Effect of the expansion of social protection programs in Costa Rica:

A microsimulation analysis

Abstract

The article aims to identify social programs, as well as to estimate the optimal coverage range and cost, that could significantly reduce the observed levels of poverty in Costa Rica, particularly extreme poverty. This is carried out with the aid of static economic microsimulation models, which quantify changes in observed poverty levels based on modifications to existing public social interventions in the country. For this purpose, microdata from the 2022 National Household Survey, which are publicly available, are used as the source. The survey contains anonymized real-person data, allowing for the selection of subjects with and without intervention. As a result, it is highlighted that the expansion of the coverage of the Atención a Familias program would have the greatest impact on reducing extreme poverty, as well as the least fiscal cost. Furthermore, the results underline the importance of precise targeting in the implementation of social policies. Policies that specifically target households in extreme poverty or without access to state transfers can offer a more directed and sustainable approach to poverty reduction. This strategy can be particularly relevant in contexts where resources are limited and the need for efficiency in spending is high.