Estimating poverty rates in target populations: an assessment of the simple poverty scorecard and alternative approaches

Alexis Diamond, Michael Gill, Miguel Angel Rebolledo Dellepiane, Emmanuel Skoufias, Katja Vinha and Yiqing Xu

No 7793, Policy Research Working Paper Series from The World Bank

Abstract: The performance of the Simple Poverty Scorecard is compared against the performance of established regression-based estimators. All estimates are benchmarked against observed poverty status based on household expenditure (or income) data from household socioeconomic surveys that span nearly a decade and are representative of subnational populations. When the models all adopt the same"one-size-fits-all"training approach, there is no meaningful difference in performance and the Simple Poverty Scorecard is as good as any of the regression-based estimators. The findings change, however, when the regression-based estimators are"trained"on"training sets"that more closely resemble potential subpopulation test sets. In this case, regression-based models outperform the nationally calculated Simple Poverty Scorecard in terms of bias and variance. These findings highlight the fundamental trade-off between simplicity of use and accuracy.

Keywords: Inequality (search for similar items in EconPapers)
Date: 2016-08-15
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Citations: View citations in EconPapers (5)

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