  This paper is part of the Global Income Dynamics 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. Differences in
labor supply (hours paid and quarters worked) are found to explain almost 90%
of the variation in worker earnings, although even after controlling for labor
supply substantial earnings differences across demographic 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 all the earnings
gap, however above the median the contribution of the differences in the
returns to characteristics becomes the dominant component.
