We establish convergence of beliefs and actions in a class of one-dimensional learning settings in which the agent's model is misspecified, she chooses actions endogenously, and the actions affect how she misinterprets information. Our stochastic-approximation-based methods rely on two crucial...

We develop a model in which an overconfident agent learns about groups in society from observations of his and others' successes. In our model, both the agent's information and his beliefs are multi-dimensional, allowing us to study interactions between different views. Overall, society always...

We investigate experimentally whether social learners appreciate the redundancy of information conveyed by their observed predecessors' actions. Each participant observes a private signal and enters an estimate of the sum of all earlier-moving participants' signals plus her own. In a first...

We explore the learning process and behavior of an individual with unrealistically high expectations (“overconfidence”) when outcomes also depend on an external fundamental that affects the optimal action. Moving beyond existing results in the literature, we show that the agent's beliefs...

We establish convergence of beliefs and actions in a class of one-dimensional learning settings in which the agent’s model is misspecified, she chooses actions endogenously, and the actions affect how she misinterprets information. The crucial assumptions of our model are that the state and...

We investigate experimentally whether social learners appreciate the redundancy of information conveyed by the behavior of those they observe. Each experimental participant observes a private signal and enters an estimate of the sum of all earlier-moving participants' signals plus her own. In a...