We develop models of markets with procrastinating consumers where competition operates - or is supposed to operate - both through the initial selection of providers and through the possibility of switching providers. As in other work, consumers fail to switch to better options after signing up...

We study the properties of a profit-maximizing monopolist's optimal price distribution when selling to a loss-averse consumer, where (following Köszegi and Rabin (2006)) we assume that the consumer's reference point is her recent rational expectations about the purchase. If it is close to...

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...

It is widely known that loss aversion leads individuals to dislike risk, and as has been argued by many researchers, in many instances this creates an incentive for firms to shield consumers and employees against economic risks. Complementing previous research, we show that consumer loss...

We model an agent who stubbornly underestimates how much his behavior is driven by undesirable motives, and, attributing his behavior to other considerations, updates his views about those considerations. We study general properties of the model, and then apply the framework to identify novel...

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 develop a model of digital ecosystems based on the assumption that a multimarket firm can use a sale in or data from one market to steer users toward its products in other markets. Due to this "cross-market leverage," a market leader at an "access point" (where users begin their online...