主题：Favor Exchange: Theory and Evidence

主讲：李禹燊，暨南大学

时间：2021年11月4日14:00

地点：学院B131

报告摘要：

We conduct an experiment on an infinitely repeated favor exchange game under complete and incomplete information. Since the efficient strategy is not incentive compatible under incomplete information, we focus on a sub-class of Markov strategies named Bounded Favors Bank (BFB), where the state variable is the net number of favors and its dimension is bounded. We consider two types of strategies in this class: BFBr which rewards the player who made the maximum net number of favors and BFBp which punishes the player who received the maximum net number of favors. When moving from complete information to incomplete information, we find that subjects cooperate to exchange favors substantially less often and the most commonly employed strategy switches from the efficient one to the non-cooperative one. Under incomplete information, BFB is played with a statistically significant probability, but providing summary information on the net number of favors does not increase the frequency of playing such class of strategies. Furthermore, BFBr is played more often than BFBp, indicating that using a form of reward may have more compliance than using a form of punishment in a long-term bilateral relationship with private information.

主讲人简介：

李禹燊，暨南大学产业经济研究院讲师。于2021年获得加拿大康考迪亚大学（Concordia University）经济学博士。曾先后担任蒙特利尔校际数量经济研究中心（CIERQ），蒙特利尔CIRANO研究中心，及加拿大央行银行与货币研究部助理研究员，从事合作与策略的博弈分析，研究方向为数字经济，平台经济，实验经济学，应用微观经济学。获得邹至庄最佳论文荣誉奖，加拿大经济学杰出国际毕业生奖。主持加拿大魁北克社会科学与文化基金委员会(FRQSC)博士研究课题。论文曾在经济科学协会(ESA)北美会议，加拿大经济学会(CEA)年会，CES经济学年会等国际会议上进行宣讲。