Non-Bayesian Learning in Misspecified Models

Sebastian Bervoets, Mathieu Faure and Ludovic Renou

No 20114, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: Deviations from Bayesian updating are traditionally categorized as biases, errors, or fallacies, thus implying their inherent ``sub-optimality.'' We offer a more nuanced view. We demonstrate that, in learning problems with misspecified models, non-Bayesian updating can outperform Bayesian updating.

Keywords: Learning (search for similar items in EconPapers)
JEL-codes: C72 D83 (search for similar items in EconPapers)
Date: 2025-04
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