We develop a dynamic model of opinion formation in social networks. Relevant information is spread throughout the network in such a way that no agent has enough data to learn a payoff-relevant parameter. Individuals engage in communication with their neighbors in order to learn from their...

Better informed consumers may be treated preferentially by firms since their consumption serves as a quality signal for other customers. For normal goods this results in wealthy individuals being treated better than poor individuals. We investigate this phenomenon in an equilibrium model of...

We develop a model of social learning from complementary information: Short-lived agents sequentially choose from a large set of flexibly correlated information sources for prediction of an unknown state, and information is passed down across periods. Will the community collectively acquire the...

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...