The hazards and benefits of condescension in social learning

Itai Arieli, Yakov Babichenko, Stephan Müller, Farzad Pourbabaee, Omer Tamuz

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)27-56
Number of pages30
JournalTheoretical Economics
Volume20
Issue number1
DOIs
StatePublished - Jan 2025

Keywords

  • D830
  • Social learning

All Science Journal Classification (ASJC) codes

  • General Economics,Econometrics and Finance

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