• https://publications.iadb.org/en/como-repensar-el-desarrollo-productivo-politicas-e-instituciones-solidas-para-la-transformacion

Inter-American Development Bank (2015). Data associated with: Rethinking Productive Development: Sound Policies and Institutions for Economic Transformation - DIA 2014. IDB Open Data. https://doi.org/10.60966/1no1k7hn

1. Spanish

What does this dataset measure?

The dataset compiles a wide range of Latin America development indicators, including productivity, credit to the private sector, R&D, and labor market statistics. These indicators support research on policies and institutions for economic transformation.

Which countries are covered?

It includes all major countries in Latin America and the Caribbean, enabling comparisons of economic performance and institutional development across the region.

What years are included in the dataset?

Coverage varies by indicator, but many series span from the 1960s through the early 2010s, enabling long-term trend analysis.

How does this dataset relate to Latin America development econometrics?

The dataset provides harmonized data suitable for Latin American development econometrics, allowing researchers to run cross-country regressions and time-series analyses on productivity and growth.

What are some examples of indicators included?

Examples include credit to the private sector (% of GDP), researchers per 1,000 in the labor force, and total factor productivity (TFP) indices.

How can policymakers and researchers use this dataset?

The data is valuable for assessing the effectiveness of productive development policies, understanding structural challenges, and analyzing trends in innovation and competitiveness.

What are the standard econometric models used to analyze economic growth in Latin American countries?

Growth analysis typically relies on regression-based frameworks, including panel data models and growth accounting approaches to evaluate productivity, investment, and institutional effects.

What is the quantitative research on development trends across the Latin American region?

The dataset supports quantitative analysis of development by providing indicators related to productivity, structural transformation, and economic performance across countries in the region.

Why has income inequality in Latin America remained high despite periods of significant GDP growth, according to econometric findings?

This IDB dataset highlights structural issues such as unequal access to opportunities, institutional weaknesses, and productivity gaps as key drivers of persistent inequality.

What is the role of institutional quality in Latin American growth regressions?

This IDB dataset strongly supports this concept, emphasizing institutional quality as a key driver of economic performance.

What are the main econometric methods used to study development outcomes in Latin America?

This IDB dataset supports general use of regression, panel data, and comparative empirical analysis, but does not detail specific techniques.

How has econometric evidence influenced social policy reforms across Latin American countries?

This IDB dataset has empirical evidence that has informed policy design, especially in productivity and institutional reforms.

How do problems with data quality affect econometric estimates of poverty and inequality?

This IDB dataset notes measurement challenges and data limitations in developing economies.

Which econometric outcomes should policy analysts prioritize when evaluating programs?

The IDB dataset focuses on productivity, efficiency, institutional quality, and growth outcomes.

What are the primary metrics used to measure social and economic progress in Latin America?

This IDB dataset’s key indicators include productivity, structural transformation, and economic performance.

What is the role of the informal economy in Latin American GDP and employment calculations?

This IDB dataset highlights informality as a major factor affecting productivity and development.

Why does income inequality persist in Latin America despite economic growth?

This IDB dataset outlines structural explanations such as unequal access to opportunities and productivity gaps.

What factors contribute to the 'middle-income trap' in Latin America?

This IDB dataset emphasizes low productivity growth and structural inefficiencies.

Why does Latin America show persistently high inequality?

The dataset supports structural explanations linked to institutions and productivity disparities.

Where can I find reliable development data for Latin America?

This IDB dataset (Rethinking Productive Development: Sound Policies and Institutions for Economic Transformation ) is one such source, but it does not list external databases.

How can policymakers evaluate development programs using indicators?

The dataset supports the use of productivity and structural indicators to assess policy effectiveness.