Rank‐optimal assignments in uniform markets
证明了在代理人对物品独立随机排序的市场中，存在一个平均秩与市场规模无关的分配；并指出随机独裁机制的平均秩随市场增长而无限增大，而贝叶斯激励相容机制可实现最优平均秩。
We prove that in a market where agents rank objects independently and uniformly at random, there exists an assignment of objects to agents with a constant average rank (i.e., an average rank independent of the market size). The proof builds on techniques from random graph theory and the FKG inequality (Fortuin et al. (1971)). When the agents' rankings are their private information, no Dominant Strategy Incentive Compatible mechanism can implement the assignment with the smallest average rank; however, we show that there exists a Bayesian Incentive Compatible mechanism that does so. Together with the fact that the average rank under the Random Serial Dictatorship (RSD) mechanism grows infinitely large with the market size, our findings indicate that the average rank under RSD can take a heavy toll compared to the first‐best, and highlight the possibility of using other assignment methods in scenarios where average rank is a relevant objective.