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...

In this paper we study "investment tournaments," a class of decision problems that involve gradual allocation of investment among several alternatives whose values are subject to exogenous shocks. The decision-maker's payoff is determined by the final values of the alternatives. An important...

We survey work using Bayesian learning in macroeconomics, highlighting common themes and new directions. First, we present many of the common types of learning problems agents face---signal extraction problems---and trace out their effects on macro aggregates, in different strategic settings....

We study the perfect Bayesian equilibrium of a model of learning over a general social network. Each individual receives a signal about the underlying state of the world, observes the past actions of a stochastically-generated neighborhood of individuals, and chooses one of two possible actions....

Investor sophistication has lagged behind the growing complexity of retail financial markets. To explore this, we develop a dynamic model to study the interaction between obfuscation and investor sophistication. Taking into account different learning mechanisms within the investor population, we...

We study the problem of a policymaker who seeks to set policy optimally in an economy where the true economic structure is unobserved, and he optimally learns from observations of the economy. This is a classic problem of learning and control, variants of which have been studied in the past, but...

Decisions take time, and the time taken to reach a decision is likely to be informative about the cost of more precise judgments. We formalize this insight in the context of a dynamic rational inattention (RI) model. Under standard conditions on the flow cost of information in our discrete-time...

Revealed preference theory offers a criterion for decision-making quality: if decisions are high quality then there exists a utility function that the choices maximize. We conduct a large-scale field experiment that enables us to test subjects' choices for consistency with utility maximization...

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...

The DeGroot model has emerged as a credible alternative to the standard Bayesian model for studying learning on networks, offering a natural way to model naive learning in a complex setting. One unattractive aspect of this model is the assumption that the process starts with every node in the...