Using GIS for spatial autocorrelation in childhood vulnerability assessment: central American comparisons

Alejandra Silva, Centro Latinoamericano de Demografía (CELADE)
María Concepción Valdez, CELADE

In order to study the spatial relationships of child vulnerability at a sub-national level in Central America it is necessary to define and analyze “child poverty,” identifying appropriate indicators that best measure and characterize this phenomenon based on the availability of information. In this research the spatial distribution of infant poverty in Central America at a sub-national level (municipalities) is analyzed using the Unmet Basic Needs methodology based on the material deprivation approach (adapted from the Bristol Indicators) and secondly, an exploratory analysis is performed to detect local spatial autocorrelation and spatial clusters based on the poverty indicators. This will provide patterns for mapping analysis of these indicators and will help us to understand spatial autocorrelation. It is expected that the analysis of how these spatial patterns are related to socio-demographic characteristics will prove to be useful for decision makers and governments seeking to promote a more equitable development.