Inertial Updating with General Information

Adam Dominiak, Matthew Kovach and Gerelt Tserenjigmid

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Abstract: We study belief revision when information is represented by a set of probability distributions, or general information. General information extends the standard event notion while including qualitative information (A is more likely than B), interval information (A has a ten-to-twenty percent chance), and more. We behaviorally characterize Inertial Updating: the decision maker's posterior is of minimal subjective distance from her prior, given the information constraint. Further, we introduce and characterize a notion of Bayesian updating for general information and show that Bayesian agents may disagree. We also behaviorally characterize f-divergences, the class of distances consistent with Bayesian updating.

Date: 2025-02
New Economics Papers: this item is included in nep-des and nep-mic
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