Employer Learning And Statistical Discrimination
AbstractWe show that if firms statistically discriminate among young workers on the basis of easily observable characteristics such as education, then as firms learn about productivity, the coefficients on the easily observed variables should fall, and the coefficients on hard-to-observe correlates of productivity should rise. We find support for this proposition using NLSY79 data on education, the AFQT test, father's education, and wages for young men and their siblings. We find little evidence for statistical discrimination in wages on the basis of race. Our analysis has a wide range of applications in the labor market and elsewhere. © 2000 the President and Fellows of Harvard College and the Massachusetts Institute of Technology
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Bibliographic InfoArticle provided by MIT Press in its journal The Quarterly Journal of Economics.
Volume (Year): 116 (2001)
Issue (Month): 1 (February)
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Other versions of this item:
- Joseph G. Altonji & Charles R. Pierret, . "Employer Learning and Statistical Discrimination," IPR working papers 97-18, Institute for Policy Resarch at Northwestern University.
- Joseph G. Altonji & Charles R. Pierret, 1997. "Employer Learning and Statistical Discrimination," NBER Working Papers 6279, National Bureau of Economic Research, Inc.
- Joseph G. Altonji & Charles R. Pierret, 1997. "Employer learning and statistical discrimination," Working Paper Series, Macroeconomic Issues WP-97-11, Federal Reserve Bank of Chicago.
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
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