In a very broad class of dynamic linear models, if agents possess knowledge of current endogenous variables in a least-squares learning process, determinacy of a rational expectations (RE) equilibrium is sufficient but not necessary for learnability of that equilibrium. Thus, since learnability...

In a model of incomplete, heterogeneous information, with externalities and strategic interactions, we analyze the possibility for learning to act as coordination device. We build on the framework proposed by Angeletos and Pavan (2007) and extend it to a dynamic multiperiod setting where agents...

This paper develops a theory of expectations-driven business cycles based on learning. Agents have incomplete knowledge about how market prices are determined and shifts in expectations of future prices affect dynamics. In a real business cycle model, the theoretical framework amplifies and...

Bennett McCallum (2009), applying Evans and Honkapohja's (2001) results, argues that "learnability" can save New-Keynesian models from their indeterminacies. He claims the unique bounded equilibrium is learnable, and the explosive equilibria are not. However, he assumes that agents can directly...

We study a sequential experimentation model with endogenous feedback. Agents choose between a safe and risky action, the latter generating stochastic rewards. When making this choice, each agent is selfishly motivated (myopic). However, agents can disclose their experiences to a public record,...

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...

We provide semiparametric identification results for a broad class of learning models in which continuous outcomes depend on three types of unobservables: i) known heterogeneity, ii) initially unknown heterogeneity that may be revealed over time, and iii) transitory uncertainty. We consider a...

The FDA is responsible for the approval of new drugs, biological products and medical devices in the United States. As part of the approval process, the FDA relies on advisory committees, which provide independent advice from outside experts. We combine a structural approach with newly collected...

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....

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...