Unexplained Gaps and Oaxaca-Blinder Decompositions

25 Pages Posted: 14 Feb 2009

See all articles by Todd E. Elder

Todd E. Elder

Michigan State University

John Goddeeris

Michigan State University

Steven J. Haider

Michigan State University - Department of Economics; IZA Institute of Labor Economics

Multiple version iconThere are 2 versions of this paper

Date Written: February 2009

Abstract

We analyze four methods to measure unexplained gaps in mean outcomes: three decompositions based on the seminal work of Oaxaca (1973) and Blinder (1973) and an approach involving a seemingly naive regression that includes a group indicator variable. Our analysis yields two principal findings. We first show that a commonly-used pooling decomposition systematically overstates the contribution of observable characteristics to mean outcome differences, therefore understating unexplained differences. We also show that the coefficient on a group indicator variable from an OLS regression is an attractive approach for obtaining a single measure of the unexplained gap. We then provide three empirical examples that explore the practical importance of our analytic results.

Keywords: decompositions, discrimination

JEL Classification: J24, J31, J15, J16

Suggested Citation

Elder, Todd E. and Goddeeris, John and Haider, Steven J., Unexplained Gaps and Oaxaca-Blinder Decompositions (February 2009). Available at SSRN: https://ssrn.com/abstract=1342576 or http://dx.doi.org/10.2139/ssrn.1342576

Todd E. Elder (Contact Author)

Michigan State University ( email )

110 Marshall-Adams Hall
Department of Economics
East Lansing, MI 48824
United States
517-355-0353 (Phone)

John Goddeeris

Michigan State University ( email )

East Lansing, MI 48824
United States

Steven J. Haider

Michigan State University - Department of Economics ( email )

East Lansing, MI 48824
United States

IZA Institute of Labor Economics

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

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