即时接受与延迟接受的渐近等价性
Asymptotic Equivalence of Immediate and Deferred Acceptance
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中文总结 AI 辅助
研究即时接受（IA）与延迟接受（DA）在如实告知偏好时的情况，通过分析独立同分布一对一随机市场，发现IA预期平均排名渐近为log n，与DA相同，表明IA帕累托效率未转化为预期平均排名的一阶提升，结论适用于IA变体及多对一市场。
中文摘要 AI 辅助
即时接受（IA，也称为波士顿机制）常用于学生择校，若家长如实报告偏好，它能产生帕累托有效匹配，与学生提议的延迟接受（DA）不同。本文研究在如实告知条件下，IA的平均排名是否比DA显著更好。结果表明，在独立同分布的一对一随机市场中，IA的预期平均排名渐近为log n，与DA相同。所以IA的帕累托效率并未转化为预期平均排名的一阶提升，该结论也适用于IA的变体及多对一市场。
英文摘要
Immediate Acceptance (IA, also known as the Boston mechanism) is commonly used to assign students to schools because it produces a Pareto-efficient matching if parents report their preferences over schools truthfully, unlike student-proposing Deferred Acceptance (DA). In this paper, we ask: does IA produce meaningfully better average ranks than DA, conditional on truth-telling? We show that, in i.i.d. one-to-one random markets, IA's expected average rank is asymptotically $\log n$, just like DA's. Therefore, IA's Pareto efficiency does not translate into a first-order improvement in expected average rank. This conclusion extends to variations of IA as well as to many-to-one markets.
