Accounting for the Black-White Wealth Gap: A Nonparametric Approach
This paper notes a potential problem in the method of Blinder and Oaxaca the most popular method in the literature for decomposing the mean difference between groups of a given variable into the portion attributable to differences in the distribution of some explanatory variables and differences in the conditional expectation functions. In its conventional application, the Blinder-Oaxaca method requires that a parametric assumption be made about the form of the conditional expectations function. We show that misspecification is likely to result in non-trivial errors in inference regarding the portion attributable to differences in the distribution of explanatory variables. A nonparametric alternative to the Blinder-Oaxaca method is proposed. Rather than specify an arbitrary functional form for the conditional expectations function, the method re-weights the empirical distribution of the outcome variable using weights that equalize the empirical distributions of the explanatory variable. Applying this method to the large black-white gap in net worth, we document a substantial difference in the estimated role of earnings differences between the two methods. Our estimates suggest that differences in earnings account for roughly two-thirds of the overall wealth gap.
Published: Barsky, Robert, John Bound, Kerwin Kofi Charles and Joseph P. Lupton. "Accounting For The Black-White Wealth Gap: A Nonparametric Approach," Journal of the American Statistical Association, 2002, v97(459,Sep), 663-673.
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