Closing the U.S. gender wage gap requires understanding its heterogeneity
This provides insights for policymakers to design more effective anti-discrimination and pay equity policies, though it is incremental in applying existing methods to new data.
The paper analyzed 2016 U.S. wage data to quantify heterogeneity in the gender wage gap, finding it varied substantially across women and was driven by factors like marital status, children, race, occupation, industry, and education.
In 2016, the majority of full-time employed women in the U.S. earned significantly less than comparable men. The extent to which women were affected by gender inequality in earnings, however, depended greatly on socio-economic characteristics, such as marital status or educational attainment. In this paper, we analyzed data from the 2016 American Community Survey using a high-dimensional wage regression and applying double lasso to quantify heterogeneity in the gender wage gap. We found that the gap varied substantially across women and was driven primarily by marital status, having children at home, race, occupation, industry, and educational attainment. We recommend that policy makers use these insights to design policies that will reduce discrimination and unequal pay more effectively.