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How Best to Target the Poor? An operational targeting of the poor using indicator-based proxy means tests

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  • Houssou, Nazaire
  • Zeller, Manfred
  • Alcaraz V., Gabriela
  • Johannsen, Julia
  • Schwarze, Stefan

Abstract

This paper seeks to answer an operational development question: how best to target the poor? In their endeavor, policy makers, program managers, and development practitioners face the daily challenge of targeting policies, projects, and services at the poorer strata of the population. This is also the case for microfinance institutions that seek to estimate the poverty outreach among their clients. This paper addresses these challenges. Using household survey data from Uganda, we estimate four alternative models for improving the identification of the poor in the country. Furthermore, we analyze the model sensitivity to different poverty lines and test their validity using bootstrapped simulation methods. While there is bound to be some errors, no indicator being perfectly correlated with poverty, the models developed achieve fairly accurate out-of-sample predictions of absolute poverty. Furthermore, findings suggest that the estimation method is not relevant for developing a fairly accurate model for targeting the poor. The models developed are potentially useful tools for the development community in Uganda. This research can also be applied in other developing countries.

Suggested Citation

  • Houssou, Nazaire & Zeller, Manfred & Alcaraz V., Gabriela & Johannsen, Julia & Schwarze, Stefan, 2010. "How Best to Target the Poor? An operational targeting of the poor using indicator-based proxy means tests," 2010 AAAE Third Conference/AEASA 48th Conference, September 19-23, 2010, Cape Town, South Africa 95780, African Association of Agricultural Economists (AAAE).
  • Handle: RePEc:ags:aaae10:95780
    DOI: 10.22004/ag.econ.95780
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    References listed on IDEAS

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    1. Omar Arias & Walter Sosa-Escudero & Kevin F. Hallock, 2001. "Individual heterogeneity in the returns to schooling: instrumental variables quantile regression using twins data," Empirical Economics, Springer, vol. 26(1), pages 7-40.
    2. Kappel, Robert & Lay, Jann & Steiner, Susan, 2005. "Uganda: No more pro-poor growth?," Proceedings of the German Development Economics Conference, Kiel 2005 31, Verein für Socialpolitik, Research Committee Development Economics.
    3. N. S. Ssewanyana & A J. Okidi & D. Angemi & V. Barungi, 2004. "Understanding the determinants of income inequality in Uganda," CSAE Working Paper Series 2004-29, Centre for the Study of African Economies, University of Oxford.
    4. Yannis Bilias & Roger Koenker, 2001. "Quantile regression for duration data: A reappraisal of the Pennsylvania Reemployment Bonus Experiments," Empirical Economics, Springer, vol. 26(1), pages 199-220.
    5. Grosh, M.E. & Baker, J.L., 1995. "Proxy Means Tests for Targetting Social Programs. Simulations and Speculation," Papers 118, World Bank - Living Standards Measurement.
    6. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    7. Diego Angemi & N.S. Ssewanyana, 2004. "Understanding the Determinants of Income Inequality in Uganda," Economics Series Working Papers WPS/2004-29, University of Oxford, Department of Economics.
    8. David P. Coady & Susan W. Parker, 2009. "Targeting Performance under Self-selection and Administrative Targeting Methods," Economic Development and Cultural Change, University of Chicago Press, vol. 57(3), pages 559-587, April.
    9. Ahmed, Akhter U. & Bouis, Howarth E., 2002. "Weighing what's practical: proxy means tests for targeting food subsidies in Egypt," Food Policy, Elsevier, vol. 27(5-6), pages 519-540.
    10. Zeller, Manfred & Sharma, Manohar & Henry, Carla & Lapenu, Cecile, 2006. "An operational method for assessing the poverty outreach performance of development policies and projects: Results of case studies in Africa, Asia, and Latin America," World Development, Elsevier, vol. 34(3), pages 446-464, March.
    11. repec:zbw:ifwkie:3715 is not listed on IDEAS
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    Cited by:

    1. Nguyen, Cuong & Lo, Duc, 2016. "Testing Proxy Means Tests in the Field: Evidence from Vietnam," MPRA Paper 80002, University Library of Munich, Germany.
    2. Cuong Viet Nguyen & Anh Tran, 2014. "Poverty identification: practice and policy implications in Vietnam," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 28(1), pages 116-136, May.

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    Keywords

    Food Security and Poverty;

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