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Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?

This paper applies cross-sectional and longitudinal propensity score matching estimators to data from the National Supported Work (NSW) Demonstration that have been previously analyzed by LaLonde (1986) and Dehejia and Wahba (1999, 2002). We find that estimates of the impact of NSW based on propensity score matching are highly sensitive to both the set of variables included in the scores and the particular analysis sample used in the estimation. Among the estimators we study, the difference-in-differences matching estimator performs the best. We attribute its performance to the fact that it eliminates potential sources of temporally-invariant bias present in the NSW data, such as geographic mismatch between participants and non-participants and the use of a dependent variable measured in different ways for the two groups. Our analysis demonstrates that while propensity score matching is a potentially useful econometric tool, it does not represent a general solution to the evaluation problem.

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Paper provided by University of Western Ontario, CIBC Centre for Human Capital and Productivity in its series University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers with number 20035.

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Date of creation: 2003
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Handle: RePEc:uwo:hcuwoc:20035
Contact details of provider: Postal: CIBC Centre for Human Capital and Productivity, Social Science Centre, University of Western Ontario, London, Ontario, Canada N6A 5C2
Phone: 519-661-2111 Ext.85244
Web page: http://economics.uwo.ca/research/research_papers/cibc_workingpapers.html

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  12. Heckman, James & Navarro-Lozano, Salvador, 2003. "Using matching, instrumental variables and control functions to estimate economic choice models," Working Paper Series 2003:4, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  13. 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.
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  22. 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.
  23. James J. Heckman, 1991. "Randomization and Social Policy Evaluation," NBER Technical Working Papers 0107, National Bureau of Economic Research, Inc.
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  31. Zhong Zhao, 2004. "Using Matching to Estimate Treatment Effects: Data Requirements, Matching Metrics, and Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 91-107, February.
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  33. 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.
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  37. Heckman, James J & Smith, Jeffrey A, 1999. "The Pre-programme Earnings Dip and the Determinants of Participation in a Social Programme. Implications for Simple Programme Evaluation Strategies," Economic Journal, Royal Economic Society, vol. 109(457), pages 313-48, July.
  38. Theresa J. Devine & James J. Heckman, 1996. "The Economics of Eligibility Rules for a Social Program: A Study of the Job Training Partnership Act (JTPA)--A Summary Report," Canadian Journal of Economics, Canadian Economics Association, vol. 29(s1), pages 99-104, April.
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