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Updating, self-confidence, and discrimination

Author

Listed:
  • Albrecht, Konstanze
  • von Essen, Emma
  • Parys, Juliane
  • Szech, Nora

Abstract

In this laboratory experiment, we show that people incorporate irrelevant group information when evaluating others. Individuals from groups that perform badly on average receive low evaluations, even when it is known that the individuals themselves perform well. This group-bias occurs both in a gendered setup, where women form the worse performing group, and in a non-gendered setup.

Suggested Citation

  • Albrecht, Konstanze & von Essen, Emma & Parys, Juliane & Szech, Nora, 2013. "Updating, self-confidence, and discrimination," European Economic Review, Elsevier, vol. 60(C), pages 144-169.
  • Handle: RePEc:eee:eecrev:v:60:y:2013:i:c:p:144-169
    DOI: 10.1016/j.euroecorev.2013.02.002
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    References listed on IDEAS

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    1. Dohmen, Thomas & Falk, Armin & Huffman, David & Marklein, Felix & Sunde, Uwe, 2009. "Biased probability judgment: Evidence of incidence and relationship to economic outcomes from a representative sample," Journal of Economic Behavior & Organization, Elsevier, vol. 72(3), pages 903-915, December.
    2. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2008. "Nonparametric Tests for Treatment Effect Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 389-405, August.
    3. Grether, David M., 1992. "Testing bayes rule and the representativeness heuristic: Some experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 17(1), pages 31-57, January.
    4. Markus M. Mobius & Muriel Niederle & Paul Niehaus & Tanya Rosenblat, 2011. "Managing self-confidence: theory and experimental evidence," Working Papers 11-14, Federal Reserve Bank of Boston.
    5. Francine Blau & Jed DeVaro, 2006. "New Evidence on Gender Differences in Promotion Rates: An Empirical Analysis of a Sample of New Hires," Working Papers 891, Princeton University, Department of Economics, Industrial Relations Section..
    6. Manuel F. Bagues & Berta Esteve-Volart, 2010. "Can Gender Parity Break the Glass Ceiling? Evidence from a Repeated Randomized Experiment," Review of Economic Studies, Oxford University Press, vol. 77(4), pages 1301-1328.
    7. Greiner, Ben, 2004. "An Online Recruitment System for Economic Experiments," MPRA Paper 13513, University Library of Munich, Germany.
    8. Phelps, Edmund S, 1972. "The Statistical Theory of Racism and Sexism," American Economic Review, American Economic Association, vol. 62(4), pages 659-661, September.
    9. Muriel Niederle & Lise Vesterlund, 2007. "Do Women Shy Away From Competition? Do Men Compete Too Much?," The Quarterly Journal of Economics, Oxford University Press, vol. 122(3), pages 1067-1101.
    10. Gary Charness & Dan Levin, 2005. "When Optimal Choices Feel Wrong: A Laboratory Study of Bayesian Updating, Complexity, and Affect," American Economic Review, American Economic Association, vol. 95(4), pages 1300-1309, September.
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    Citations

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    Cited by:

    1. Abigail Wozniak, 2015. "Discrimination and the Effects of Drug Testing on Black Employment," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 548-566, July.
    2. Krawczyk, Michał & Smyk, Magdalena, 2016. "Author׳s gender affects rating of academic articles: Evidence from an incentivized, deception-free laboratory experiment," European Economic Review, Elsevier, vol. 90(C), pages 326-335.
    3. Stijn Baert & Ann-Sophie De Pauw & Nick Deschacht, 2016. "Do Employer Preferences Contribute to Sticky Floors?," ILR Review, Cornell University, ILR School, vol. 69(3), pages 714-736, May.
    4. Michał Krawczyk & Natalia Starzykowska, 2017. "Belief-based and taste-based gender discrimination. Evidence from a game show," Working Papers 2017-15, Faculty of Economic Sciences, University of Warsaw.

    More about this item

    Keywords

    Updating; Conservatism; Gender; Discrimination; Self-confidence;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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