Employer Learning and the Signaling Value of Education

41 Pages Posted: 18 Aug 2000 Last revised: 12 Nov 2022

See all articles by Joseph G. Altonji

Joseph G. Altonji

Yale University - Economic Growth Center; National Bureau of Economic Research (NBER); Yale University - Cowles Foundation

Charles R. Pierret

Bureau of Labor Statistics

Date Written: January 1996

Abstract

If profit maximizing firms have limited information about the general productivity of new workers, they may choose to use easily observable characteristics such as years of education to 'statistically discriminate' among workers. The pure credential value of education will depend on how quickly firms learn. To obtain information on employer learning, we work with a wage equation that contains both the interaction between experience and a hard-to-observe variable that is positively related to productivity and the interaction between experience and a variable that firms can easily observe, such as years of education. The time path of the coefficient on the unobservable productivity variable provides information about the rate at which employers learn about worker productivity. Using data from the NLSY we obtain preliminary estimates of the rate at which employers learn about worker quality and use these, along with some strong auxiliary assumptions, to explore the empirical relevance of the educational screening hypothesis. We show that even if employers learn relatively slowly about the productivity of new workers, the portion of the return to education that could reflect signaling of ability is limited.

Suggested Citation

Altonji, Joseph G. and Pierret, Charles R., Employer Learning and the Signaling Value of Education (January 1996). NBER Working Paper No. w5438, Available at SSRN: https://ssrn.com/abstract=225495

Joseph G. Altonji (Contact Author)

Yale University - Economic Growth Center ( email )

Box 208269
New Haven, CT 06520-8269
United States

National Bureau of Economic Research (NBER)

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Yale University - Cowles Foundation

Box 208281
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Charles R. Pierret

Bureau of Labor Statistics

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Washington, DC 20212
United States