Where Are the Poor Located? A Spatial Heterogeneity Analysis of Monetary Poverty in Peru

Measuring poverty is a first step to the design of effective public policies, however, it is alsoessential to know where the poor are located. The main objective of this research is to evaluatethe spatial heterogeneity of the factors that influence monetary poverty for each district in Peru. We apply a Geographically Weighted Regression (GWR) approach, which allows us to capture thenon-stationarity of the hidden data and to provide coefficients for each district, unlike the OLSmodel. This research mainly uses the Poverty Map and the Population and Household Censusof Peru, both from 2007 and 2017. The overriding findings of our results indicate that femaleheadship, secondary education, electricity, and sanitation services are directly associated withpoverty reduction at the local level. For 2007, significant effects are mainly concentrated in thedistricts of Pasco, Lima and Cajamarca regions. For 2017, the results show a shift towards districtsof Junín, Huancavelica, and Cajamarca regions. Likewise, it is highlighted that the highest meannegative effect on poverty is generated by Secondary Education in the GWR estimates; whilemalnutrition represents the highest mean positive effect on poverty for the level and intercensalmodels. Finally, the empirical evidence found in this research can help establish better policydesigns at the district level.