Multiagent Mechanism Design Without Money

• 成果类型: Article
• 署名作者: Balseiro, Santiago R.; Gurkan, Huseyin; Sun, Peng
• 署名单位: Columbia University; Duke University
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.2018.1820
• 发表日期: 2019
• 页码: 1417-1436
• 关键词: adverse selection model; allocation

摘要

We consider a principal repeatedly allocating a single resource in each period to one of multiple agents, whose values are private, without relying on monetary payments over an infinite horizon with discounting. We design a dynamic mechanism that induces agents to report their values truthfully in each period via promises/threats of future favorable/unfavorable allocations. We show that our mechanism asymptotically achieves the first-best efficient allocation (the welfare-maximizing allocation as if values are public) as agents become more patient and provide sharp characterizations of convergence rates to first best as a function of the discount factor. In particular, in the case of two agents we prove that the convergence rate of our mechanism is optimal-that is, no other mechanism can converge faster to first best.