Managing Congestion in Matching Markets

Abstract

Participants in matching markets face search and screening costs which prevent the market from clearing efficiently. We study the magnitude of this inefficiency, and the effects of simple market interventions.

We consider a mean field limit of a stochastic, game theoretic, dynamic model in which “applicants” and “employers” pay costs to search and screen. Importantly, applicants may send applications that are never screened, and employers may screen applicants, only to learn that they have already matched. We prove existence and uniqueness of equilibrium, and characterize welfare for participants on both sides of the market. We also establish that equilibria of our model are approximate equilibria in large finite markets.

We provide two main insights. First, we identify that the welfare of market participants depends crucially on whether the market is *screening-limited* or *application-limited*. In screening-limited markets, application costs are low and there are enough employers that most applicants can match. In this case, employers screen many applicants who turn out to be unavailable, and screening costs fully offset the benefit of matching: employers’ expected welfare is zero, and some employers choose not to participate. In contrast, application-limited markets typically feature low screening costs and a shortage of employers. In such markets, applicants engage in wasteful competition, sending many applications that are never read. Our second contribution is to show that simple interventions – such as limiting the number of applications that an individual can send, or making it more costly to apply – can significantly improve the welfare of agents on one or both sides of the market.

Keywords: Matching, market design, mean field

JEL Classification: D40, J41