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The Welfare Returns to Finer Targeting: The Case of The Progresa Program in Mexico

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  • David Coady

Abstract

It is common in developing countries to attempt finer targeting of the benefits from social safety net programs through combining different targeting methods. We evaluate the returns to finer targeting in the context of the PROGRESA program in Mexico. This program is a prominent program in the literature reflecting the fact that it has been widely evaluated, is perceived to be well targeted, and has been used as a prototype for many other programs in the region and beyond. We also identify the relative incremental contribution of each targeting method to the overall targeting performance of the program. We find that geographic targeting dominates demographic targeting (based on linking transfer levels to demographic composition), which in turn dominates household proxy-means targeting. However, the contribution of proxy-means targeting increases substantially as the program expands into less marginal localities. Adjusting for incomplete take-up increases the targeting performance of the program only slightly. Copyright Springer Science + Business Media, Inc. 2006

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  • David Coady, 2006. "The Welfare Returns to Finer Targeting: The Case of The Progresa Program in Mexico," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 13(2), pages 217-239, May.
  • Handle: RePEc:kap:itaxpf:v:13:y:2006:i:2:p:217-239
    DOI: 10.1007/s10797-006-4824-2
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    3. Mark Schreiner, 2015. "A Comparison of Two Simple, Low-Cost Ways for Local, Pro-Poor Organizations to Measure the Poverty of Their Participants," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 124(2), pages 537-569, November.
    4. Chikako Yamauchi, 2010. "Community-Based Targeting and Initial Local Conditions: Evidence from Indonesia's IDT Program," Economic Development and Cultural Change, University of Chicago Press, vol. 59(1), pages 95-147, October.
    5. Viviane Azevedo & Marcos Robles, 2013. "Multidimensional Targeting: Identifying Beneficiaries of Conditional Cash Transfer Programs," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 112(2), pages 447-475, June.
    6. Blumenstock, Joshua & Aiken, Emily & Bellue, Suzanne & Udry, Christopher & Karlan, Dean, 2021. "Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance," CEPR Discussion Papers 16385, C.E.P.R. Discussion Papers.
    7. Mr. David Coady & Susan Parker, 2009. "Targeting Social Transfers to the Poor in Mexico," IMF Working Papers 2009/060, International Monetary Fund.
    8. Lang, Corey & Barrett, Christopher B. & Naschold, Felix, 2013. "Targeting Maps: An Asset-Based Approach to Geographic Targeting," World Development, Elsevier, vol. 41(C), pages 232-244.
    9. Garcia-Diaz, Rocio & Sosa-Rub, Sandra G., 2011. "Analysis of the distributional impact of out-of-pocket health payments: Evidence from a public health insurance program for the poor in Mexico," Journal of Health Economics, Elsevier, vol. 30(4), pages 707-718, July.
    10. Yörük, Erdem & Öker, İbrahim & Şarlak, Lara, 2019. "Indigenous unrest and the contentious politics of social assistance in Mexico," World Development, Elsevier, vol. 123(C), pages 1-1.
    11. Bjorkegren, Dan & Blumenstock, Joshua & Knight, Samsun, 2022. "(Machine) Learning What Policies Value," CEPR Discussion Papers 17364, C.E.P.R. Discussion Papers.
    12. Guanghua Chi & Han Fang & Sourav Chatterjee & Joshua E. Blumenstock, 2022. "Microestimates of wealth for all low- and middle-income countries," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(3), pages 2113658119-, January.
    13. 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.

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