We examine the design of incentive-compatible screening mechanisms for dynamic environments in which the agents' types follow a (possibly non-Markov) stochastic process, decisions may be made over time and may affect the type process, and payoffs need not be time-separable. We derive a formula...

We examine the design of incentive-compatible screening mechanisms for dynamic environments in which the agents' types follow a (possibly non-Markov) stochastic process, decisions may be made over time and may affect the type process, and payoffs need not be time-separable. We derive a formula...

I study the properties of optimal long-term contracts in an environment in which the agent's type evolves stochastically over time. The model stylizes a buyer-seller relationship but the results apply quite naturally to many contractual situations including regulation and optimal...

We study centralized many-to-many matching in markets where agents have private information about (vertical) characteristics that determine match values. Our analysis reveals how matching patterns reflect cross-subsidization between sides. Agents are endogenously partitioned into consumers and...

We study centralized many-to-many matching in markets where agents have private information about (vertical) characteristics that determine match values. Our analysis reveals how matching patterns reflect cross-subsidization between sides. Agents are endogenously partitioned into consumers and...

We characterize the optimal incentive scheme for a manager who faces costly effort decisions and whose ability to generate profits for the firm varies stochastically over time. The optimal contract is obtained as the solution to a dynamic mechanism design problem with hidden actions and...