We study robust welfare comparisons of learning biases (misspecified Bayesian and some
forms of non-Bayesian updating). Given a true signal distribution, we deem one bias more …

Toward explaining the persistence of biased inferences, we propose a framework to
evaluate competing (mis) specifications in strategic settings. Agents with heterogeneous …

We study how misperceptions of others' tastes influence beliefs, demand, and prices in
markets with observational learning. Consumers infer a good's quality from the quantity …

I study endogenous learning dynamics for people who misperceive intertemporal
correlations in random sequences. Biased agents face an optimal‐stopping problem. They …

We consider an agent who posits a set of probabilistic models for the payoff-relevant
outcomes. The agent has a prior over this set but fears the actual model is omitted and …

We discuss models of updating that depart from Bayes' rule even when it is well-defined.
After reviewing Bayes' rule and its foundations, we begin our analysis with models of non …

This paper studies the forms of model misspecification that are more likely to persist when
an agent compares her subjective model with competing models. The agent learns about an …

This paper studies the long-term interaction between two overconfident agents who choose
how much effort to exert while learning about their environment. Overconfidence causes …

Individuals use models to guide decisions, but many models are wrong. This paper studies
which misspecified models are likely to persist when individuals also entertain alternative …

In a misspecified social learning setting, agents are condescending if they perceive their
peers as having private information that is of lower quality than it is in reality. Applying this to …