Testing for Selection Bias

41 Pages Posted: 27 Sep 2014

See all articles by Joonhwi Joo

Joonhwi Joo

University of Texas at Dallas - Naveen Jindal School of Management

Robert LaLonde

University of Chicago, Harris School of Public Policy (deceased); National Bureau of Economic Research (NBER) (deceased); IZA Institute of Labor Economics (deceased)

Abstract

This paper uses the control function to develop a framework for testing for selection bias. The idea behind our framework is if the usual assumptions hold for matching or IV estimators, the control function identifies the presence and magnitude of potential selection bias. Averaging this correction term with respect to appropriate weights yields the degree of selection bias for alternative treatment effects of interest. One advantage of our framework is that it motivates when is appropriate to use more efficient estimators of treatment effects, such as those based on least squares or matching. Another advantage of our approach is that it provides an estimate of the magnitude of the selection bias. We also show how this estimate can help when trying to infer program impacts for program participants not covered by LATE estimates.

Keywords: selection bias, program evaluation, average treatment effects

JEL Classification: C21, C26, D04

Suggested Citation

Joo, Joonhwi and LaLonde, Robert J., Testing for Selection Bias. IZA Discussion Paper No. 8455, Available at SSRN: https://ssrn.com/abstract=2502315 or http://dx.doi.org/10.2139/ssrn.2502315

Joonhwi Joo (Contact Author)

University of Texas at Dallas - Naveen Jindal School of Management ( email )

P.O. Box 830688
Richardson, TX TX 75083-0688
United States
75080 (Fax)

Robert J. LaLonde

University of Chicago, Harris School of Public Policy (deceased)

National Bureau of Economic Research (NBER) (deceased)

IZA Institute of Labor Economics (deceased)

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
171
Abstract Views
1,585
Rank
346,395
PlumX Metrics