北大经院工作坊第1032场
微观理论经济学工作坊
主讲人：
Jiangtao Li（Associate Professor, Singapore Management University）
Fan Wu（PhD candidate from Caltech）
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1月2日（周四）10:00-12:15
地点：北京大学经济学院302会议室
【讲座一】
题目：Undominated Mechanisms
主讲人简介：
Jiangtao Li is an Associate Professor at the School of Economics, Singapore Management University, with a focus on economic theory and mechanism design. His research has been published in top journals, including Econometrica, Journal of Economic Theory, and Games and Economic Behavior. He also serves as an Associate Editor for the Journal of Mathematical Economics, Mathematical Social Sciences, and the International Journal of Economic Theory.
摘要：
We study the design of mechanisms when the designer faces multiple plausible scenarios and is uncertain about the true scenario. A mechanism is dominated by another if the latter performs at least as well in all plausible scenarios and strictly better in at least one. A mechanism is undominated if no other feasible mechanism dominates it. We show how analyzing undominated mechanisms could be useful and illustrate the tractability of characterizing such mechanisms. This approach provides an alternative criterion for mechanism design under non-Bayesian uncertainty, complementing existing methods.
【讲座二】
题目：Incentivizing Information Acquisition
主讲人简介：
Fan Wu is a fifth-year PhD candidate from Caltech. He works on information economics, including information acquisition, information design, and mechanism design. He also works on econometrics and empirical IO. He has two publications on the Journal of Economic Theory.
摘要：
I study a principal-agent model in which a principal hires an agent to collect information about an unknown continuous state. The agent acquires a signal whose distribution is centered around the state, controlling the signal's precision at a cost. The principal observes neither the precision nor the signal, but rather, using transfers that can depend on the state, incentivizes the agent to choose high precision and report the signal truthfully. I identify a sufficient and necessary condition on the agent’s information structure which ensures that there exists an optimal transfer with a simple cutoff structure: the agent receives a fixed prize when his prediction is close enough to the state and receives nothing otherwise. This condition is mild and applies to all signal distributions commonly used in the literature.
供稿：科研与博士后办公室
美编：初夏
责编：度量、雨禾、雨田
