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Optimal Cash Transfers with Distribution Regressions: An Application to Egypt at the Dawn of the XXIst Century

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Abstract

Social programmes for poverty alleviation involve eligibility rules and transfer rules that often proxy-means tests. We propose to specify the estimator in connection with the poverty alleviation problem. Three distinct stages emerge from the optimization analysis: the identification of the poor, the ranking of their priorities and the calculus of the optimal transfer amount. These stages are implemented simultaneous by using diverse distribution regression methods to generate fitted-values of living standards plugged into the poverty minimization programme to obtain the transfer amounts. We apply these methods to Egypt in 2013. Recentered Influence Function (RIF) regressions focusing on the poor correspond to the most efficient transfer scheme. Most of the efficiency gain is obtained by making transfer amounts varying across beneficiaries rather than by varying estimation methods. Using RIF regressions instead of quantile regressions delivers only marginal poverty alleviation, although it allows for substantial reduction of the exclusion of the poor.

Suggested Citation

  • Christophe Muller, 2018. "Optimal Cash Transfers with Distribution Regressions: An Application to Egypt at the Dawn of the XXIst Century," AMSE Working Papers 1802, Aix-Marseille School of Economics, France.
  • Handle: RePEc:aim:wpaimx:1802
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    Cited by:

    1. Msangi, Haji Athumani & Löhr, Katharina & Sieber, Stefan & Waized, Betty & Ndyetabula, Daniel Wilson, 2023. "Maximizing impact: The power of combining land tenure formalization and productive social safety nets programmes in Tanzania," 2023 Seventh AAAE/60th AEASA Conference, September 18-21, 2023, Durban, South Africa 365859, African Association of Agricultural Economists (AAAE).
    2. Msangi, Haji Athumani & Ndyetabula, Daniel Wilson & Waized, Betty, 2024. "Maximizing impact: The power of combining land tenure formalization and productive social safety nets programmes in Tanzania," Land Use Policy, Elsevier, vol. 138(C).

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    Keywords

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    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

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