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Did PROGRESA send drop-outs back to school?

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  • Maria Nieves Valdes

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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.

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Bibliographic Info

Paper provided by Universidad Carlos III, Departamento de Economía in its series Economics Working Papers with number we085926.

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Date of creation: Jun 2008
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Handle: RePEc:cte:werepe:we085926

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Keywords: Anti-poverty program evaluation; School enrollment; Re-enrollment decision; Heterogeneous program effects; Correlated random effects model;

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  1. 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.
  2. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-75, March.
  3. 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.
  4. 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.
  5. 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.
  6. Heckman, James J & Ichimura, Hidehiko & Todd, Petra, 1998. "Matching as an Econometric Evaluation Estimator," Review of Economic Studies, Wiley Blackwell, vol. 65(2), pages 261-94, April.
  7. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
  8. Chamberlain, Gary, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 225-38, January.
  9. Joshua D. Angrist, 1995. "Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants," NBER Working Papers 5192, National Bureau of Economic Research, Inc.
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