Poverty Mapping in El Salvador

Poverty mapping, the spatial representation and analysis of human wellbeing and poverty indicators is becoming an increasingly important instrument for investigating and discussing socioeconomic issues, informing targeting efforts, and guiding the geographic allocation of resources. One approach to...

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Bibliographic Details
Main Author: Robayo-Abril, Monica
Other Authors: Rude, Britta
Format: eBook
Language:English
Published: Washington, D.C The World Bank 2023
Series:Other Poverty Study
Subjects:
Online Access:
Collection: World Bank E-Library Archive - Collection details see MPG.ReNa
Description
Summary:Poverty mapping, the spatial representation and analysis of human wellbeing and poverty indicators is becoming an increasingly important instrument for investigating and discussing socioeconomic issues, informing targeting efforts, and guiding the geographic allocation of resources. One approach to addressing poverty is the geographic approach. In the geographic approach, poor people are identified and targeted through poverty maps. Indeed, the geographical approach is one of the methods used worldwide for targeting anti-poverty programs to reduce the gaps in social protection coverage of poor and vulnerable groups, and it has been widely implemented in several countries around the world. In 2020, the Salvador's General Directorate of Statistics and Censuses (DIGESTYC) and the World Bank started working on the project 'Poverty mapping in El Salvadora'. The project is part of the government and International Bank for Reconstruction and Development (IBRD) Programme, which is performed by experts of the National Statistical Institute (NSI) and the World Bank (WB). The main objective is to calculate the shares of households living in moderate and extreme poverty at disaggregated territorial levels (municipalities). Poverty mapping enhances our understanding of the geographic distribution of people living in poverty. This report presents poverty maps at the municipality level based on the Fay-Herriot model for small-area estimations