Biased learning under ambiguous information

Jaden Yang Chen

Journal of Economic Theory, 2022, vol. 203, issue C

Abstract: This paper proposes a model of how biased individuals update beliefs in the presence of informational ambiguity. Individuals are ambiguous about the actual signal-generating process and interpret signals according to the model that can best support their biases. This paper provides a complete characterization of the limit beliefs under this rule. The presence of model ambiguity has the following effects. First, it destroys correct learning even if infinitely many informative signals can be observed. When the ambiguity is sufficiently high, individuals can justify their biases, leading to belief extremism and polarization. Second, an ambiguous individual can exhibit greater confidence than a Bayesian individual with any feasible model perception. This phenomenon comes from a novel complementary effect of different models in the belief set.

Keywords: Biased learning; Model uncertainty; Ambiguity; Self-serving bias (search for similar items in EconPapers)
JEL-codes: C72 D81 D83 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jetheo:v:203:y:2022:i:c:s0022053122000825

DOI: 10.1016/j.jet.2022.105492

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