Gender Wage Disparities among the Highly Educated
利用美国大学毕业生调查数据，通过非参数匹配分析发现，高学历女性与白人男性之间的工资差距中，44%到99%可由学历、专业等市场前因素解释，且高劳动参与度女性差距更小。
In the U.S. college-educated women earn approximately 30 percent less than their non-Hispanic white male counterparts. We conduct an empirical examination of this wage disparity for four groups of women-non-Hispanic white, black, Hispanic, and Asian-using the National Survey of College Graduates, a large data set that provides unusually detailed information on higher-level education. Nonparametric matching analysis indicates that among men and women who speak English at home, between 44 and 73 percent of the gender wage gaps are accounted for by such pre-market factors as highest degree and major. When we restrict attention further to women who have "high labor force attachment" (i.e., work experience that is similar to male comparables) we account for 54 to 99 percent of gender wage gaps. Our nonparametric approach differs from familiar regression-based decompositions, so for the sake of comparison we conduct parametric analyses as well. Inferences drawn from these latter decompositions can be quite misleading.