Beliefs dynamics in communication networks

We study the dynamics of individual beliefs and information aggregation when agents communicate via a social network. We provide a general framework of social learning that captures the interactive effects of three main factors on the structure of individual beliefs resulting from such a dynamic process; that is historical factors—prior beliefs, learning mechanisms—rational and bounded rational learning, and the topology of communication structure governing information exchange. More specifically, we provide conditions under which heterogeneity and consensus prevail. We then establish conditions on the structures of the communication network, prior beliefs and private information for public beliefs to correctly aggregate decentralized information. The speed of learning is also established, but most importantly, its implications on efficient information aggregation.

Keywords: Learning, social networks, public beliefs, speed of learning, information aggregation.

JEL Classification: C70, D83, D85