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Finding the Best Indicators to Identify the Poor

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  • Adama Bah

    (CERDI - Centre d'Études et de Recherches sur le Développement International - UdA - Université d'Auvergne - Clermont-Ferrand I - CNRS - Centre National de la Recherche Scientifique)

Abstract

Proxy-means testing (PMT) is a method used to assess household or individual welfare level based on a set of observable indicators. The accuracy, and therefore usefulness of PMT relies on the selection of indicators that produce accurate predictions of household welfare. In this paper I propose a method to identify indicators that are robustly and strongly correlated with household welfare, measured by per capita consumption. From an initial set of 340 candidate variables drawn from the Indonesian Family Life Survey, I identify the variables that contribute most significantly to model predictive performance and that are therefore desirable to be included in a PMT formula. These variables span the categories of household private asset holdings, access to basic domestic energy, education level, sanitation and housing. A comparison of the predictive performance of PMT formulas including 10, 20 and 30 of the best predictors of welfare shows that leads to recommending formulas with 20 predictors. Such parsimonious models have similar predictive performance as the PMT formulas currently used in Indonesia, although these latter are based on models of 32 variables on average.

Suggested Citation

  • Adama Bah, 2015. "Finding the Best Indicators to Identify the Poor," CERDI Working papers halshs-00936201, HAL.
    • Handle: RePEc:hal:cdiwps:halshs-00936201
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00936201v2
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    References listed on IDEAS

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