Abstract

This talk explores integrating diverse data sources—household surveys, censuses, and satellite imagery—to disaggregate SDG indicators in Latin America. By employing small area estimation models, it addresses data gaps and enhances the accuracy of regional and local SDG monitoring. This approach aims to provide more precise and actionable insights for policymakers, improving the implementation and tracking of sustainable development goals across varying spatial scales in the region.