U.S. long‐term earnings outcomes by sex, race, ethnicity, and place of birth

Abstract

This paper is part of the Global Repository of Income Dynamics (GRID) project cross‐country comparison of earnings inequality, volatility, and mobility. Using data from the U.S. Census Bureau's Longitudinal Employer‐Household Dynamics (LEHD) infrastructure files, we produce a uniform set of earnings statistics for the U.S. From 1998 to 2019, we find U.S. earnings inequality has increased and volatility has decreased. The combination of increased inequality and reduced volatility suggest earnings growth differs substantially across different demographic groups. We explore this further by estimating 12‐year average earnings for a single cohort of age 25–54 eligible workers. Overall, differences in labor supply (hours paid and quarters worked) are found to explain almost 90% of the variation in worker earnings at the mean, although substantial earnings differences across and within groups remain unexplained. Using a quantile regression approach, we estimate counterfactual earnings distributions for each demographic group. We find that at the bottom of the earnings distribution differences in characteristics such as hours paid, geographic division, industry, and education explain almost the entire earnings gap; however, above the median the contribution of the differences in the returns to characteristics is the dominant component.