Oaxaca decomposition

Abstract: Regressions explaining the wage rates of white males, black males, and white females are used to analyze the white-black wage differential among men and the male-female wage differential among whites A distinction is drawn between reduced form and structural wage equations, and both are estimated They are shown to have very different implications for analyzing the white-black and male-female wage differentials When the two sets of estimates are synthesized, they jointly imply that 70 percent of the overall race differential and 100 percent of the overall sex differential are ultimately attributable to discrimination of various sorts

Abstract: The counterfactual decomposition technique popularized by Blinder (1973, Journal of Human Resources, 436–455) and Oaxaca (1973, International Economic Review, 693–709) is widely used to study mean outcome differences between groups. For example, the technique is often used to analyze wage gaps by sex or race. This article summarizes the technique and addresses several complications, such as the identification of effects of categorical predictors in the detailed decomposition or the estimation of standard errors. A new command called oaxaca is introduced, and examples illustrating its usage are given.

Abstract: This paper considers the linkage of empirical estimates of wage discrimination between two groups, introduced by Oaxaca (1973), to a theoretical model of employers' discriminatory behavior. It is shown that, conditional on different assumptions about employers' discriminatory tastes, Oaxaca's estimators of wage discrimination can be derived. That the approach is more generally useful is demonstrated by deriving an alternative estimator of wage discrimination, based on the assumption that within each type of labor (e.g., unskilled, skilled) the utility function capturing employers' discriminatory tastes is homogeneous of degree zero with respect to labor inputs from each of the two groups. The estimators are compared empirically in an application to male-female wage differentials.

Abstract: The Blinder-Oaxaca decomposition technique is widely used to identify and quantify the separate contributions of group differences in measurable characteristics, such as education, experience, marital status, and geographical differences to racial and gender gaps in outcomes. The technique cannot be used directly, however, if the outcome is binary and the coefficients are from a logit or probit model. I describe a relatively simple method of performing a decomposition that uses estimates from a logit or probit model. Expanding on the original application of the technique in Fairlie (1999), I provide a more thorough discussion of how to apply the technique, an analysis of the sensitivity of the decomposition estimates to different parameters, and the calculation of standard errors.