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The Wisdom of the Crowd and Higher-Order Beliefs

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  • Yi-Chun Chen
  • Manuel Mueller-Frank
  • Mallesh M Pai

Abstract

The classic wisdom-of-the-crowd problem asks how a principal can "aggregate" information about the unknown state of the world from agents without understanding the information structure among them. We propose a new simple procedure called Population-Mean-Based Aggregation to achieve this goal. The procedure only requires eliciting agents' beliefs about the state, and also eliciting some agents' expectations of the average belief in the population. We show that this procedure fully aggregates information: in an infinite population, it always infers the true state of the world. The procedure can accommodate correlations in agents' information, misspecified beliefs, any finite number of possible states of the world, and only requires very weak assumptions on the information structure.

Suggested Citation

  • Yi-Chun Chen & Manuel Mueller-Frank & Mallesh M Pai, 2021. "The Wisdom of the Crowd and Higher-Order Beliefs," Papers 2102.02666, arXiv.org, revised Nov 2021.
  • Handle: RePEc:arx:papers:2102.02666
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    References listed on IDEAS

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    Cited by:

    1. Dirk Bergemann & Marco Ottaviani, 2021. "Information Markets and Nonmarkets," Cowles Foundation Discussion Papers 2296, Cowles Foundation for Research in Economics, Yale University.

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