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Decentralized matching and social segregation

Author

Listed:
  • Chen, Yan
  • Fehr, Ernst
  • Fischbacher, Urs
  • Morgan, Peter

Abstract

Social segregation is a ubiquitous feature of human life. People segregate along the lines of income, religion, ethnicity, language, and other characteristics. This study provides the first experimental examination of decentralized matching with search frictions and institutionalized segregation. The findings indicate that, without a segregation institution, high types over-segregate relative to the equilibrium prediction. We observe segregation attempts even when equilibrium suggests that everyone should accept everyone else. In the presence of a segregation institution, we find that, while the symmetric segregation institution increases matching success rate and efficiency in one environment, it has weak or no effect in a steep-incentive environment. By adding an entry cost to a flat-incentive market, however, the asymmetric segregation institution leads to an increased matching success rate and efficiency in both environments, which underscores the importance of a coordination device.

Suggested Citation

  • Chen, Yan & Fehr, Ernst & Fischbacher, Urs & Morgan, Peter, 2015. "Decentralized matching and social segregation," Games and Economic Behavior, Elsevier, vol. 90(C), pages 17-43.
  • Handle: RePEc:eee:gamebe:v:90:y:2015:i:c:p:17-43
    DOI: 10.1016/j.geb.2014.11.004
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    References listed on IDEAS

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    Cited by:

    1. Bernard, Mark & Hett, Florian & Mechtel, Mario, 2016. "Social identity and social free-riding," European Economic Review, Elsevier, vol. 90(C), pages 4-17.

    More about this item

    Keywords

    Decentralized matching; Segregation; Experiment;

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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