The Walras-Bowley Lecture: Fragmentation of Matching Markets and How Economics Can Help Integrate Them

2025-08-27

AI Summary

This paper addresses efficiency losses arising from market fragmentation in matching markets, using Japan’s daycare allocation system as an empirical setting to examine how inter-regional student mobility affects child welfare and matching efficiency. Methodologically, it proposes a partial integration mechanism under “balance constraints,” designed for settings where full integration is infeasible. The approach estimates students’ utility functions and conducts counterfactual simulations across multiple integration scenarios. Results show that the proposed mechanism recovers 39.2%–59.6% of the welfare gains achievable under full integration—equivalent to a 3.3%–4.9% reduction in average commuting time and a 40.0%–52.8% decline in unmatched applicants. The study contributes a theoretically grounded, policy-relevant framework for the gradual integration of fragmented public service markets, offering both analytical rigor and practical implementation pathways.

Technology Category

• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Mechanism Design
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Economics, Online Markets and Human Computation: The sharing economy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

Fragmentation of matching markets is a ubiquitous problem across countries and across applications. In order to study the implications of fragmentation and possibilities for integration, we first document and discuss a variety of fragmentation cases in practice such as school choice, medical residency matching, and so forth. Using the real-life dataset of daycare matching markets in Japan, we then empirically evaluate the impact of interregional transfer of students by estimating student utility functions under a variety of specifications and then using them for counterfactual simulation. Our simulation compares a fully integrated market and a partially integrated one with a ``balancedness'' constraint -- for each region, the inflow of students from the other regions must be equal to the outflow to the other areas. We find that partial integration achieves 39.2 to 59.6% of the increase in the child welfare that can be attained under full integration, which is equivalent to a 3.3 to 4.9% reduction of travel time. The percentage decrease in the unmatch rate is 40.0 to 52.8% under partial integration compared to the case of full integration. The results suggest that even in environments where full integration is not a realistic option, partial integration, i.e., integration that respects the balancedness constraint, has a potential to recover a nontrivial portion of the loss from fragmentation.

Problem

• Studying fragmentation in matching markets across various applications
• Empirically evaluating integration impact using daycare matching data
• Comparing full and partial integration effects on child welfare

Innovation

• Estimating student utility functions using real-life data
• Simulating counterfactual scenarios with balancedness constraints
• Comparing partial and full integration impacts empirically