发表机构
University of Toronto; University of Cologne; Northwestern University（多伦多大学; 科隆大学; 西北大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文研究异质性环境中的优先定价设计，证明在经济自然条件下，三个优先层级（付费高质量、补偿低质量、基准中间层）即可在平等分配基准上实现帕累托改进，而两个层级不足，为克服公平-效率权衡提供框架。
AI 中文摘要
我们研究了在异质性代理环境中优先定价系统的设计问题，在该环境中，为某些代理提高质量会降低可提供的平均质量。与公共辩论中强调的公平-效率权衡相反，我们表明，在经济自然条件下，优先定价可以在平等分配基准上实现帕累托改进。三个优先层级足以实现这种改进，即结合付费获得更高质量、补偿获得较低质量以及处于基准质量的中间层级；两个层级永远不够。我们的结果为克服车道定价、排队设计、公共供给和保险等应用中的公平-效率紧张关系提供了一个框架。
英文摘要
We study the design of priority pricing systems with heterogeneous agents in environments in which improving quality for some agents reduces the average quality that can be provided. Contrary to the equity-efficiency tradeoff emphasized in public debates, we show that under economically natural conditions priority pricing can Pareto-improve on an equal-allocation benchmark. Three priority tiers suffice for such an improvement, combining higher quality for a fee, lower quality with compensation, and an intermediate tier at the benchmark quality; two tiers are never enough. Our results provide a framework for overcoming equity-efficiency tensions in applications such as lane pricing, waiting-line design, public provision, and insurance.
