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The hazards and benefits of condescension in social learning

Author

Listed:
  • Arieli, Itai

    (Data and Decision Sciences, Technion–Israel Institute of Technology)

  • Babichenko, Yakov

    (Data and Decision Sciences, Technion–Israel Institute of Technology)

  • Müller, Stephan

    (Department of Economics, University of Goettingen)

  • Pourbabaee, Farzad

    (Department of Economics, Caltech)

  • Tamuz, Omer

    (Department of Economics, Caltech)

Abstract
In a misspecified social learning setting, agents are condescending if they perceive their peers as having private information that is of lower quality than it is in reality. Applying this to a standard sequential model, we show that outcomes improve when agents are mildly condescending. In contrast, too much condescension leads to worse outcomes, as does anti-condescension.

Suggested Citation

  • Arieli, Itai & Babichenko, Yakov & Müller, Stephan & Pourbabaee, Farzad & Tamuz, Omer, 0. "The hazards and benefits of condescension in social learning," Theoretical Economics, Econometric Society.
    • Handle: RePEc:the:publsh:5743
    as

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    References listed on IDEAS

    as
    1. Bogaçhan Çelen & Sen Geng & Huihui Li, 2018. "Belief Error and Non-Bayesian Social Learning: An Experimental Evidence," GRU Working Paper Series GRU_2018_022, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Social learning;

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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