Augmenting the Human Capital Earnings Equation with Measures of Where People Work
We augment standard ln earnings equations with variables reflecting unmeasured attributes of workers and measured and unmeasured attributes of their employer. Using panel employee-establishment data for US manufacturing we find that the observable employer characteristics that most impact earnings are: number of workers, education of co-workers, capital equipment per worker, industry in which the establishment produces, and R&D intensity of the firm. Employer fixed effects also contribute to the variance of ln earnings, though substantially less than individual fixed effects. In addition to accounting for some of the variance in earnings, the observed and unobserved measures of employers mediate the estimated effects of individual characteristics on earnings and increasing earnings inequality through the sorting of workers among establishments.
We have benefited from support from the Labor and Worklife Program at Harvard University, NBER and from the Norwegian Research Council (projects # 202647 and 199836 (Barth)). Thanks to Thomas Lemieux for very useful comments. Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the U.S. Census Bureau. All results have been reviewed to ensure that no confidential information is disclosed. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Erling Barth & James Davis & Richard B. Freeman, 2018. "Augmenting the Human Capital Earnings Equation with Measures of Where People Work," Journal of Labor Economics, vol 36(S1), pages S71-S97.
Augmenting the Human Capital Earnings Equation with Measures of Where People Work, Erling Barth, James Davis, Richard B. Freeman. in Firms and the Distribution of Income: The Roles of Productivity and Luck, Lazear and Shaw. 2018