Dynamic Matching Under Patience Imbalance

TL;DR

This paper analyzes a dynamic two-sided matching platform with unbalanced patience levels, comparing centralized optimal policies and decentralized equilibria, and explores how patience affects social welfare under different system configurations.

Contribution

It characterizes the optimal centralized policy, the decentralized equilibrium, and compares social welfare across different patience and backlog scenarios.

Findings

Optimal centralized policy follows a threshold-based rationing rule.

Decentralized equilibrium can match low-type demand with high-type supply, differing from centralized outcomes.

Social welfare in decentralized systems depends on payoff allocation, patience, and backlog levels.

Abstract

We study a dynamic matching problem on a two-sided platform with unbalanced patience, in which long-lived supply accumulates over time with a unit waiting cost per period, while short-lived demand departs if not matched promptly. High- or low-quality agents arrive sequentially with one supply agent and one demand agent arriving in each period, and matching payoffs are supermodular. In the centralized benchmark, the optimal policy follows a threshold-based rule that rations high-quality supply, preserving it for future high-quality demand. In the decentralized system, where self-interested agents decide whether to match under an exogenously specified payoff allocation proportion, we characterize a welfare-maximizing Markov perfect equilibrium. Unlike outcomes in the centralized benchmark or in full-backlog markets, the equilibrium exhibits distinct matching patterns in which low-type demand may match with high-type supply even when low-type supply is available. Unlike settings in which both sides have long-lived agents and perfect coordination is impossible, the decentralized system can always be perfectly aligned with the centralized optimum by appropriately adjusting the allocation of matching payoffs across agents on both sides. Finally, when the arrival probabilities for H- and L-type arrivals are identical on both sides, we compare social welfare across systems with different patience levels: full backlog on both sides, one-sided backlog, and no backlog. In the centralized setting, social welfare is weakly ordered across systems. However, in the decentralized setting, the social welfare ranking across the three systems depends on the matching payoff allocation rule and the unit waiting cost, and enabling patience can either increase or decrease social welfare.