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Did PROGRESA send drop-outs back to school?

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  • Valdés, Nieves

Abstract

This paper analyzes the effect of PROGRESA education grants on school enrollment. It looks at its effect on total school enrollment and in particular on school enrollment of drop-outs, i.e. those children who face a re-enrollment decision since they were not enrolled in school the year prior to the implementation of the PROGRESA program. Estimates of the impact of PROGRESA education grants on drop-outs and non-drop-outs are obtained applying difference estimation and maximum likelihood estimation of a reduced form equation for schooling decision. Differences in results between both groups of children are discussed looking at the distribution of marginal effects. PROGRESA did send drop-outs back to school. It had a larger effect on drop-outs than on non-drop-outs. However, for the particular group of girls who dropped out of school just before attending secondary school PROGRESA grants only had a minor effect. This last finding highlights the fact that determinants of the schooling decision are different for young girls and that PROGRESA grants do not provide a strong enough incentive to send them back to school.

Suggested Citation

  • Valdés, Nieves, 2008. "Did PROGRESA send drop-outs back to school?," UC3M Working papers. Economics we085926, Universidad Carlos III de Madrid. Departamento de Economía.
  • Handle: RePEc:cte:werepe:we085926
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    1. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    2. Petra Todd & Kenneth I. Wolpin, 2002. "Using a Social Experiment to Validate a Dynamic Behavioral Model of Child Schooling and Fertility: Assessing the Impact of a School Subsidy Program in Mexico," PIER Working Paper Archive 03-022, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Sep 2003.
    3. Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 225-238.
    4. Charles F. Manski, 1996. "Learning about Treatment Effects from Experiments with Random Assignment of Treatments," Journal of Human Resources, University of Wisconsin Press, vol. 31(4), pages 709-733.
    5. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    6. Joshua D. Angrist, 1998. "Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants," Econometrica, Econometric Society, vol. 66(2), pages 249-288, March.
    7. Paul Schultz, T., 2004. "School subsidies for the poor: evaluating the Mexican Progresa poverty program," Journal of Development Economics, Elsevier, vol. 74(1), pages 199-250, June.
    8. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    9. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    10. Behrman, Jere R. & Deolalikar, Anil B., 1988. "Health and nutrition," Handbook of Development Economics, in: Hollis Chenery & T.N. Srinivasan (ed.), Handbook of Development Economics, edition 1, volume 1, chapter 14, pages 631-711, Elsevier.
    11. James Heckman, 1997. "Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations," Journal of Human Resources, University of Wisconsin Press, vol. 32(3), pages 441-462.
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    Cited by:

    1. Valdés, Nieves, 2009. "The school reentry decision on poor girls: structural estimation and policy analysis using PROGRESA database," UC3M Working papers. Economics we101406, Universidad Carlos III de Madrid. Departamento de Economía.

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    More about this item

    Keywords

    Anti-poverty program evaluation;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs

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