Thickness and Information in Dynamic Matching Markets

57 Pages Posted: 15 Feb 2014 Last revised: 5 May 2017

Mohammad Akbarpour

Stanford Graduate School of Business

Shengwu Li

Stanford University - Department of Economics

Shayan Oveis Gharan

University of California, Berkeley

Date Written: April 1, 2017

Abstract

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. We show that if the planner can identify agents who are about to depart, then waiting to thicken the market is highly valuable, and if the planner cannot identify such agents, then matching agents greedily is close to optimal. The planner’s decision problem in our model involves a combinatorially complex state space. However, we show that simple local algorithms that choose the right time to match agents, but do not exploit the global network structure, can perform close to complex optimal algorithms. Finally, we consider a setting where agents have private information about their departure times, and design a continuous-time dynamic mechanism to elicit this information.

Keywords: Market Design, Matching, Networks, Continuous-time Markov Chains, Mechanism Design

JEL Classification: D47, C78, C60

Suggested Citation

Akbarpour, Mohammad and Li, Shengwu and Oveis Gharan, Shayan, Thickness and Information in Dynamic Matching Markets (April 1, 2017). Available at SSRN: https://ssrn.com/abstract=2394319 or http://dx.doi.org/10.2139/ssrn.2394319

Mohammad Akbarpour (Contact Author)

Stanford Graduate School of Business ( email )

Shengwu Li

Stanford University - Department of Economics ( email )

Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States

HOME PAGE: http://www.stanford.edu/~shengwu/

Shayan Oveis Gharan

University of California, Berkeley ( email )

Berkeley, CA
United States

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