Thickness and Information in Dynamic Matching Markets
成果类型：
Article
署名作者：
Akbarpour, Mohammad; Li, Shengwu; Gharan, Shayan Oveis
署名单位：
Stanford University; Harvard University; University of Washington; University of Washington Seattle
刊物名称：
JOURNAL OF POLITICAL ECONOMY
ISSN/ISSBN：
0022-3808
DOI：
10.1086/704761
发表日期：
2020
页码：
783-815
关键词：
摘要：
We introduce a simple model of dynamic matching in networked markets, where agents arrive and depart stochastically and the composition of the trade network depends endogenously on the matching algorithm. If the planner can identify agents who are about to depart, then waiting to thicken the market substantially reduces the fraction of unmatched agents. If not, then matching agents greedily is close to optimal. We specify conditions under which local algorithms that choose the right time to match agents, but do not exploit the global network structure, are close to optimal. Finally, we consider a setting where agents have private information about their departure times and design a mechanism to elicit this information.