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Small area estimation of poverty under structural change

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  • Lange,Simon
  • Pape,Utz Johann
  • Putz,Peter

Abstract

Small area poverty maps allow for the design of policies based on spatial differences in welfare. They are typically estimated based on a consumption survey reporting on poverty and a census providing the spatial disaggregation. This paper presents a new method which allows for the estimation of up-to-date small area poverty maps when only a dated census and a more recent survey are available and predictors and structural parameters are subject to drift over time, a situation commonly encountered in practice. Instead of using survey variables to explain consumption in the survey, the new approach uses variables constructed from the census. The proposed estimator has fewer data requirements and weaker assumptions than common small area poverty map estimators. Applications to simulated data and to poverty estimation in Brazil show an overall good performance.

Suggested Citation

  • Lange,Simon & Pape,Utz Johann & Putz,Peter, 2018. "Small area estimation of poverty under structural change," Policy Research Working Paper Series 8472, The World Bank.
    • Handle: RePEc:wbk:wbrwps:8472
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    Cited by:

    1. Becerra Luna,Laura Natalia & Lebrand,Mathilde Sylvie Maria & Pkhikidze,Nino & Yi Chang,Andres, 2022. "Infrastructure Matters : Complementarities with the Quality of Health ServiceDelivery in Kenya," Policy Research Working Paper Series 10220, The World Bank.
    2. Newhouse David, 2020. "Discussion of “Small area estimation: its evolution in five decades”, by Malay Ghosh," Statistics in Transition New Series, Polish Statistical Association, vol. 21(4), pages 45-50, August.
    3. Masaki,Takaaki & Newhouse,David Locke & Silwal,Ani Rudra & Bedada,Adane & Engstrom,Ryan, 2020. "Small Area Estimation of Non-Monetary Poverty with Geospatial Data," Policy Research Working Paper Series 9383, The World Bank.
    4. Simon Lange & Utz Johann Pape & Peter Pütz, 2022. "Small Area Estimation of Poverty Under Structural Change," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(S2), pages 264-281, December.
    5. Corral, Paul & Henderson, Heath & Segovia, Sandra, 2025. "Poverty mapping in the age of machine learning," Journal of Development Economics, Elsevier, vol. 172(C).
    6. Corral Rodas,Paul Andres & Kastelic,Kristen Himelein & Mcgee,Kevin Robert & Molina,Isabel, 2021. "A Map of the Poor or a Poor Map ?," Policy Research Working Paper Series 9620, The World Bank.
    7. Paul Corral & Kristen Himelein & Kevin McGee & Isabel Molina, 2021. "A Map of the Poor or a Poor Map?," Mathematics, MDPI, vol. 9(21), pages 1-40, November.
    8. Newhouse,David Locke, 2023. "Small Area Estimation of Poverty and Wealth Using Geospatial Data : What Have We Learned SoFar ?," Policy Research Working Paper Series 10512, The World Bank.

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