Kailin Chen (BGSE) 21.12.2022

This paper studies learning from multiple informed agents where each agent has a small piece of information about the unknown state of the world in the form of a noisy signal and sends a message to the principal, who then makes a decision that is not constrained by predetermined rules. In contrast to the existing literature, I model the conflict of interest between the principal and the agents more generally and consider the case where the preferences of the principal and the agents are misaligned in some realized states. I show that if the conflict of interest between the principal and the agents is moderate, there is a discontinuity: when the number of agents is large enough, adding even a tiny probability of misaligned states leads to complete unraveling in which the agents ignore their signals, in contrast to the almost complete revealing that is predicted by the existing literature. [...]