Augmenting the Human Capital Earnings Equation With Measures of Where People Work
Peer reviewed, Journal article
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Date
2018Metadata
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Abstract
We augment standard log earnings equations for workers in US manufacturing with variables reflecting measured and unmeasured attributes of their employer. Using panel employee-establishment data, we find that establishment-level employment, education of coworkers, capital equipment per worker, and firm-level R&D intensity affects earnings substantially. Unobserved characteristics of employers captured by employer fixed effects also contribute to the variance of log earnings, although less than unobserved characteristics of individuals captured by individual fixed effects. The observed and unobserved measures of employers mediate the effects of individual characteristics on earnings and increase earnings inequality through sorting of workers among establishments