We analyze the optimal design of dynamic mechanisms in the absence of transfers. The designer uses future allocation decisions to elicit private information. Values evolve according to a two-state Markov chain. We solve for the optimal allocation rule, which permits a simple implementation....

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...

These notes examine the problem of how to extend envelope theorems to infinite-horizon dynamic mechanism design settings, with an application to the design of "bandit auctions." -- Asymmetric information ; stochastic processes ; incentives ; mechanism design

We analyze the optimal design of dynamic mechanisms in the absence of transfers. The designer uses future allocation decisions to elicit private information. Values evolve according to a two-state Markov chain. We solve for the optimal allocation rule, which permits a simple implementation....

Dynamic mechanisms offer powerful techniques to improve on both revenue and efficiency by linking sequential auctions using state information, but these techniques rely on exact distributional information of the buyers' valuations (present and future), which limits their use in learning...

We design a non-clairvoyant dynamic mechanism under budget and ex-post individual rationality constraints that is dynamic incentive-compatible and achieves non-trivial revenue performance, even without any knowledge about the future. In particular, our dynamic mechanism obtains a constant...

We introduce a new family of dynamic mechanisms that restricts sellers from using future distributional knowledge. Since the allocation and pricing of each auction period do not depend on the type distributions of future periods, we call this family of dynamic mechanisms non-clairvoyant.We...

Short-lived buyers arrive to a platform over time and randomly match with sellers. The sellers stay at the platform and sequentially decide whether to accept incoming requests. The platform designs what buyer information the sellers observe before deciding to form a match. We show full...

Dynamic mechanisms are a powerful technique in designing revenue-maximizing repeated auctions. Despite their strength, these types of mechanisms have not been widely adopted in practice for several reasons, e.g., for their complexity, and for their sensitivity to the accuracy of predicting...