The Database of Labor Markets and Social Security Information System (SIMS) is the most important source of information about jobs and pensions in Latin America and the Caribbean. It encompasses harmonized statistics of 23 countries in the region, assuring the comparability of the indicators among them and also over time. The dataset includes data since 1990 and it presents 72 main indicators, which can be broken down by age group, gender, zone, level of education and other. The SIMS contains information in 6 broad categories: population, employment, unemployment, income, social security and poverty. This database seeks to contribute to public policies design based on evidence to strengthen the development of the region.


Click here to access the data: https://mydata.iadb.org/d/v2c9-36h7

Social Accounting Matrix (SAM) for Paraguay for the year 2009 with 37 activities and 51 products.


Click here to access the data: https://mydata.iadb.org/Economics/Social-Accounting-Matrix-SAM-for-Paraguay-2009/8gbp-twbk

Social Indicator is a diverse dataset of indicators designed to capture social conditions in Latin America and the Caribbean. The indicators are derived from national household survey data, Censuses, and other sources covering 21 countries from 1990 to date. While the Sociómetro includes traditional global indicators, the database also includes tailor-made indicators in five areas: Demographics, Education, Labor Market, Housing, and Income, to better capture conditions in LAC.

Moreover, unlike traditional aggregate indicators, the Sociómetro indicators are disaggregated by ethnicity and race (when available) and by gender, geographic residence, education, and income quintile.

The management and implementation of the Sociómetro are provided by the Social Sector (SCL) of the Vice Presidency of Knowledge and Sectors to strengthen the analytical content of projects and studies. The indicators are not intended to serve as official data for any particular country but instead aim to provide a comparable set of social indicators for the Latin American region.

Social Indicator is a diverse dataset of indicators designed to capture social conditions in Latin America and the Caribbean. The indicators are derived from national household survey data, Censuses, and other sources covering 21 countries from 1990 to date. While the Sociómetro includes traditional global indicators, the database also includes tailor-made indicators in five areas: Demographics, Education, Labor Market, Housing, and Income, to better capture conditions in LAC. In this particular dataset, we marked those indicators whose value we found to be out of normal expected range but whose value is justified and correctly measured.

Social Indicator is a diverse dataset of indicators designed to capture social conditions in Latin America and the Caribbean. The indicators are derived from national household survey data, Censuses, and other sources covering 21 countries from 1990 to date. While the Sociómetro includes traditional global indicators, the database also includes tailor-made indicators in five areas: Demographics, Education, Labor Market, Housing, and Income, to better capture conditions in LAC. In this particular dataset, we marked those indicators whose value we found to be out of normal expected range, this values maybe correctly measured and the deviation from the norm may be due to events occurring during the year. However, they are added to this list for them to be verified by a Technical Steward of the social sector.

The purpose of this dataset is to be a test dataset for creating new indicators or analyzing correction of legacy versions.

Social Indicator is a diverse dataset of indicators designed to capture social conditions in Latin America and the Caribbean. The indicators are derived from national household survey data, Censuses, and other sources covering 21 countries from 1990 to date. While the Sociómetro includes traditional global indicators, the database also includes tailor-made indicators in five areas: Demographics, Education, Labor Market, Housing, and Income, to better capture conditions in LAC.

SPOON: Sustained Program for Improving Nutrition, aims to implement and evaluate the effectiveness of a comprehensive strategy to prevent chronic malnutrition and to reduce the risks of future obesity in children from 0 to 24 months of age living in high-poverty. The program was implemented between 2014 and 2021 in Guatemala, including the evaluation. This dataset includes data from surveys conducted for this program containing two rounds of data, the baseline (2018) and the final evaluation of the program (2021) conducted in 76 communities in the department of Baja-Verapaz, Guatemala to a sample of 1628 households with children under 4.5 months and mothers who were in the third trimester of pregnancy at the time of the baseline. The survey includes a broad set of socioeconomic, demographic and nutritional variables. The data sets were anonymized to protect the privacy of the subjects. The variable names, their labels, and any steps taken for de-identification purposes are indicated in the codebook below.

This database compiles up-to-date standardized statistics on sovereign debt issuances for the LAC region and contains bi-annual data starting in 2006 through to 2021. Sovereign Debt Data is classified by legislation, creditor, currency and maturity amongst others for 26 countries. The availability of valid, comparable, and standardized public debt data is essential for the implementation of sound policies in Latin America and the Caribbean (LAC). This is why at the core of the LAC Debt Group initiative is the development of a standardized sovereign debt database to help debt managers, policy makers, and other actors of financial markets analyze the evolution and composition of public debt in LAC and conduct cross-country comparisons. The information of this database is provided by the public debt offices of LAC countries in response to a questionnaire specifically designed to allow comparability of data. The questionnaire, whose response is non-compulsory, is intended to compile up-to-date standardized statistics for objective and homogeneous definitions of public debt.

Click here to access the data: https://mydata.iadb.org/idb/dataset/3bvi-edbq

The database allows estimating structural fiscal balances for 20 countries in the region under different assumptions regarding the output gap and commodity structural prices. It is a unique database of its kind since: 1) It takes into consideration the distinct responsiveness of different types of revenues to changes in the output gap: In order to adjust for the impact of the business cycle on revenues, we calculate individual elasticities for each source of revenue (i.e. direct taxes, indirect taxes, revenues from non-renewable resources, etc.). Since the different types of revenues in the region have different sensitivities to changes in the output gap, this disaggregated approach allows for a more fine-tuned adjustment. 2) It includes estimations of SFBs based on output gaps’ projections available in “real time”. In addition to giving estimations of the actual SFBs, we provide with estimations of the SFBs that would have resulted should the projections on output gaps available to policymakers at the time of designing fiscal policy (data in “real time”) have been correct. This is in contrast to much of the existing work on structural fiscal balances that makes only an “ex post” analysis using actual and revised information on the output gaps. 3) It allows assessing the response of fiscal policy to the business cycle. We provide with measures of the fiscal impulse, assessing not only the actual but also the intentional fiscal stance, as well as the degree of procyclicality of fiscal policy.

Click here to access the data: https://mydata.iadb.org/idb/dataset/3itg-avtz

The database allows estimating structural fiscal balances for 20 countries in the region under different assumptions regarding the output gap and commodity structural prices. It is a unique database of its kind since: 1) It takes into consideration the distinct responsiveness of different types of revenues to changes in the output gap: In order to adjust for the impact of the business cycle on revenues, we calculate individual elasticities for each source of revenue (i.e. direct taxes, indirect taxes, revenues from non-renewable resources, etc.). Since the different types of revenues in the region have different sensitivities to changes in the output gap, this disaggregated approach allows for a more fine-tuned adjustment. 2) It includes estimations of SFBs based on output gaps’ projections available in “real time”. In addition to giving estimations of the actual SFBs, we provide with estimations of the SFBs that would have resulted should the projections on output gaps available to policymakers at the time of designing fiscal policy (data in “real time”) have been correct. This is in contrast to much of the existing work on structural fiscal balances that makes only an “ex post” analysis using actual and revised information on the output gaps. 3) It allows assessing the response of fiscal policy to the business cycle. We provide with measures of the fiscal impulse, assessing not only the actual but also the intentional fiscal stance, as well as the degree of procyclicality of fiscal policy.

Click here to access the data: https://mydata.iadb.org/idb/dataset/3itg-avtz