We study a model of social learning in networks where agents have heterogeneous preferences, and neighbors tend to have similar preferences---a phenomenon known as homophily. Using this model, we resolve a puzzle in the literature: theoretical models predict that preference diversity helps...

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...

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...

Despite addressing similar underlying questions, the literatures on network formation and matching have evolved more or less independently. This paper offers a common framework, studying a general model of network formation without externalities---equivalently, a one-sided many-to-many matching...

Evidence suggests that individuals and firms are more innovative when subject to low-powered incentives. I offer an explanation based on a characteristic feature of creative work: hitting dead ends. An agent works on successive ideas, each of which may lead to a breakthrough with some...

In many allocation problems, transfers are unavailable, but incentives are partially aligned due to positive externalities. We study how a designer can exploit this alignment to allocate a resource between n agents. We identify a natural mechanism that partitions types into intervals and...

Regulators often impose rules that constrain the behavior of market participants. We propose a new framework in which to study optimal regulation, representing the policy choice as a delegation problem overlaying a mechanism design problem: a regulator chooses a set of permitted mechanisms to...

We often make high stakes choices based on complex information that we have no way to verify. Careful Bayesian reasoning---assessing every reason why a claim could be false or misleading---is not feasible, so we necessarily act on faith: we trust certain sources and treat claims as if they were...

Disagreement, including on matters of fact, is a pervasive phenomenon, yet this is incompatible with existing work on social learning. I propose a model of information processing with two key features: (i) the agent encounters false information, and (ii) the agent cannot distinguish true...

This survey covers models of how agents update behaviors and beliefs using information conveyed through social connections. We begin with sequential social learning models, in which each agent makes a decision once and for all after observing a subset of prior decisions; the discussion is...