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Pol Campos . Photo

Pol Campos

Senior lecturer

Pol Campos . Photo

Non-Bayesian Statistical Discrimination

Author

  • Pol Campos-Mercade
  • Friederike Mengel

Summary, in English

Models of statistical discrimination typically assume that employers make rational inference from (education) signals. However, there is a large amount of evidence showing that most people do not update their beliefs rationally. We use a model and two experiments to show that employers who are conservative, in the sense of signal neglect, discriminate more against disadvantaged groups than Bayesian employers. We find that such non-Bayesian statistical discrimination deters high-ability workers from disadvantaged groups from pursuing education, further exacerbating initial group inequalities. Excess discrimination caused by employer conservatism is especially important when signals are very informative. Out of the overall hiring gap in our data, around 40% can be attributed to Bayesian statistical discrimination, a further 40% is due to non-Bayesian statistical discrimination, and the remaining 20% is unexplained or potentially taste-based.

Department/s

  • Department of Economics

Publishing year

2024

Language

English

Pages

2549-2567

Publication/Series

Management Science

Volume

70

Issue

4

Document type

Journal article

Publisher

INFORMS Institute for Operations Research and the Management Sciences

Topic

  • Economics

Status

Published

ISBN/ISSN/Other

  • ISSN: 0025-1909