The paper investigates social-learning when the information structure is not commonly known. Individuals repeatedly interact in social-learning settings with distinct information structures. In each round of interaction, they use their experience gained in past rounds to draw inferences from...

Experimental studies on decision making based on advice received from others find that the weight put on the advice is negatively related to the distance between the advice and the decisionmaker's initial opinion. In this paper, we show that the distance effect can follow from rational signal...

We consider a Bayesian decision problem in which an agent must draw inferences about multiple unobserved variables. This problem appears in different economic settings, for instance in the theory of agency. Assume that both observed and unobserved variables are ordered. We say that the inference...

We consider the following ’truth serum’ mechanism problem: Two players observe signals drawn from a common prior on n x m. They are risk neutral, care only about mechanism payoffs, and will not provide information without incentives. A counterexample shows that one cannot construct a robust...

We study perfect Bayesian equilibria of a sequential social learning model in which agents in a network learn about an underlying state by observing neighbors' choices. In contrast with prior work, we do not assume that the agents' sets of neighbors are mutually independent. We introduce a new...

In this paper we introduce a stochastic network formation model where agents choose both actions and links. Neighbors in the network benefit from each other's action levels through local complementarities and there exists a global interaction effect reflecting a strategic substitutability in...

Bayesian updating is the dominant theory of learning. However, the theory is silent about how individuals react to events that were previously unforeseeable or unforeseen. Building on a recently developed axiomatic framework to analyze such situations, we test if subjects update their beliefs...

The term "information risk" or "information uncertainty" is defined as the risk of a misleading signal. This risk is understood Bayesianly in terms of the likelihood function f(S|φ). In Bayesian method, f(S|φ) captures the quality of signal S with respect to parameter φ. The Bayesian position...

In recent years there has been a growing stream of literature in marketing and economics that models consumers as Bayesian learners. Such learning behavior is often embedded within a discrete choice framework which is then calibrated on scanner panel data. At the same time it is now accepted...

We develop methods to solve general equilibrium models in which forward-looking agents are subject to waves of pessimism, optimism, and uncertainty that turn out to critically affect macroeconomic outcomes. Agents in the model are fully rational, conduct Bayesian learning, and they know that...