Employer Learning, Productivity and the Earnings Distribution: Evidence from Performance Measures

57 Pages Posted: 21 Nov 2016

See all articles by Lisa Kahn

Lisa Kahn

Yale School of Management

Fabian Lange

McGill University

Date Written: August 19, 2013


Pay distributions fan out with experience. The leading explanations for this pattern are that over time, either employers learn about worker productivity but productivity remains fixed or workers’ productivities themselves evolve heterogeneously. We propose a dynamic specification that nests both employer learning and dynamic productivity heterogeneity. We estimate this model on a 20-year panel of pay and performance measures from a single, large firm. The advantage of these data is that they provide us with repeat measures of productivity, some of which have not yet been observed by the firm when it sets wages. We use our estimates to investigate how learning and dynamic productivity heterogeneity jointly contribute to the increase in pay dispersion with age. We find that both mechanisms are important for understanding wage dynamics. The dispersion of pay increases with experience primarily because productivity differences increase. Imperfect learning however means that wages differ significantly from individual productivity all along the life-cycle because firms continuously struggle to learn about a moving target in worker productivity. Our estimates allow us to calculate the degree to which imperfect learning introduces a wedge between the private and social incentives to invest in human capital. We find that these disincentives exist throughout the life-cycle but increase rapidly after about 15 years of experience. Thus, in contrast to the existing literature on employer learning, we find that imperfect learning might have large effects on investments especially among older workers.

Keywords: Employer Learning, Careers

JEL Classification: J33, D83, M50, M51, M52

Suggested Citation

Kahn, Lisa and Lange, Fabian, Employer Learning, Productivity and the Earnings Distribution: Evidence from Performance Measures (August 19, 2013). Available at SSRN: https://ssrn.com/abstract=2872260 or http://dx.doi.org/10.2139/ssrn.2872260

Lisa Kahn

Yale School of Management ( email )

135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
United States

Fabian Lange (Contact Author)

McGill University ( email )

1001 Sherbrooke St. W
Montreal, Quebec H3A 1G5

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