We study the role of information structures in mechanism design problems with limited commitment. In each period, a principal offers a ''spot'' contract to a privately informed agent without committing to future spot contracts, and the agent responds to the contract. In contrast to the classical approach in which the information structure is fixed, we allow for all admissible information structures. We represent the information structure as a fictitious mediator and re-interpret the model as a mechanism design problem by the mediator with commitment. The mediator collects the agent's private information and then, in each period, privately recommends the principal's spot contract and the agent's response in an incentive-compatible manner (both in truth-telling and obedience). We construct several examples to clarify why new equilibrium outcomes can arise once we allow for general information structures. We next develop a durable-good monopoly application. We show that trading outcomes and welfare consequences can substantially differ from those in the classical model with a fixed information structure. In the seller-optimal mechanism, the seller offers a discounted price to the high-valuation buyer only in the initial period, followed by the high, surplus-extracting price until some endogenous deadline, when the buyer's information is revealed and hence fully extracted. As a result, the Coase conjecture fails: even in the limiting case of perfect patience, the seller makes a positive surplus, and the trading outcome is not the first best. We also characterize mediated and unmediated implementation of the seller-optimal outcome.

We study information design in games with a continuum of actions such that the payoff of each player is concave in his action. A designer chooses an information structure--a joint distribution of a state and a private signal of each player. The information structure induces a Bayesian game and is evaluated according to the expected designer's payoff under the equilibrium play.

The canonical Bayesian persuasion setting studies a model where an informed agent, the Sender, can partially share his information with an uninformed agent, the Receiver. The Receiver's utility is a function of the state of nature and the Receiver's action while the Sender's is only a function of the Receiver's action. The classical results characterize the Sender's optimal information disclosure policy whenever the state space is finite. In this paper we study the same setting where the state space is an interval on the real line. We introduce the class of bi-pooling policies and the induced distribution over posteriors which we refer to as bi-pooling distributions. We show that this class of distributions characterizes the set of optimal distributions in the aforementioned setting. Every persuasion problem admits an optimal bi-pooling distribution as a solution. Conversely, for every bi-pooling distribution there exists a persuasion problem in which the given distribution is the unique optimal one. We leverage this result to study the structure of the price function (see [1]) in this setting and to identify optimal information disclosure policies. The full paper can be accessed at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3511516.