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

TL;DR

This study analyzes U.S. earnings inequality, volatility, and mobility from 1998 to 2019, revealing increasing inequality, decreasing volatility, and persistent earnings gaps across demographic groups, with labor supply and returns to characteristics as key factors.

Contribution

It provides a comprehensive analysis of long-term earnings outcomes by sex, race, ethnicity, and birthplace using a unified dataset and advanced regression techniques.

Findings

Earnings inequality increased from 1998 to 2019.

Volatility in earnings decreased over the same period.

Labor supply explains nearly 90% of earnings variation.

Abstract

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.