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  • Bagues, Manuel
  • Perez-Villadoniga, Maria J.

Abstract

In this paper we extend the standard model of statistical discrimination to a multidimensional framework where the accuracy of evaluators depends on how knowledgeable they are in each dimension. The model yields two main implications. First, candidates who excel in the same dimensions as the evaluator tend to be preferred. Second, if two equally productive groups of workers differ in their distribution of ability across dimensions group discrimination will arise unless (i) evaluators are well informed about the extent of these differences and (ii) evaluators can take candidatesʼ group belonging into account in their assessments.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Economic Theory.

Volume (Year): 148 (2013)
Issue (Month): 3 ()
Pages: 1292-1299

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Handle: RePEc:eee:jetheo:v:148:y:2013:i:3:p:1292-1299

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Web page: http://www.elsevier.com/locate/inca/622869

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Keywords: Statistical discrimination; Similar-to-me effect;

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References

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Cited by:
  1. 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.
  2. Manuel Bagues & Maria Jose Perez-Villadoniga, 2009. "Do recruiters prefer applicants with similar skills? Evidence from a randomized natural experiment," Business Economics Working Papers wb090562, Universidad Carlos III, Departamento de Economía de la Empresa.
  3. Natalia Zinovyeva & Manuel F. Bagues, 2010. "Does gender matter for academic promotion? Evidence from a randomized natural experiment," Working Papers 2010-15, FEDEA.

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