Abstract

http://ssrn.com/abstract=1402506
 
 

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Unexplained Gaps and Oaxaca-Blinder Decompositions


Todd E. Elder


Michigan State University

John Goddeeris


Michigan State University

Steven J. Haider


Michigan State University - Department of Economics; Institute for the Study of Labor (IZA)


IZA Discussion Paper No. 4159

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 naïve regression that includes a group indicator variable. Our analysis yields two principal findings. We 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 also show that a commonly-used pooling decomposition systematically overstates the contribution of observable characteristics to mean outcome differences when compared to OLS regression, therefore understating unexplained differences. We then provide three empirical examples that explore the practical importance of our analytic results.

Number of Pages in PDF File: 28

Keywords: decompositions, discrimination

JEL Classification: J31, J24, J15, J16

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Date posted: May 13, 2009  

Suggested Citation

Elder, Todd E. and Goddeeris, John and Haider, Steven J., Unexplained Gaps and Oaxaca-Blinder Decompositions. IZA Discussion Paper No. 4159. Available at SSRN: http://ssrn.com/abstract=1402506

Contact Information

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
Institute for the Study of Labor (IZA)
P.O. Box 7240
Bonn, D-53072
Germany
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