We theoretically study how social information affects agents' search behavior and the resulting observable outcomes that identify search models. We generalize canonical empirical search models by allowing a share of agents in the population to observe some peers' choices. Social information...

I study social learning in networks with information acquisition and choice. Bayesian agents act in sequence, observe the choices of their connections, and acquire information via sequential search. Complete learning occurs if search costs are not bounded away from zero and the network is...

We develop a method to estimate a game’s primitives in complex dynamic environments. Because of the environment’s complexity, agents may not know or understand some key features of their interaction. Instead of equilibrium assumptions, we impose an asymptotic ε-regret (ε-AR) condition on...