How to Use Prices for Efficient Online Matching

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.