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Testing Theories of Discrimination: Evidence from "Weakest Link"

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  • Steven D. Levitt

Abstract

In most settings, it is difficult to measure discrimination, and even more challenging to distinguish between competing theories of discrimination (taste-based versus information-based). Using contestant voting behavior on the television game show Weakest Link, one can in principle empirically address both of these questions. On the show, contestants answer questions and vote off other players, competing for a winner-take-all prize. In early rounds, strategic incentives encourage voting for the weakest competitors. In later rounds, the incentives reverse, and the strongest competitors become the logical target. Controlling for other observable characteristics including the number of correct answers thus far, both theories of discrimination predict that in early rounds, excess votes will be made against groups targeted for discrimination. In later rounds, however, taste-based models predict continued excess votes, whereas statistical discrimination predicts fewer votes against the target group. Empirically, I find some evidence of information-based discrimination towards Hispanics (i.e., other players perceive them as having low ability) and taste-based discrimination against older players (i.e., other players treat them with animus). There is little in the data to suggest discrimination against women and Blacks.

Suggested Citation

  • Steven D. Levitt, 2003. "Testing Theories of Discrimination: Evidence from "Weakest Link"," NBER Working Papers 9449, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:9449
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    1. John Knowles & Nicola Persico & Petra Todd, 2001. "Racial Bias in Motor Vehicle Searches: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 109(1), pages 203-232, February.
    2. Marco Haan & Bart Los & Yohanes Riyanto & Martin van Geest, 2002. "The Weakest Link - A Field Experiment in Rational Decision Making," Experimental 0203001, University Library of Munich, Germany.
    3. Metrick, Andrew, 1995. "A Natural Experiment in "Jeopardy!"," American Economic Review, American Economic Association, vol. 85(1), pages 240-253, March.
    4. Joseph G. Altonji & Charles R. Pierret, 2001. "Employer Learning and Statistical Discrimination," The Quarterly Journal of Economics, Oxford University Press, vol. 116(1), pages 313-350.
    5. Lundberg, Shelly J & Startz, Richard, 1983. "Private Discrimination and Social Intervention in Competitive Labor Markets," American Economic Review, American Economic Association, vol. 73(3), pages 340-347, June.
    6. Roland G. Fryer & Matthew O. Jackson, 2002. "Categorical Cognition: A Psychological Model of Categories and Identification in Decision Making," Microeconomics 0211002, University Library of Munich, Germany.
    7. Altonji, Joseph G. & Blank, Rebecca M., 1999. "Race and gender in the labor market," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 48, pages 3143-3259, Elsevier.
    8. repec:dgr:rugsom:02f20 is not listed on IDEAS
    9. Phelps, Edmund S, 1972. "The Statistical Theory of Racism and Sexism," American Economic Review, American Economic Association, vol. 62(4), pages 659-661, September.
    10. Fevrier, Philippe & Linnemer, Laurent, 2006. "Equilibrium selection: Payoff or risk dominance?: The case of the "weakest link"," Journal of Economic Behavior & Organization, Elsevier, vol. 60(2), pages 164-181, June.
    11. Coate, Stephen & Loury, Glenn C, 1993. "Will Affirmative-Action Policies Eliminate Negative Stereotypes?," American Economic Review, American Economic Association, vol. 83(5), pages 1220-1240, December.
    12. Lawrence M. Kahn, 1991. "Discrimination in Professional Sports: A Survey of the Literature," ILR Review, Cornell University, ILR School, vol. 44(3), pages 395-418, April.
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    More about this item

    JEL classification:

    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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