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Differences of Opinion

This paper studies an agent forming beliefs by translating data into signals about the truth of propositions. The agent faces ambiguity when she observes low-quality data yielding set-identified signals. Rules for decision-making under ambiguity choose the single belief generating an extreme utility. Separating belief formation from decision-making, I suppose the agent’s objective is to choose the single belief replicating what would occur with high-quality data yielding point-identified signals. I allow the agent to solve this missing data problem using signals observed through her network in combination with a model of social learning. In some cases the agent’s belief formation reduces to DeGroot updating, but in other cases her updating can generate polarization and permanent disagreement, even on a connected network.