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Simple and Bias-Corrected Matching Estimators for Average
Treatment Effects

57 Pages Posted: 14 Jan 2003  

Alberto Abadie

Harvard University - Harvard Kennedy School (HKS); National Bureau of Economic Research (NBER)

Guido W. Imbens

Stanford Graduate School of Business

Date Written: August 2002

Abstract

Matching estimators for average treatment effects are widely used in evaluation research despite the fact that their large sample properties have not been established in many cases. In this article, we develop a new framework to analyze the properties of matching estimators and establish a number of new results. First, we show that matching estimators include a conditional bias term which may not vanish fast enough for the estimators to be root-N-consistent. Second, we show that even after removing the conditional bias, matching estimators with a fixed number of matches are mnot efficient, although the efficiency loss may be small. Third, we propose a bias-correction that removes the conditional bias asymptotically, making matching estimators root-N-consistent. Fourth, we provide a new estimator for the conditional variance that does not require consistent nonparametric estimation of unknown functions. We carry out a small simulation study based where a simple implementation of the bias-corrected matching estimator performs well compared to both simple matching estimators and to regression estimators in terms of bias and root-mean-squared-error. Software for implementing the proposed estimators in STATA and Matlab is available from the authors on the web.

Keywords: matching, average treatment effect, program evaluation, selection-on-observables

JEL Classification: C14, C20

Suggested Citation

Abadie, Alberto and Imbens, Guido W., Simple and Bias-Corrected Matching Estimators for Average Treatment Effects (August 2002). Available at SSRN: https://ssrn.com/abstract=341300 or http://dx.doi.org/10.2139/ssrn.341300

Alberto Abadie

Harvard University - Harvard Kennedy School (HKS) ( email )

79 John F. Kennedy Street
Cambridge, MA 02138
United States
617-496-4547 (Phone)
617-495-2575 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Guido W. Imbens (Contact Author)

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States

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