Abstract
This dataset provides a comprehensive view of Environmental, Social, and Economic (ESG) indicators for countries classified as lower-middle-income by the World Bank from 2000 to 2024. Environmental indicators include renewable electricity output (% of total electricity) and forest area (% of land area), reflecting progress toward sustainable energy use and natural resource conservation. Social indicators capture life expectancy at birth, adult literacy rates, and the ratio of female to male labor force participation, providing insights into human development, education, and gender equity. Economic indicators include GDP per capita (constant 2015 US$), poverty headcount ratio at $3.00 a day (2021 PPP), and unemployment rate, offering a quantitative measure of economic development and labor market conditions. The dataset is structured as a panel dataset with countries as rows and annual observations for each indicator, facilitating longitudinal and cross-country analysis. It is suitable for research, policy analysis, and ESG-related studies in emerging economies. By combining environmental, social, and economic dimensions, the dataset enables researchers and policymakers to assess sustainability trends, identify areas of improvement, and track progress toward development goals in lower-middle-income countries.
Supplementary weblinks
Title
ESG and Sustainability Indicators in Lower-Middle-Income Countries (2000–2024)
Description
This World Bank DataBank link provides access to a comprehensive dataset of Environmental, Social, and Economic (ESG) indicators for lower-middle-income countries from 2000 to 2024. The dataset includes renewable electricity output, forest area, life expectancy, adult literacy rate, female-to-male labor force participation, GDP per capita, poverty headcount ratio, and unemployment rates. It enables longitudinal and cross-country analysis of sustainability, socio-economic development, and progress toward sustainable development goals (SDGs) in emerging economies. The data is structured for easy extraction, analysis, and visualization, making it suitable for research, policy evaluation, and ESG-focused studies.
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