This paper studies how the outcome of Bayesian persuasion depends on the information available to Sender. I study a game in which Designer restricts the most informative signal Sender can generate. In the binary action case, I consider arbitrary preferences of Designer and characterize all...

We study a hierarchical Bayesian persuasion game with a sender, a receiver, and several potential intermediaries, generalizing the framework of Kamenica and Gentzkow (2011). The sender must be persuasive through a hierarchy of intermediaries to reach the final receiver, whose action affects all...

This paper introduces private sender information into a sender-receiver game of Bayesian persuasion with monotonic sender preferences. I derive properties of increasing differences related to the precision of signals and use these to fully characterize the set of equilibria robust to the...

This paper examines the phenomenon of management-initiated, court-supervised reorganization of companies in U.S. bankruptcy court. The proposed in-court persuasion mechanism reconciles excessive reorganizations of non-viable companies (and subsequent repeat failures) with management-initiated...

In a multi-sender Bayesian persuasion game, Gentzkow and Kamenica (2016) show that increasing the number of senders cannot decrease the amount of information revealed. They assume: (i) senders reveal information simultaneously, (ii) information can be arbitrarily correlated, and (iii) senders...

Drawing upon the Bayesian persuasion literature, I show that a mediator can provide conflicting parties strategically with information to decrease the ex-ante war probability. In a conflict between two parties with private information about military strength, the mediator generates information...

This paper studies sequential Bayesian persuasion games with multiple senders. We provide a tractable characterization of equilibrium outcomes. We apply the model to study how the structure of consultations affects information revelation. Adding a sender who moves first cannot reduce...

We study the general problem of Bayesian persuasion (optimal information design) with continuous actions and continuous state space in arbitrary dimensions. First, we show that with a finite signal space, the optimal information design is always given by a partition. Second, we take the limit of...

How should an agent (the sender) observing multi-dimensional data (the state vector) persuade another agent to take the desired action? We show that it is always optimal for the sender to perform a (non-linear) dimension reduction by projecting the state vector onto a lower-dimensional object...