北大经院工作坊第1078场
Incentive Compatibility and Belief Restrictions
微观理论经济学工作坊
主讲人：Mariann Ollár（Assistant Professor of Economics at NYU Shanghai）
主持老师：
（北大经院）吴泽南、石凡奇
（北大国发院）胡岠
参与老师：
（北大经院）胡涛
（北大国发院）汪浩、邢亦青
（北大光华）翁翕、刘烁
时间：2025年4月17日（周四）10:30-12:00
地点：8455新葡萄娱乐场特色302会议室
主讲人简介：
Mariann Ollár is an Assistant Professor of Economics at NYU Shanghai. She received her PhD from the University of Wisconsin, Madison. Mariann works on Mechanism Design and Market Design, and her research has been published in the American Economic Review and the Review of Economic Studies. Her ongoing research covers topics that relate to externalities, moment conditions in economic design, information aggregation, information design in exchanges, uniform price market clearing, and game theoretic solution concepts such as rationalizability under various assumptions on beliefs.
摘要：
We study a framework for robust mechanism design that can accommodate various degrees of robustness with respect to agents’ beliefs, which encompasses both the belief-free and Bayesian settings as special cases. For general belief restrictions, we characterize the set of incentive compatible direct mechanisms in general environments with interdependent values. Our main results, which we obtain based on a first-order approach, inform the design of transfers via ‘belief-based’ terms to attain incentive compatibility. In environments that satisfy a property of generalized independence, our results imply a robust version of revenue equivalence in non-Bayesian settings. Instead, under a notion of comovement between types and beliefs, which extends the idea of correlated information to non-Bayesian settings, we show that any allocation rule can be implemented, even if standard single-crossing and monotonicity conditions do not hold. Yet, unless the environment is Bayesian, information rents typically remain, and they decrease monotonically as the robustness requirements are weakened.
供稿：科研与博士后办公室
美编：闻听
责编：度量、雨禾、雨田
