Information Aggregation in Dynamic Markets with Adverse Selection (with William Fuchs and Brett Green)

Abstract:
How effectively does a decentralized marketplace aggregate information that is dispersed throughout the economy? We study this question in a dynamic setting, in which sellers have private information that is correlated with an unobservable aggregate state. We first characterize equilibria with an arbitrary (but finite) number of informed sellers. A common feature is that each seller’s trading behavior provides an informative and conditionally independent signal about the aggregate state. We then ask whether the state is revealed as the number of informed sellers goes to infinity. Perhaps surprisingly, the answer is no. We provide conditions under which the amount of information revealed is necessarily bounded and does not reveal the aggregate state. When these conditions are violated, there may be coexistence of equilibria that lead to full revelation with those that do not. Finally, the theory has implications for policies meant to enhance information dissemination in markets.