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

Author

Listed:
  • Diamond,Alexis
  • Gill,Michael
  • Rebolledo Dellepiane,Miguel Angel
  • Skoufias,Emmanuel
  • Vinha,Katja
  • Xu,Yiqing
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.

Suggested Citation

  • Diamond,Alexis & Gill,Michael & Rebolledo Dellepiane,Miguel Angel & Skoufias,Emmanuel & Vinha,Katja & Xu,Yiqing, 2016. "Estimating poverty rates in target populations : an assessment of the simple poverty scorecard and alternative approaches," Policy Research Working Paper Series 7793, The World Bank.
    • Handle: RePEc:wbk:wbrwps:7793
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    Citations

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    Cited by:

    1. Brown, Caitlin & Ravallion, Martin & van de Walle, Dominique, 2018. "A poor means test? Econometric targeting in Africa," Journal of Development Economics, Elsevier, vol. 134(C), pages 109-124.
    2. Dang,Hai-Anh H., 2018. "To impute or not to impute ? a review of alternative poverty estimation methods in the context of unavailable consumption data," Policy Research Working Paper Series 8403, The World Bank.
    3. Catherine Porter & Emily White, 2017. "The Development of Vulnerability Functions Relating Household Poverty Outcomes to Crop Failures in Ethiopia with the Prospect of Developing a Probabilistic Catastrophe Risk Model," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 42(4), pages 657-674, October.
    4. Hai‐Anh H. Dang, 2021. "To impute or not to impute, and how? A review of poverty‐estimation methods in the absence of consumption data," Development Policy Review, Overseas Development Institute, vol. 39(6), pages 1008-1030, November.

    More about this item

    Keywords

    Inequality;

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