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....

We have seen in the past decade a sharp increase in the extent that companies use data to optimize their businesses. Variously called the `Big Data' or `Data Science' revolution, this has been characterized by massive amounts of data, including unstructured and nontraditional data like text and...

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...

We estimate a Bayesian learning model in order to assess the value of health plan performance information and the extent to which the explicit provision of information about product quality alters consumer behavior. We take advantage of a natural experiment in which health plan performance...

This paper introduces a new cost dataset for a commercial aircraft firm and uses this data to analyze the dynamics of learning in commercial aircraft production. This dataset is found to be inconsistent with the simple learning hypothesis, and particularly the prediction that a firm's unit cost...

The paper analyzes the impact of financial liberalizations and reforms in emerging markets on the dynamics of capital flows to these markets, using a simple model of international investors' behavior. We first show that the gradual nature of liberalizations, combined with the cost of absorbing...

We attempt to explain employment practices in internal labor markets using models that combine job assignment, on-the-job human-capital acquisition, and learning. We show that a framework that integrates these familiar ideas captures a number of recent empirical findings concerning wage and...

We provide a test for statistical discrimination or rational stereotyping in in environments in which agents learn over time. Our application is to the labor market. If profit maximizing firms have limited information about the general productivity of new workers, they may choose to use easily...