Level-$k$ Mechanism Design
研究了当代理人认为他人不如自己理性时，机制设计的必要条件与充分条件，发现与标准纳什均衡下的结果惊人相似，并提出了严格响应贝叶斯激励相容条件。
Models of choice where agents see others as less sophisticated than themselves have significantly different, sometimes more accurate, predictions in games than does Nash equilibrium. When it comes to mechanism design, however, they turn out to have surprisingly similar implications. This paper provides tight necessary and sufficient conditions for implementation with bounded depth of reasoning, discussing the role and implications of different behavioral anchors. The central condition slightly strenghthens standard incentive constraints, and we term it strict-if-responsive Bayesian incentive compatibility (SIRBIC).