Mean-preserving contractions are critical for studying Bayesian models of information design. We introduce the class of bi-pooling policies, and the class of bi-pooling distributions as their induced distributions over posteriors. We show that every extreme point in the set of all...

The canonical Bayesian persuasion setting studies a model where an informed agent, the Sender, can partially share his information with an uninformed agent, the Receiver. The Receiver's utility is a function of the state of nature and the Receiver's action while the Sender's is only a function...

New ways of doing things often get started through the actions of a few innovators, then diffuse rapidly as more and more people come into contact with prior adopters in their social network. Much of the literature focuses on the speed of diffusion as a function of the network topology. In...

We consider a multi-receiver Bayesian persuasion problem where an informed sender tries to persuade a group of receivers to adopt a certain product. The sender is allowed to commit to a signaling policy where she sends a private signal to every receiver. The utility of the sender is a function...

We analyze boundedly rational updating from aggregate statistics in a modelwith binary actions and binary states. Agents each take an irreversible action in sequence after observing the unordered set of previous actions. Each agent first forms her prior based on the aggregate statistic, then...

We analyze boundedly rational updating in a repeated interaction network model with binary actions and binary states. Agents form beliefs according to discretized DeGroot updating and apply a decision rule that assigns a (mixed) action to each belief. We first show that under weak assumptions...

We study a canonical setting of learning in networks where initially agents receive conditionally i.i.d. signals about a binary state. The distribution according to which signals are drawn is called an information structure. Agents repeatedly communicate beliefs with their neighbors and update...