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Poverty Mapping: Innovative Approaches to Creating Poverty Maps with New Data Sources

Conclusions and Suggestions

This paper explores both traditional and novel methods that can be used to derive geographically disaggregated poverty estimates and poverty maps. Granular and up-to-date poverty data are critical for responding to questions regarding the relevance and effectiveness of policy interventions in the context of evaluation. The approaches outlined above provide a brief overview of some of the data and methodological alternatives that can be used to generate cost-efficient poverty maps.

Many of these methodological options can be derived using publicly available data and existing resources at a relatively low cost. This is an important consideration given that traditional in-the-field poverty data collection for a country or an area of interest is expensive and time-consuming.

Finally, this paper also introduces some readily available resources in the form of data sets that can be directly used to plot detailed poverty maps (such as the wealth index jointly developed by Facebook and University of California, Berkeley) or code repositories that provide all the implementation details that are essential to replicate some of the methods described herein.