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On Statistical Discrimination as a Failure of Social Learning: A Multiarmed Bandit Approach

Author

Listed:
  • Junpei Komiyama

    (Leonard N. Stern School of Business, New York University, New York, New York 10012)

  • Shunya Noda

    (Graduate School of Economics, The University of Tokyo, Tokyo 113-0033, Japan)

Abstract

We analyze statistical discrimination in hiring markets using a multiarmed bandit model. Myopic firms face workers arriving with heterogeneous observable characteristics. The association between the worker’s skill and characteristics is unknown ex ante; thus, firms need to learn it. Laissez-faire causes perpetual underestimation: minority workers are rarely hired, and therefore, the underestimation tends to persist. Even a marginal imbalance in the population ratio frequently results in perpetual underestimation. We demonstrate that a subsidy rule that is implemented as temporary affirmative action effectively alleviates discrimination stemming from insufficient data.

Suggested Citation

  • Junpei Komiyama & Shunya Noda, 2026. "On Statistical Discrimination as a Failure of Social Learning: A Multiarmed Bandit Approach," Management Science, INFORMS, vol. 72(1), pages 442-455, January.
    • Handle: RePEc:inm:ormnsc:v:72:y:2026:i:1:p:442-455
    DOI: 10.1287/mnsc.2022.00893
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    References listed on IDEAS

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    1. Dianat, Ahrash & Echenique, Federico & Yariv, Leeat, 2022. "Statistical discrimination and affirmative action in the lab," Games and Economic Behavior, Elsevier, vol. 132(C), pages 41-58.
    2. Cornell, Bradford & Welch, Ivo, 1996. "Culture, Information, and Screening Discrimination," Journal of Political Economy, University of Chicago Press, vol. 104(3), pages 542-571, June.
    3. Lones Smith & Peter Sorensen, 2000. "Pathological Outcomes of Observational Learning," Econometrica, Econometric Society, vol. 68(2), pages 371-398, March.
    4. J. Aislinn Bohren & Alex Imas & Michael Rosenberg, 2019. "The Dynamics of Discrimination: Theory and Evidence," American Economic Review, American Economic Association, vol. 109(10), pages 3395-3436, October.
    5. Art B. Owen & Hal Varian, 2018. "Optimizing the tie-breaker regression discontinuity design," Papers 1808.07563, arXiv.org, revised Jul 2020.
    6. Phelps, Edmund S, 1972. "The Statistical Theory of Racism and Sexism," American Economic Review, American Economic Association, vol. 62(4), pages 659-661, September.
    7. Moro, Andrea & Norman, Peter, 2004. "A general equilibrium model of statistical discrimination," Journal of Economic Theory, Elsevier, vol. 114(1), pages 1-30, January.
    8. Danielle Li & Lindsey R. Raymond & Peter Bergman, 2020. "Hiring as Exploration," NBER Working Papers 27736, National Bureau of Economic Research, Inc.
    9. Yiangos Papanastasiou & Kostas Bimpikis & Nicos Savva, 2018. "Crowdsourcing Exploration," Management Science, INFORMS, vol. 64(4), pages 1727-1746, April.
    10. Paat Rusmevichientong & John N. Tsitsiklis, 2010. "Linearly Parameterized Bandits," Mathematics of Operations Research, INFORMS, vol. 35(2), pages 395-411, May.
    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. David Neumark, 2018. "Experimental Research on Labor Market Discrimination," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 799-866, September.
    13. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    14. Hamsa Bastani & Mohsen Bayati & Khashayar Khosravi, 2021. "Mostly Exploration-Free Algorithms for Contextual Bandits," Management Science, INFORMS, vol. 67(3), pages 1329-1349, March.
    15. Dean P. Foster & Rakesh V. Vohra, 1992. "An Economic Argument for Affirmative Action," Rationality and Society, , vol. 4(2), pages 176-188, April.
    16. Rema N. Hanna & Leigh L. Linden, 2012. "Discrimination in Grading," American Economic Journal: Economic Policy, American Economic Association, vol. 4(4), pages 146-168, November.
    17. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
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