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Seeing What is Representative

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  • Ignacio Esponda
  • Ryan Oprea
  • Sevgi Yuksel

Abstract

We provide evidence for a bias that we call “representative signal distortion” (RSD), which is particularly relevant to settings of statistical discrimination. Experimental subjects distort their evaluation of new evidence on individual group members and interpret such information to be more representative of the group to which the individual belongs (relative to a reference group) than it really is. This produces a discriminatory gap in the evaluation of members of the two groups. Because it is driven by representativeness, the bias (and the discriminatory gap) disappears when subjects are prevented from contrasting different groups; because it is a bias in the interpretation of information, it disappears when subjects receive information before learning of the individual’s group. We show that this bias can be easily estimated from appropriately constructed data sets and can be distinguished from previously documented inferential biases in the literature. Importantly, we document how removing the bias produces a kind of free lunch in reducing discrimination, making it possible to significantly reduce discrimination without lowering accuracy of inferences.

Suggested Citation

  • Ignacio Esponda & Ryan Oprea & Sevgi Yuksel, 2023. "Seeing What is Representative," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(4), pages 2607-2657.
  • Handle: RePEc:oup:qjecon:v:138:y:2023:i:4:p:2607-2657.
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    File URL: http://hdl.handle.net/10.1093/qje/qjad020
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    Cited by:

    1. Barron, Kai & Ditlmann, Ruth & Gehrig, Stefan & Schweighofer-Kodritsch, Sebastian, 2020. "Explicit and implicit belief-based gender discrimination: A hiring experiment," Discussion Papers, Research Unit: Economics of Change SP II 2020-306, WZB Berlin Social Science Center.

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