Bandwidth Selection and the Estimation of Treatment Effects with Unbalanced Data

46 Pages Posted: 7 Nov 2007

See all articles by José Galdo

José Galdo

Syracuse University - Department of Economics; IZA Bonn

Jeffrey A. Smith

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

Dan Black

University of Chicago - Harris School of Public Policy

Date Written: October 2007

Abstract

This paper addresses the selection of smoothing parameters for estimating the average treatment effect on the treated using matching methods. Because precise estimation of the expected counterfactual is particularly important in regions containing the mass of the treated units, we define and implement weighted cross-validation approaches that improve over conventional methods by considering the location of the treated units in the selection of the smoothing parameters. We also implement a locally varying bandwidth method that uses larger bandwidths in areas where the mass of the treated units is located. A Monte Carlo study compares our proposed methods to the conventional unweighted method and to a related method inspired by Bergemann et al. (2005). The Monte Carlo analysis indicates efficiency gains from all methods that take account of the location of the treated units. We also apply all five methods to bandwidth selection in the context of the data from LaLonde's (1986) study of the performance of non-experimental estimators using the experimental data from the National Supported Work (NSW) Demonstration program as a benchmark. Overall, both the Monte Carlo analysis and the empirical application show feasible precision gains for the weighted cross-validation and the locally varying bandwidth approaches.

Keywords: matching, cross-validation, kernel regression, Monte Carlo simulation

JEL Classification: C13, C14

Suggested Citation

Galdo, José and Smith, Jeffrey Andrew and Black, Dan, Bandwidth Selection and the Estimation of Treatment Effects with Unbalanced Data (October 2007). IZA Discussion Paper No. 3095. Available at SSRN: https://ssrn.com/abstract=1028208

José Galdo

Syracuse University - Department of Economics ( email )

Syracuse, NY 13244-1020
United States

IZA Bonn

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

Jeffrey Andrew Smith (Contact Author)

University of Wisconsin - Madison

716 Langdon Street
Madison, WI 53706-1481
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Institute for the Study of Labor (IZA)

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

Dan Black

University of Chicago - Harris School of Public Policy ( email )

1155 East 60th Street
Chicago, IL 60637
United States

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