Augmenting the Human Capital Earnings Equation with Measures of Where People Work

Erling Barth, James Davis and Richard Freeman

No 22512, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: J0 J01 J24 J3 J40 (search for similar items in EconPapers)
Date: 2016-08
New Economics Papers: this item is included in nep-hrm, nep-lab and nep-ltv
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Published as 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.
Published as 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

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Working Paper: Augmenting the Human Capital Earnings Equation with Measures of Where People Work (2016)
Chapter: Augmenting the Human Capital Earnings Equation with Measures of Where People Work (2015)
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