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Proxy Means Tests for Targeting the Poorest Households -- Applications to Uganda

Author

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

Abstract

The motivation for this research stems from increasing interest showed for the issue of targeting. The paper explores the use of proxy means tests to identify the poorest households in Uganda. The set of indicators used in our model includes variables usually available in Living Standard Measurement Surveys (LSMS). Previous researches seeking to develop proxy means tests for poverty most often use Ordinary Least Squares (OLS) as regression method. In addition to the OLS, the paper explores the use of Linear Probability Model, Probit, and Quantile regressions for correctly predicting the household poverty status. A further innovation of this research compared to the existing literature is the use of out-of sample validation tests to assess the predictive power and hence the robustness of the identified set of regressors. Moreover, the confidence intervals are approximated out-of sample using the bootstrap algorithm and the percentile method. The main conclusion that emerges from this research is that measures of absolute poverty estimated with Quantile regression can yield fairly accurate in-sample predictions of absolute poverty in a nationally representative sample. On the other hand, the OLS and Probit perform better out-of sample. Besides it complexity, the Quantile regression is less robust. The Probit may be the best alternative for optimizing both accuracy and robustness of a poverty assessment tool. The best regressor sets and their derived weights can be used in a range of applications, including the identification of the poorest households in the country, the assessment of poverty outreach of Microfinance Institutions (MFIs), and the measurement of poverty and welfare impacts of agricultural development projects. To confirm or reject the conclusions in this paper, future research using datasets from other countries is needed.

Suggested Citation

  • Houssou, Nazaire & Zeller, Manfred & Alcaraz V., Gabriela & Schwarze, Stefan & Johannsen, Julia, 2007. "Proxy Means Tests for Targeting the Poorest Households -- Applications to Uganda," 106th Seminar, October 25-27, 2007, Montpellier, France 7946, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaa106:7946
    DOI: 10.22004/ag.econ.7946
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    References listed on IDEAS

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    1. Julia Johannsen, 2006. "Operational Poverty Targeting In Peru – Proxy Means Testing With Non-Income Indicators," Working Papers 30, International Policy Centre for Inclusive Growth.
    2. Grosh, M.E. & Baker, J.L., 1995. "Proxy Means Tests for Targetting Social Programs. Simulations and Speculation," Papers 118, World Bank - Living Standards Measurement.
    3. Grootaert, Christiaan & Braithwaite, Jeanine, 1998. "Poverty correlates and indicator-based targeting in Eastern Europe and the Former Soviet Union," Policy Research Working Paper Series 1942, The World Bank.
    4. Ahmed, Akhter U. & Rashid, Shahidur & Sharma, Manohar & Zohir, Sajjad, 2004. "Food aid distribution in Bangladesh," FCND briefs 173, International Food Policy Research Institute (IFPRI).
    5. 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.
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    Cited by:

    1. Stefanía D’Iorio & Liliana Forzani & Rodrigo García Arancibia & Ignacio Girela, 2023. "Predictive Power of Composite Socioeconomic Indices in Regression and Classification: Principal Components and Partial Least Squares," Working Papers 246, Red Nacional de Investigadores en Economía (RedNIE).
    2. Tapanat Paiboonsin, 2019. "Targeting Poor Students With Proxy Means Test," International Journal of Business and Administrative Studies, Professor Dr. Bahaudin G. Mujtaba, vol. 5(3), pages 155-176.
    3. Dmytro Boyarchuk & Liudmyla Kotusenko & Katarzyna Pietka-Kosinska & Roman Semko & Irina Sinitsina, 2009. "Agriculture Income Assessment for the Purpose of Social Assistance: the Case of Ukraine," CASE Network Studies and Analyses 0399, CASE-Center for Social and Economic Research.
    4. Barrios, Erniel B. & Mina, Christian D., 2009. "Profiling Poverty with Multivariate Adaptive Regression Splines," Discussion Papers DP 2009-29, Philippine Institute for Development Studies.
    5. Mohamed Bakhshoodeh, 2013. "Proxy Means Tests for Targeting Subsidies Scheme in Iran," Working Papers 795, Economic Research Forum, revised Nov 2013.
    6. Delalić Adela & Abdić Ademir & Halilbašić Muamer & Šćeta Lamija, 2020. "Assesing efficiency of targeting in social services in Federation of Bosnia and Herzegovina," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 6(1), pages 56-74, May.

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