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Empirical Implications of Statistical Discrimination on the Returns to Measures of Skill

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  • Andrea Moro
  • Peter Norman

Abstract

This article investigates how lack of information may bias the investigator's assessment of the presence of statistical discrimination. We show that the nature of the bias is such that statistical discrimination may be rejected in a Mincerian regression even when the data is generated from an equilibrium with statistical discrimination. This may occur even when the investigator has a more informative signal of productivity the employers have.

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  • Andrea Moro & Peter Norman, 2003. "Empirical Implications of Statistical Discrimination on the Returns to Measures of Skill," Annals of Economics and Statistics, GENES, issue 71-72, pages 377-398.
    • Handle: RePEc:adr:anecst:y:2003:i:71-72:p:377-398
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    File URL: http://www.jstor.org/stable/20079061
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    Cited by:

    1. Nicola Persico & Andrew Postlewaite & Dan Silverman, 2004. "The Effect of Adolescent Experience on Labor Market Outcomes: The Case of Height," Journal of Political Economy, University of Chicago Press, vol. 112(5), pages 1019-1053, October.
    2. Vanessa Scholes, 2014. "You Are Not Worth the Risk: Lawful Discrimination in Hiring," Rationality, Markets and Morals, Frankfurt School Verlag, Frankfurt School of Finance & Management, vol. 5(82), February.
    3. Nicola Persico & Andrew Postlewaite & Dan Silverman, 2001. "The Effect of Adolescent Experience on Labor Market Outcomes: The Case of Height, Third Version," PIER Working Paper Archive 04-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 15 Mar 2004.

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