Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?

49 Pages Posted: 10 Oct 2001

See all articles by Jeffrey A. Smith

Jeffrey A. Smith

University of Wisconsin - Madison; National Bureau of Economic Research (NBER); Institute for the Study of Labor (IZA)

Petra Todd

University of Pennsylvania - Department of Economics; National Bureau of Economic Research (NBER); IZA Institute of Labor Economics

Date Written: November 2000

Abstract

This paper applies recently developed cross-sectional and longitudinal propensity score matching estimators to data from the National Supported Work Demonstration that have been previously analyzed by LaLonde (1986) and Dehejia and Wahba (1998,1999). We find little support for recent claims in the econometrics and statistics literatures that traditional, cross-sectional matching estimators generally provide a reliable method of evaluating social experiments (e.g. Dehejia and Wahba, 1998, 1999). Our results show that program impact estimates generated through propensity score matching are highly sensitive to choice of variables used in estimating the propensity scores and sensitive to the choice of analysis sample. Among the estimators we study, the difference-in-differences matching estimator is the most robust. We attribute its better performance to the fact that it eliminates temporarily - invariant sources of bias that may arise, for example, when program participants and nonparticipants are geographically mismatched or from differences in survey questionnaires, which are both common sources of biases in evaluation studies.

Suggested Citation

Smith, Jeffrey Andrew and Todd, Petra, Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators? (November 2000). Available at SSRN: https://ssrn.com/abstract=286297 or http://dx.doi.org/10.2139/ssrn.286297

Jeffrey Andrew Smith

University of Wisconsin - Madison ( email )

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Madison, WI 53706-1481
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National Bureau of Economic Research (NBER)

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Institute for the Study of Labor (IZA)

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Germany

Petra Todd (Contact Author)

University of Pennsylvania - Department of Economics ( email )

Ronald O. Perelman Center for Political Science
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Philadelphia, PA 19104-6297
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

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