Employer Learning and Statistical Discrimination

67 Pages Posted: 18 Aug 2000  

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

Multiple version iconThere are 2 versions of this paper

Date Written: November 1997

Abstract

We provide a test for statistical discrimination or rational stereotyping in in environments in which agents learn over time. Our application is to the labor market. 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. As firms acquire more information about a worker, pay will become more dependent on actual productivity and less dependent on easily observable characteristics or credentials that predict productivity. Consider 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. We show that the wage coefficient on the unobservable productivity variable should rise with time in the labor market and the wage coefficient on education should fall. We investigate this proposition using panel data on education, the AFQT test, father's education, and wages for young men and their siblings from NLSY. We also examine the empirical implications of statistical discrimination on the basis of race. Our results support the hypothesis of statistical discrimination, although they are inconsistent with the hypothesis that firms fully utilize the information in race. Our analysis has wide implications for the analysis of the determinants of wage growth and productivity and the analysis of statistical discrimination in the labor market and elsewhere.

Suggested Citation

Altonji, Joseph G. and Pierret, Charles R., Employer Learning and Statistical Discrimination (November 1997). NBER Working Paper No. w6279. Available at SSRN: https://ssrn.com/abstract=226036

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)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Yale University - Cowles Foundation

Box 208281
New Haven, CT 06520-8281
United States

Charles R. Pierret

Bureau of Labor Statistics

2 Massachusetts Avenue, NE
Washington, DC 20212
United States

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