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Must conditional cash transfer programs be conditioned to be effective?: The impact of conditioning transfers on school enrollment in Mexico

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  • de Brauw, Alan
  • Hoddinott, John

Abstract

"A growing body of evidence suggests that conditional cash transfer (CCT) programs can have strong, positive effects on a range of welfare indicators for poor households in developing countries. However, the contribution of individual program components toward achieving these outcomes is not well understood. This paper contributes to filling this gap by explicitly testing the importance of conditionality on one specific outcome related to human capital formation (namely school enrollment), using data collected during the evaluation of Mexico's Programa de Educación, Salud, y Alimentación (PROGRESA) CCT program. We exploit the fact that some PROGRESA beneficiaries who received transfers did not receive the forms needed to monitor their children's attendance at school. We use a variety of techniques, including nearest neighbor matching and household fixed effects regressions, to show that the lack of these forms reduced the likelihood of children attending school, with this effect being most pronounced among children who were transitioning to lower secondary school. We provide substantial evidence that these findings are not driven by unobservable characteristics related to households or localities." from Author's Abstract

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Bibliographic Info

Paper provided by International Food Policy Research Institute (IFPRI) in its series IFPRI discussion papers with number 757.

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Date of creation: 2008
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Handle: RePEc:fpr:ifprid:757

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Keywords: Conditionality; Cash transfers; School enrollment; School attendance; Progresa; Social protection; Education;

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  1. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
  2. John Maluccio & Natàlia Caldés & David Coady, 2005. "The Cost of Poverty Alleviation Transfer Programs: A Comparative Analysis of Three Programs in Latin America," Middlebury College Working Paper Series 0527, Middlebury College, Department of Economics.
  3. 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.
  4. Markus Frölich, 2004. "Finite-Sample Properties of Propensity-Score Matching and Weighting Estimators," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 77-90, February.
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  6. Gary Burtless, 1995. "The Case for Randomized Field Trials in Economic and Policy Research," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 63-84, Spring.
  7. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2000. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," NBER Working Papers 7831, National Bureau of Economic Research, Inc.
  8. Hotz, V. Joseph & Crump, Richard K. & Mitnik, Oscar A. & Imbens, Guido, 2009. "Dealing with Limited Overlap in Estimation of Average Treatment Effects," Scholarly Articles 3007645, Harvard University Department of Economics.
  9. Behrman, Jere R & Sengupta, Piyali & Todd, Petra, 2005. "Progressing through PROGRESA: An Impact Assessment of a School Subsidy Experiment in Rural Mexico," Economic Development and Cultural Change, University of Chicago Press, vol. 54(1), pages 237-75, October.
  10. Heckman, James J & Ichimura, Hidehiko & Todd, Petra E, 1997. "Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Wiley Blackwell, vol. 64(4), pages 605-54, October.
  11. Petra E. Todd & Jeffrey A. Smith, 2001. "Reconciling Conflicting Evidence on the Performance of Propensity-Score Matching Methods," American Economic Review, American Economic Association, vol. 91(2), pages 112-118, May.
  12. Laibson, David I., 1997. "Golden Eggs and Hyperbolic Discounting," Scholarly Articles 4481499, Harvard University Department of Economics.
  13. Edward C. Norton & Hua Wang & Chunrong Ai, 2004. "Computing interaction effects and standard errors in logit and probit models," Stata Journal, StataCorp LP, vol. 4(2), pages 154-167, June.
  14. Hoddinott, John & Skoufias, Emmanual, 2003. "The impact of Progresa on food consumption," FCND discussion papers 150, International Food Policy Research Institute (IFPRI).
  15. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
  16. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
  17. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in the Estimation of Average Treatment Effects by Changing the Estimand," NBER Technical Working Papers 0330, National Bureau of Economic Research, Inc.
  18. Alain de Janvry & Elisabeth Sadoulet, 2006. "Making Conditional Cash Transfer Programs More Efficient: Designing for Maximum Effect of the Conditionality," World Bank Economic Review, World Bank Group, vol. 20(1), pages 1-29.
  19. Maluccio, John A. & Flores, Rafael, 2005. "Impact evaluation of a conditional cash transfer program: the Nicaraguan Red de Protección Social," Research reports 141, International Food Policy Research Institute (IFPRI).
  20. Schady, Norbert & Araujo, Maria Caridad, 2006. "Cash transfers, conditions, school enrollment, and child work : evidence from a randomized experiment in Ecuador," Policy Research Working Paper Series 3930, The World Bank.
  21. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, 01.
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