Learning with Heterogeneous Misspecified Models: Characterization and Robustness

Published: Jan 1, 2021
Abstract
This paper develops a general framework to study how misinterpreting information impacts learning. Our main result is a simple criterion to characterize long-run beliefs based on the underlying form of misspecification. We present this characterization in the context of social learning, then highlight how it applies to other learning environments, including individual learning. A key contribution is that our characterization applies to settings...
Paper Details
Title
Learning with Heterogeneous Misspecified Models: Characterization and Robustness
Published Date
Jan 1, 2021
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