Game Theoretic Consequences of Resident Matching

TL;DR

This paper examines the implications of the longstanding Gale-Shapley resident matching algorithm amid evolving applicant and program dynamics, highlighting increased costs and strategic behaviors in the matching process.

Contribution

It provides a game-theoretic analysis of the resident matching process, revealing how current algorithms influence applicant and program strategies amidst changing market conditions.

Findings

Increased application and interview costs for applicants and programs.

Strategic behaviors emerge due to the algorithm's structure and market shifts.

Potential for algorithmic modifications to reduce costs and strategic gaming.

Abstract

The resident matching algorithm, Gale-Shapley, currently used by SF Match and the National Residency Match Program (NRMP), has been in use for over 50 years without fundamental alteration. The algorithm is a 'stable-marriage' method that favors applicant outcomes. However, in these 50 years, there has been a big shift in the supply and demand of applicants and programs. These changes along with the way the Match is implemented have induced a costly race among applicants to apply and interview at as many programs as possible. Meanwhile programs also incur high costs as they maximize their probability of matching by interviewing as many candidates as possible.