How to Use Prices for Efficient Online Matching
Terence Highsmith

TL;DR
This paper introduces the Sequential Equilibrium Mechanism (SEM), an online matching algorithm that efficiently, fairly, and strategy-proofly matches agents to objects in dynamic markets, with promising real-world applications.
Contribution
The paper presents SEM, a novel online matching algorithm that approximates market equilibria and is asymptotically efficient, fair, and strategy-proof, with plans for real-world deployment.
Findings
SEM is asymptotically efficient, fair, and strategy-proof.
Simulation evidence shows SEM can significantly improve welfare.
A lab-in-the-field experiment is planned for real-world testing.
Abstract
Many matching markets feature unknown, dynamic arrivals of agents that must match immediately. A caseworker must match an abused child to a foster home, a hospital must assign a patient in critical condition to a room, or a city must place a homeless individual into a shelter. We design an online matching algorithm -- the Sequential Equilibrium Mechanism (SEM) -- that approximates large market equilibria to match arriving agents to objects. SEM is asymptotically efficient, fair, and strategy-proof with probability one. Our application plans to deploy a lab-in-the-field experiment where real caseworkers match vulnerable children to host homes, and we provide simulation evidence that SEM can substantially improve welfare.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
