Incentives and Stability in Large Two-Sided Matching Markets

A number of labor markets and student placement systems can be modeled as many-to-one matching markets. We analyze the scope for manipulation in many-to-one matching markets under the student-optimal stable mechanism when the number of participants is large. Under some regularity conditions, we show that the fraction of participants that have incentives to misrepresent their preferences when others are truthful approaches zero as the market becomes large. With an additional technical condition, truthful reporting by every participant is an approximate equilibrium under the student-optimal stable mechanism in large markets. The results help explain the success of the student-optimal stable mechanism in large matching markets observed in practice.