Person:

Ishii, Yuhta

This dissertation presents three independent essays. Chapter 1, which is joint work with Mira Frick, studies a model of innovation adoption by a large population of long-lived consumers who face stochastic opportunities to adopt an innovation of uncertain quality. We study how the potential for social learning in an economy affects consumers' informational incentives and how these in turn shape the aggregate adoption dynamics of an innovation. For a class of Poisson learning processes, we establish the existence and uniqueness of equilibria. In line with empirical findings, equilibrium adoption patterns are either S-shaped or feature successions of concave bursts. In the former case, our analysis predicts a novel saturation effect: Due to informational free-riding, increased opportunities for social learning necessarily lead to temporary slow-downs in learning and do not produce welfare gains.

We extend the folk theorem of repeated games to two settings in which players' information about others' play arrives with stochastic lags. In our first model, signals are almost-perfect if and when they do arrive, that is, each player either observes an almost-perfect signal of period-t play with some lag or else never sees a signal of period-t play. The second model has the same lag structure, but the information structure corresponds to a lagged form of imperfect public monitoring, and players are allowed to communicate via cheap-talk messages at the end of each period. In each case, we construct equilibria in “delayed-response strategies,” which ensure that players wait long enough to respond to signals that with high probability all relevant signals are received before players respond. To do so, we extend past work on private monitoring to obtain folk theorems despite the small residual amount of private information.