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Beyond Unbounded Beliefs: How Preferences and Information Interplay in Social Learning

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  • Navin Kartik
  • SangMok Lee
  • Tianhao Liu
  • Daniel Rappoport

Abstract

When does society eventually learn the truth, or take the correct action, via observational learning? In a general model of sequential learning over social networks, we identify a simple condition for learning dubbed excludability. Excludability is a joint property of agents' preferences and their information. We develop two classes of preferences and information that jointly satisfy excludability: (i) for a one‐dimensional state, preferences with single‐crossing differences and a new informational condition, directionally unbounded beliefs; and (ii) for a multi‐dimensional state, intermediate preferences and subexponential location‐shift information. These applications exemplify that with multiple states, “unbounded beliefs” is not only unnecessary for learning, but incompatible with familiar informational structures like normal information. Unbounded beliefs demands that a single agent can identify the correct action. Excludability, on the other hand, only requires that a single agent must be able to displace any wrong action, even if she cannot take the correct action.

Suggested Citation

  • Navin Kartik & SangMok Lee & Tianhao Liu & Daniel Rappoport, 2024. "Beyond Unbounded Beliefs: How Preferences and Information Interplay in Social Learning," Econometrica, Econometric Society, vol. 92(4), pages 1033-1062, July.
  • Handle: RePEc:wly:emetrp:v:92:y:2024:i:4:p:1033-1062
    DOI: 10.3982/ECTA21470
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    References listed on IDEAS

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