origine","region":"","theme":"demo","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_ABR","name":"Taux de natalité chez les adolescentes (nombre de naissances vivantes chez les adolescentes pour 1 000 adolescentes)","unit":"Naissances pour 1 000 femmes","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_ABR/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Pourcentage d'adolescents (15-19 ans) ayant consommé au moins une boisson alcoolisée à un moment quelconque au cours des 12 derniers mois","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_ADO_TOBACCO","name":"Pourcentage d'adolescents (13-15 ans) ayant fumé des cigarettes ou consommé des produits du tabac fumé ou sans fumée à un moment quelconque au cours du dernier mois","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_ADO_TOBACCO/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage d'adolescents (13-15 ans) ayant fumé des cigarettes ou consommé des produits du tabac fumé ou sans fumée à un moment quelconque au cours d","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_ANC1","name":"Soins prénatals, 1 visite ou plus - pourcentage de femmes (15-49 ans) vues au moins une fois pendant la grossesse par du personnel de santé qualifié","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_ANC1/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Soins prénatals, 4 visites ou plus - pourcentage de femmes (15-49 ans) vues au moins quatre fois pendant la grossesse par un prestataire quelconque","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_BIRTH18","name":"Maternité précoce - pourcentage de femmes (20-24 ans) ayant donné naissance avant 18 ans","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_BIRTH18/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Demande de planification familiale satisfaite par des méthodes modernes - pourcentage de femmes (15-49 ans)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_DIARCARE","name":"Recours aux soins pour la diarrhée - pourcentage d'enfants (de moins de 5 ans) atteints de diarrhée pour lesquels des conseils ou un traitement ont été recherchés auprès d'un établissement ou d'un prestataire de santé","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_DIARCARE/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Recours aux soins pour la diarrhée - pourcentage d'enfants (de moins de 5 ans) atteints de diarrhée pour lesquels des conseils ou un traitement ont ét","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_INFDEC","name":"Proportion de femmes de 15-19 ans prenant elles-mêmes des décisions éclairées concernant les relations sexuelles, l'utilisation de contraceptifs et les soins de santé procréative","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_INFDEC/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Proportion de femmes de 15-19 ans prenant elles-mêmes des décisions éclairées concernant les relations sexuelles, l'utilisation de contraceptifs et le","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_INSTDEL","name":"Accouchements en établissement de santé – pourcentage d'accouchements dans un établissement de santé","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_INSTDEL/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Accouchements en établissement de santé – pourcentage d'accouchements dans un établissement de santé","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_IPTP","name":"TPI chez les femmes enceintes – pourcentage de femmes (15-49 ans) ayant reçu trois doses ou plus de traitement préventif intermittent lors des consultations prénatales pendant leur dernière grossesse","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_IPTP/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"TPI chez les femmes enceintes – pourcentage de femmes (15-49 ans) ayant reçu trois doses ou plus de traitement préventif intermittent lors des consult","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_ITN","name":"Utilisation de MII par les enfants – pourcentage d'enfants (de moins de 5 ans) ayant dormi sous une moustiquaire imprégnée d'insecticide la nuit précédant l'enquête","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_ITN/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Utilisation de MII par les enfants – pourcentage d'enfants (de moins de 5 ans) ayant dormi sous une moustiquaire imprégnée d'insecticide la nuit précé","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_ITN2","name":"Ménages disposant de moustiquaires imprégnées d'insecticide (MII) et/ou ayant bénéficié d'une pulvérisation intra-domiciliaire d'insecticide à effet rémanent (PID) – pourcentage de ménages ayant au moins une MII pour deux personnes et/ou une PID au cours des 12 derniers mois","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_ITN2/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Ménages disposant de moustiquaires imprégnées d'insecticide (MII) et/ou ayant bénéficié d'une pulvérisation intra-domiciliaire d'insecticide à effet r","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_ITNOWN","name":"Pourcentage de ménages possédant au moins une moustiquaire imprégnée d'insecticide (MII)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_ITNOWN/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pourcentage de ménages possédant au moins une moustiquaire imprégnée d'insecticide (MII)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_ITNPREG","name":"Femmes enceintes dormant sous MII – pourcentage de femmes enceintes (15-49 ans) ayant dormi sous une moustiquaire imprégnée d'insecticide la nuit précédente","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_ITNPREG/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Femmes enceintes dormant sous MII – pourcentage de femmes enceintes (15-49 ans) ayant dormi sous une moustiquaire imprégnée d'insecticide la nuit préc","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_LIFE_EXPECTANCY","name":"Espérance de vie à la naissance – nombre d'années que vivraient les nouveau-nées de sexe féminin si elles étaient soumises aux risques de mortalité observés dans la population au moment de leur naissance (estimation)","unit":"Nombre","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_LIFE_EXPECTANCY/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Espérance de vie à la naissance – nombre d'années que vivraient les nouveau-nées de sexe féminin si elles étaient soumises aux risques de mortalité ob","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_LTR_MATERNAL_DEATH","name":"Risque de décès maternel sur la durée de vie (probabilité (1 sur X) qu'une fille de 15 ans (l'année de l'estimation) décède un jour d'une cause maternelle)","unit":"1 sur X","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_LTR_MATERNAL_DEATH/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Risque de décès maternel sur la durée de vie (probabilité (1 sur X) qu'une fille de 15 ans (l'année de l'estimation) décède un jour d'une cause matern","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_MATERNAL_DEATHS","name":"Décès maternels (estimés)","unit":"Nombre","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_MATERNAL_DEATHS/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Décès maternels (estimés)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_MLRACT","name":"Paludisme, traitement de première intention – pourcentage d'enfants fébriles (moins de 5 ans) recevant un CTA (antipaludique de première intention), parmi ceux recevant un antipaludique quelconque","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_MLRACT/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Recours aux soins pour les enfants fébriles - pourcentage d'enfants (de moins de 5 ans) avec de la fièvre pour lesquels des conseils ou un traitement ","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_MLRDIAG","name":"Diagnostic du paludisme – pourcentage d'enfants fébriles (moins de 5 ans) ayant eu une piqûre au doigt ou au talon pour un test de dépistage du paludisme","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_MLRDIAG/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Diagnostic du paludisme – pourcentage d'enfants fébriles (moins de 5 ans) ayant eu une piqûre au doigt ou au talon pour un test de dépistage du paludi","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_MMR","name":"Ratio de mortalité maternelle (nombre de décès maternels pour 100 000 naissances vivantes)","unit":"Décès pour 100 000 naissances","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_MMR/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Ratio de mortalité maternelle (nombre de décès maternels pour 100 000 naissances vivantes)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_ORS","name":"Traitement de la diarrhée - pourcentage d'enfants (de moins de 5 ans) atteints de diarrhée ayant reçu des SRO (sachets ou liquides préconditionnés)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_ORS/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Traitement de la diarrhée - pourcentage d'enfants (de moins de 5 ans) atteints de diarrhée ayant reçu des SRO (sachets ou liquides préconditionnés)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_ORSZINC","name":"Traitement de la diarrhée - pourcentage d'enfants (de moins de 5 ans) atteints de diarrhée ayant reçu des SRO et du zinc","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_ORSZINC/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Traitement de la diarrhée - pourcentage d'enfants (de moins de 5 ans) atteints de diarrhée ayant reçu des SRO et du zinc","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_ORTCF","name":"Traitement de la diarrhée - pourcentage d'enfants (de moins de 5 ans) atteints de diarrhée ayant reçu une TRO (sels de réhydratation orale ou liquides faits maison recommandés ou augmentation des liquides) et dont l'alimentation a été poursuivie","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_ORTCF/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Traitement de la diarrhée - pourcentage d'enfants (de moins de 5 ans) atteints de diarrhée ayant reçu une TRO (sels de réhydratation orale ou liquides","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_PNCMOM","name":"Soins postnatals pour les mères – pourcentage de femmes (15-49 ans) ayant reçu des soins postnatals dans les 2 jours suivant l'accouchement","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_PNCMOM/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Personnel qualifié à l'accouchement - pourcentage d'accouchements assistés par du personnel de santé qualifié","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_UHC","name":"Couverture des services de santé essentiels","unit":"Indice","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_UHC/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Couverture des services de santé essentiels","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.MNCH_UHC_RMNCH","name":"Indice de couverture santé universelle pour les interventions de santé reproductive, maternelle, néonatale et infantile","unit":"Indice","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/MNCH_UHC_RMNCH/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Traitement de la diarrhée - pourcentage d'enfants (de moins de 5 ans) atteints de diarrhée ayant reçu du zinc","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_ANE_WOM_15_49_MOD","name":"Prévalence de l'anémie chez les femmes de 15-49 ans (estimations modélisées)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_ANE_WOM_15_49_MOD/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Prévalence de l'anémie chez les femmes de 15-49 ans (estimations modélisées)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_ANT_HAZ_NE2","name":"Taille pour âge < -2 ET (retard de croissance)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_ANT_HAZ_NE2/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Taille pour âge < -2 ET (retard de croissance)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_ANT_HAZ_NE2_MOD","name":"Taille pour âge < -2 ET (retard de croissance), estimations modélisées","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_ANT_HAZ_NE2_MOD/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Taille pour âge < -2 ET (retard de croissance), estimations modélisées","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_ANT_HAZ_NE2_MOD_NUMTH","name":"Taille pour âge < -2 ET (retard de croissance), estimations modélisées, effectifs touchés","unit":"1000","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_ANT_HAZ_NE2_MOD_NUMTH/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Taille pour âge < -2 ET (retard de croissance), estimations modélisées, effectifs touchés","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_ANT_WAZ_NE2","name":"Poids pour âge < -2 ET (insuffisance pondérale)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_ANT_WAZ_NE2/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Poids pour âge < -2 ET (insuffisance pondérale)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_ANT_WHZ_NE2","name":"Poids pour taille < -2 ET (émaciation)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_ANT_WHZ_NE2/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Poids pour taille < -2 ET (émaciation)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_ANT_WHZ_NE3","name":"Poids pour taille < -3 ET (émaciation sévère)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_ANT_WHZ_NE3/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Poids pour taille < -3 ET (émaciation sévère)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_ANT_WHZ_PO2","name":"Poids pour taille > +2 ET (surpoids)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_ANT_WHZ_PO2/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Poids pour taille > +2 ET (surpoids)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_ANT_WHZ_PO2_MOD","name":"Poids pour taille > +2 ET (surpoids), estimations modélisées","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_ANT_WHZ_PO2_MOD/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Poids pour taille > +2 ET (surpoids), estimations modélisées","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_ANT_WHZ_PO2_MOD_NUMTH","name":"Poids pour taille > +2 ET (surpoids), estimations modélisées, nombre de personnes touchées","unit":"1000","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_ANT_WHZ_PO2_MOD_NUMTH/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Poids pour taille > +2 ET (surpoids), estimations modélisées, nombre de personnes touchées","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_BF_CBF_12_23","name":"Poursuite de l'allaitement (12-23 mois)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_BF_CBF_12_23/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Poursuite de l'allaitement (12-23 mois)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_BF_EBF","name":"A déjà été allaité (0-23 mois)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_BF_EBF/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"A déjà été allaité (0-23 mois)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_BF_EIBF","name":"Initiation précoce de l'allaitement","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_BF_EIBF/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Initiation précoce de l'allaitement","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_BF_EXBF","name":"Allaitement exclusif (0-5 mois)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_BF_EXBF/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Allaitement exclusif (0-5 mois)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_BF_EXBF_2D","name":"Allaité exclusivement durant les deux premiers jours suivant la naissance","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_BF_EXBF_2D/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Allaité exclusivement durant les deux premiers jours suivant la naissance","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_BF_MIXMF","name":"Allaitement mixte (0-5 mois)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_BF_MIXMF/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Allaitement mixte (0-5 mois)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_BW_LBW","name":"Prévalence de l'insuffisance pondérale à la naissance chez les nouveau-nés","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_BW_LBW/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Prévalence de l'insuffisance pondérale à la naissance chez les nouveau-nés","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_BW_WEI","name":"Enfants dont le poids à la naissance est connu","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_BW_WEI/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Enfants dont le poids à la naissance est connu","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_CF_ASF","name":"Consommation d'œufs et/ou de chair (6-23 mois)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_CF_ASF/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Consommation d'œufs et/ou de chair (6-23 mois)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_CF_FG_0_T_2","name":"Pauvreté alimentaire sévère","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_CF_FG_0_T_2/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pauvreté alimentaire sévère","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_CF_FG_3_T_4","name":"Pauvreté alimentaire modérée","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_CF_FG_3_T_4/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Pauvreté alimentaire modérée","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_CF_ISSSF_FL","name":"Introduction d'aliments solides, semi-solides (6-8 mois)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_CF_ISSSF_FL/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Introduction d'aliments solides, semi-solides (6-8 mois)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_CF_MAD","name":"Alimentation minimale acceptable (enfants de 6 à 23 mois)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_CF_MAD/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Alimentation minimale acceptable (enfants de 6 à 23 mois)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_CF_MDD","name":"Diversité alimentaire minimale (enfants de 6 à 23 mois)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_CF_MDD/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Diversité alimentaire minimale (enfants de 6 à 23 mois)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_CF_MMF","name":"Fréquence minimale des repas (enfants de 6 à 23 mois)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_CF_MMF/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Fréquence minimale des repas (enfants de 6 à 23 mois)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_CF_ZEROFV","name":"Aucune consommation de légumes ou de fruits (6-23 mois)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_CF_ZEROFV/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Aucune consommation de légumes ou de fruits (6-23 mois)","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_DANT_BMI_G25_MOD","name":"Prévalence du surpoids chez les adultes, IMC ≥ 25 (estimation brute)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_DANT_BMI_G25_MOD/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Consommation de sel iodé (>0 ppm) parmi tous les ménages testés","region":"","theme":"sante","source_group":"unicef"},{"code":"NAT.od.unicef.NT_IOD_ANY_TS","name":"Consommation de sel iodé (>0 ppm) parmi tous les ménages testés disposant de sel","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/NT_IOD_ANY_TS/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Pourcentage d'enfants (1-14 ans) ayant subi des châtiments corporels et/ou des agressions psychologiques de la part des personnes qui s'occupent d'eux","region":"","theme":"social","source_group":"unicef"},{"code":"NAT.od.unicef.PT_CHLD_5-17_LBR_ECON","name":"Pourcentage d'enfants (5-17 ans) astreints au travail des enfants (activités économiques)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/PT_CHLD_5-17_LBR_ECON/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Proportion de la population utilisant au moins des services d'assainissement de base","region":"","theme":"territory","source_group":"unicef"},{"code":"NAT.od.unicef.WS_PPL_S-B","name":"Proportion de la population utilisant des services d'assainissement de base","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/WS_PPL_S-B/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Proportion de la population utilisant des services d'eau potable de base","region":"","theme":"territory","source_group":"unicef"},{"code":"NAT.od.unicef.WS_PPL_W-I","name":"Proportion de la population utilisant des sources d'eau potable améliorées","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/WS_PPL_W-I/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Proportion de la population utilisant des services d'eau potable limités","region":"","theme":"territory","source_group":"unicef"},{"code":"NAT.od.unicef.WS_PPL_W-NP","name":"Proportion de la population utilisant des sources d'eau potable améliorées non canalisées","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/WS_PPL_W-NP/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. Licence : CC BY 3.0 IGO.","description":"Proportion de la population utilisant des sources d'eau potable améliorées non canalisées","region":"","theme":"territory","source_group":"unicef"},{"code":"NAT.od.unicef.WS_PPL_W-P","name":"Proportion de la population utilisant des sources d'eau potable canalisées","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/WS_PPL_W-P/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Proportion d'écoles sans service d'assainissement","region":"","theme":"territory","source_group":"unicef"},{"code":"NAT.od.unicef.WS_SCH_W-I","name":"Proportion d'écoles disposant de sources d'eau potable améliorées","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/WS_SCH_W-I/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Proportion d'écoles sans service d'eau potable","region":"","theme":"territory","source_group":"unicef"},{"code":"NAT.od.unicef.WT_ADLS_10-17_LBR_ECON","name":"Seuils du travail des enfants (activité économique)","unit":"%","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/WT_ADLS_10-17_LBR_ECON/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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Licence : CC BY 3.0 IGO.","description":"Seuils du travail des enfants (tâches ménagères)","region":"","theme":"social","source_group":"unicef"},{"code":"NAT.od.unicef.WT_ADLS_10-17_TIME_HC","name":"Temps consacré aux tâches ménagères","unit":"Heures par semaine","source":"UNICEF (entrepôt de données)","source_link":"https://data.unicef.org/indicator-profile/WT_ADLS_10-17_TIME_HC/","methodology":"Indicateurs de l'UNICEF sur l'enfance (mortalité, nutrition, vaccination, éducation, protection, eau et assainissement). Série « total » retenue quand l'indicateur est ventilé. Données récupérées automatiquement via l'API le 2026-11-03. 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