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Matching as an Econometric Evaluation Estimator

James J. Heckman, Hidehiko Ichimura and Petra Todd
The Review of Economic Studies
Vol. 65, No. 2 (Apr., 1998), pp. 261-294
Published by: Oxford University Press
Stable URL: http://www.jstor.org/stable/2566973
Page Count: 34
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Matching as an Econometric Evaluation Estimator
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Abstract

This paper develops the method of matching as an econometric evaluation estimator. A rigorous distribution theory for kernel-based matching is presented. The method of matching is extended to more general conditions than the ones assumed in the statistical literature on the topic. We focus on the method of propensity score matching and show that it is not necessarily better, in the sense of reducing the variance of the resulting estimator, to use the propensity score method even if propensity score is known. We extend the statistical literature on the propensity score by considering the case when it is estimated both parametrically and nonparametrically. We examine the benefits of separability and exclusion restrictions in improving the efficiency of the estimator. Our methods also apply to the econometric selection bias estimator.

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