Herd Design

Abstract

The classical herding model examines the asymptotic behavior of agents who observe their predecessors' actions as well as a private signal from an exogenous information structure. In this paper, we introduce a self-interested sender into the model and study her problem of designing this information structure. If agents cannot observe each other the model reduces to the Bayesian persuasion framework. However, when the agents do observe predecessors' actions, they may learn from each other, possibly lowering the sender's utility. We identify necessary and sufficient conditions under which the sender can nevertheless obtain the same utility as when the agents are unable to observe each other.

Keywords: Bayesian Persuasion, Herding