Journal Of The Econometric Society

An International Society for the Advancement of Economic
Theory in its Relation to Statistics and Mathematics

Edited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262

Econometrica: Mar, 2024, Volume 92, Issue 2

Production and Learning in Teams
p. 467-504

Kyle Herkenhoff, Jeremy Lise, Guido Menzio, Gordon M. Phillips

To what extent is a worker's human capital growth affected by the quality of his coworkers? To answer this question, we develop and estimate a model in which the productivity and the human capital growth of an individual depend on the average human capital of his coworkers. The measured production function is supermodular: The marginal product of a more knowledgeable individual is increasing in the human capital of his coworkers. The measured human capital accumulation function is convex: An individual's human capital growth is increasing in coworkers' human capital only when paired with more knowledgeable coworkers, but independent of coworkers' human capital when paired with less knowledgeable coworkers. Learning from coworkers accounts for two thirds of the stock of human capital accumulated on the job. Technological changes that increase production supermodularity lead to labor market segregation and, by reducing the opportunities for low human capital workers to learn from better coworkers, lead to a decline in aggregate human capital and output.

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Supplemental Material

Supplement to "Production and Learning in Teams"

Kyle Herkenhoff, Jeremy Lise, Guido Menzio, and Gordon Phillips

The replication package for this paper is available at The authors were granted an exemption to publish parts of their data because either access to the data is restricted or the authors do not have the right to republish them. They were also granted an exemption from publishing parts of their code, because the terms of use of their the data does not allow them to share information on some of the variables. The journal checked the public parts of the replication package for their ability to reproduce the results in the paper and approved online appendices. The replication package contains information on how authors can obtain access to the original data and code, archived by the data provider for a period of at least 10 years. During that time, authors commit to assist users who, having obtained access to the confidential part of the package, may have trouble reproducing the results generated from the confidential data and codes.

Supplement to "Production and Learning in Teams"

Kyle Herkenhoff, Jeremy Lise, Guido Menzio, and Gordon Phillips

This appendix contains material not found within the manuscript.