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An Assessment of Propensity Score Matching as a Non Experimental Impact Estimator: Evidence from Mexico's PROGRESA Program

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  • Díaz, Juan José
  • Handa, Sudhanshu

Abstract

In this working paper the authors present evidence on the reliability of propensity score matching to estimate the bias associated with the effect of treatment on the treated, exploiting the availability of experimental data from a Mexican antipoverty program (PROGRESA: Programa de Educación, Salud y Alimentación). The data comes from several outcomes such as food expenditure and child schooling and labor. The methodology compares the results of the experimental impact estimator with those using matched samples drawn from a (non-experimental) national survey carried out to measure household income and expenditures. The results show that simple-cross sectional matching produces significant bias for outcomes measured in different ways. Results are more positive for outcomes measured similarly across survey instruments, but even in this case there are indications of bias depending on sample and matching method.

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  • Díaz, Juan José & Handa, Sudhanshu, 2005. "An Assessment of Propensity Score Matching as a Non Experimental Impact Estimator: Evidence from Mexico's PROGRESA Program," IDB Publications (Working Papers) 2999, Inter-American Development Bank.
  • Handle: RePEc:idb:brikps:2999
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    1. 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.
    2. Barbara Sianesi, 2004. "An Evaluation of the Swedish System of Active Labor Market Programs in the 1990s," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 133-155, February.
    3. Charles Michalopoulos & Howard S. Bloom & Carolyn J. Hill, 2004. "Can Propensity-Score Methods Match the Findings from a Random Assignment Evaluation of Mandatory Welfare-to-Work Programs?," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 156-179, February.
    4. 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.
    5. Roberto Agodini & Mark Dynarski, 2004. "Are Experiments the Only Option? A Look at Dropout Prevention Programs," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 180-194, February.
    6. David I. Levine & Gary Painter, 2003. "The Schooling Costs of Teenage Out-of-Wedlock Childbearing: Analysis with a Within-School Propensity-Score-Matching Estimator," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 884-900, November.
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