Learning Dynamics in Social Networks

This paper proposes a tractable model of Bayesian learning on large random networks where agents choose whether to adopt an innovation. We study the impact network structure dynamics and product diffusion. In directed networks, all direct indirect links contribute agents' learning. comparison, welfare are lower in undirected with cliques. rich class behavior is described by small number differential equations, making useful for empirical work.