Verifiable communication on networks

Research output: Contribution to journalArticlepeer-review

Abstract

This paper models the diffusion of verifiable information on a network populated by biased agents. Some agents, who are exogenously informed, choose whether to inform their neighbors. Informing a neighbor affects her behavior, but also enables her to inform others. Agents cannot lie; they can, however, feign ignorance. The model yields three main results. First, unless a large set of agents is initially informed, learning is incomplete. Second, full learning is more likely for moderate than for extreme states of the world. Third, when agents are forward-looking, concerns about learning cascades lead to an endogenous division of the population into like-minded groups that do not communicate with each other.

Original languageAmerican English
Article number105494
JournalJournal of Economic Theory
Volume204
DOIs
StatePublished - Sep 2022

ASJC Scopus subject areas

  • Economics and Econometrics

Keywords

  • Learning cascades
  • Networks
  • Social learning
  • Strategic communication
  • Verifiable information

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