The Attention Cost of Stable Matching

2026-09-09

AI Summary

研究解决大市场中注意力稀缺导致的匹配问题，通过有限注意力延迟接受方法提高匹配效率和质量。

Abstract

In large markets, scarce attention limits partner evaluation and creates allocation loss, which stability magnifies. In an independent random market with average executable degree $d$, unmatched shares fall at rates $e^{-\sqrt d}$ under stability and $e^{-d}$ under maximum matching on the same graph. Changing consideration can make applications rejected in a provisional active-screen computation relevant again. Exact query-neutral implementation must retain allocation-relevant off-screen authorizations; otherwise, missing authorization must be reacquired. Limited-attention deferred acceptance (LA-DA) preserves valid authorizations and reengages eligible pairs. Conditional on exact next-best information and persistent execution rights, adaptive discovery saves a logarithmic factor in reached proposals relative to independent exposure. In an application to speed dating, bilateral reports let us compare stable and maximum matching on restricted graphs, separating missed opportunities from same-graph stability loss. In Chilean school choice, we document 9,502 applicants accepting higher-ranked or new placements through retained rankings.

Problem

• attention scarcity
• partner evaluation
• allocation loss
• stability

Innovation

• Limited-Attention Deferred Acceptance (LA-DA)
• Adaptive Discovery
• Stable Matching
• Maximum Matching