Standard Errors for the Blinder-Oaxaca Decomposition

The decomposition technique introduced by Blinder (1973) and Oaxaca (1973) is widely used to study outcome differences between groups. For example, the technique is commonly applied to the analysis of the gender wage gap. However, despite the procedure's frequent use, very little attention has been paid to the issue of estimating the sampling variances of the decomposition components. We therefore suggest an approach that introduces consistent variance estimators for several variants of the decomposition. The accuracy of the new estimators under ideal conditions is illustrated with the results of a Monte Carlo simulation. As a second check, the estimators are compared to bootstrap results obtained using real data. In contrast to previously proposed statistics, the new method takes into account the extra variation imposed by stochastic regressors.

OAXACA: Stata module to compute the Blinder-Oaxaca decomposition

-oaxaca- computes the so-called Blinder-Oaxaca decomposition, which is often used to analyze wage gaps by sex or race. Older versions of this routine are available as -oaxaca9- and -oaxaca8-.

FAIRLIE: Stata module to generate nonlinear decomposition of binary outcome differentials

fairlie computes the nonlinear decomposition of binary outcome differentials proposed by Fairlie (1999, 2003).

SMITHWELCH: Stata module to compute trend decomposition of outcome differentials

smithwelch computes decompositions of differences in mean outcome differentials. Smith and Welch (1989) used such decomposition techniques in their analysis of the change in the black-white wage differential over time. An alternative application would be the decomposition of country differences in the male-female wage gap.

JMPIERCE2: Stata module to compute trend decomposition of outcome differentials

jmpierce2 computes the decomposition of differences in mean outcome differentials proposed by Juhn, Murphy and Pierce (1991). An example is the decomposition of the change of the black-white or the male-female wage differential over time or the decomposition of differences in the male-female wage differential between countries. This routine was previously circulated as jmp2.

A Stata implementation of the Blinder-Oaxaca decomposition

The counterfactual decomposition technique popularized by Blinder (1973) and Oaxaca (1973) 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. The present paper summarizes the technique and addresses a number of complications such as the identification of effects of categorical predictors in the detailed decomposition or the estimation of standard errors. A new Stata command called -oaxaca- is introduced and examples illustrating its usage are given.