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Statistical Discrimination with Neighborhood Effects: Can Integration Eliminate Negative Stereotypes?

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  • Shubham Chaudhuri

    (Columbia University)

  • Rajiv Sethi

    (Columbia University)

Abstract

We introduce neighborhood effects in the costs of human capital acquisition into a model of statistical discrimination in labor markets. This creates a link between the level of segregation and the likelihood and extent of statistical discrimination. As long as negative stereotypes persist in the face of increasing integration, skill levels rise in the disadvantaged group and fall in the advantaged group. If integration proceeds beyond some threshold, however, there can be a qualitative change in the set of equilibria, with negative stereotypes becoming unsustainable and skill levels in both groups changing significantly. This change can work in either direction: skill levels may rise in both groups, or fall in both groups. Which of these outcomes arises depends on the population share of the disadvantaged group, and on the curvature of the relationship between neighborhood quality and the costs of human capital accumulation.

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Bibliographic Info

Paper provided by EconWPA in its series Game Theory and Information with number 0312001.

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Date of creation: 04 Dec 2003
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Handle: RePEc:wpa:wuwpga:0312001

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Keywords: Statistical discrimination; Neighborhood effects; Human capital spillovers;

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Cited by:
  1. Brendan O'Flaherty & Rajiv Sethi, 2004. "Robbery and Race," Game Theory and Information 0411005, EconWPA, revised 10 Jan 2005.
  2. Sáez-Martí, Maria & Zenou, Yves, 2010. "Cultural Transmission and Discrimination," CEPR Discussion Papers 7622, C.E.P.R. Discussion Papers.
  3. Samuel Bowles & Rajiv Sethi, 2006. "Social Segregation and the Dynamics of Group Inequality," UMASS Amherst Economics Working Papers 2006-02, University of Massachusetts Amherst, Department of Economics.

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