Abstract
We characterize the incentive compatible, constrained efficient policy ("second-best") in a dynamic matching environment, where impatient, privately informed agents arrive over time, and where the designer gradually learns about the distribution of agents' values. We also derive conditions on the learning process ensuring that the complete-information, dynamically efficient allocation of resources ("first-best") is incentive compatible. Our analysis reveals and exploits close, formal relations between the problem of ensuring implementable allocation rules in our dynamic allocation problems with incomplete information and learning, and between the classical problem, posed by Rothschild (1974) [20], of finding optimal stopping policies for search that are characterized by a reservation price property.
| Original language | English |
|---|---|
| Pages (from-to) | 881-909 |
| Number of pages | 29 |
| Journal | Journal of Economic Theory |
| Volume | 147 |
| Issue number | 3 |
| DOIs | |
| State | Published - May 2012 |
Bibliographical note
Funding Information:The comments of an associate editor and an anonymous referee greatly improved the quality of the exposition. We wish to thank Sergiu Hart, Philippe Jehiel, Alessandro Pavan, Xianwen Shi, Phil Reny and Asher Wolinsky for helpful remarks. Participants at the workshop “Information and Dynamic Mechanism Design” June 2009, Bonn, made very fruitful comments. We are grateful to the German Science Foundation and to the European Research Council for financial support.
Keywords
- Dynamic mechanism design
- Learning
- Optimal stopping