We compare how well agents aggregate information in two repeated social learning environments. In the first setting agents have access to a public data set. In the second they have access to the same data, and also to the past actions of others. Despite the fact that actions contain no...

Most economic analyses presume that there are limited differences in the prior beliefs of individuals, as assumption most often justified by the argument that sufficient common experiences and observations will eliminate disagreements. We investigate this claim using a simple model of Bayesian...

We propose a new measure of the cost of information structures in rational inattention problems, the "neighborhood-based" cost functions, given that many applications involve states with a topological structure. These cost functions summarize the results of a sequential information sampling...

The literature exploring other regarding behavior sheds important light on interesting social phenomena, yet less attention has been given to how the received results speak to foundational assumptions within economics. Our study synthesizes the empirical evidence, showing that recent work...

Discretionary policymaking can foster strategic complementarities between private sector decisions, thus leading to multiple equilibria. This article studies a simple example, originating with Kydland and Prescott, of a government which must decide whether to build a dam to prevent adverse...

Social distancing via shelter-in-place strategies, and wearing masks, have emerged as the most effective non-pharmaceutical ways of combatting COVID-19. In the United States, choices about these policies are made by individual states. We develop a game-theoretic model and then test it...

A vibrant literature has emerged that suggests willingness to pay and willingness to accept measures of value are quite different for inexperienced consumers but that value differences erode with market experience. One potential shortcoming of this literature is that market experience is...

Existing learning models attribute failures to learn to a lack of data. We model a different barrier. Given the large number of dimensions one could focus on when using a technology, people may fail to learn because they failed to notice important features of the data they possess. We conduct a...

The central question we address in this paper is: what can an analyst infer from choice data about what a decision maker has learned? The key constraint we impose, which is shared across models of Bayesian learning, is that any learning must be rationalizable. To implement this constraint, we...

The experimental literature on repeated games has largely focused on settings where players discount the future identically. In applications, however, interactions often occur between players whose time preferences differ. We study experimentally the effects of discounting differentials in...