On the Distributional Robustness of Finite Rational Inattention Models

Emerson Melo

Papers from arXiv.org

Abstract: In this paper we study a rational inattention model in environments where the decision maker faces uncertainty about the true prior distribution over states. The decision maker seeks to select a stochastic choice rule over a finite set of alternatives that is robust to prior ambiguity. We fully characterize the distributional robustness of the rational inattention model in terms of a tractable concave program. We establish necessary and sufficient conditions to construct robust consideration sets. Finally, we quantify the impact of prior uncertainty, by introducing the notion of \emph{Worst-Case Sensitivity}.

Date: 2022-08, Revised 2023-05
New Economics Papers: this item is included in nep-mic and nep-upt
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