28 Pages Posted: 13 May 2009
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.
Keywords: decompositions, discrimination
JEL Classification: J31, J24, J15, J16
Suggested Citation: 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: https://ssrn.com/abstract=1402506