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This paper is part of the Global Income Dynamics Project cross-countrycomparison of earnings inequality, volatility, and mobility. Using data fromthe U.S. Census Bureau's Longitudinal Employer-Household Dynamics (LEHD)infrastructure files we produce a uniform set of earnings statistics for theU.S. From 1998 to 2019, we find U.S. earnings inequality has increased andvolatility has decreased. The combination of increased inequality and reducedvolatility suggest earnings growth differs substantially across differentdemographic groups. We explore this further by estimating 12-year averageearnings for a single cohort of age 25-54 eligible workers. Differences inlabor supply (hours paid and quarters worked) are found to explain almost 90%of the variation in worker earnings, although even after controlling for laborsupply substantial earnings differences across demographic groups remainunexplained. Using a quantile regression approach, we estimate counterfactualearnings distributions for each demographic group. We find that at the bottomof the earnings distribution differences in characteristics such as hours paid,geographic division, industry, and education explain almost all the earningsgap, however above the median the contribution of the differences in thereturns to characteristics becomes the dominant component.

U.S. Long-Term Earnings Outcomes by Sex, Race, Ethnicity, and Place of Birth