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廿五经研”建院25周年25场学术系列报告之二十四暨山大行为实验经济学公开分享荟2021年第15期预告

发布日期:2021-12-21   作者:    浏览次数:
时间 2021年12月23日(周四)下午16:00 地点 腾讯会议ID:321 598 056

主讲人:教沛然

时间:20211223日(周四)下午1600

地点:腾讯会议ID321 598 056

题目: Attention constraints and learning in categories

主讲人简介:Dr. Peiran Jiao is an Associate Professor of Finance at the Department of Finance, School of Business and Economics, Maastricht University (UM). He is also an Associated Fellow at Nuffield College, University of Oxford, and Director of the Centre for Experimental Social Sciences – China, a collaborated experimental centre between Nuffield College (Oxford, UK) and Nankai University Institute of State Economy (Tianjin, China). Before joining UM, Dr. Jiao was a Postdoctoral Research Fellow in the Department of Economics and Nuffield College, University of Oxford from 2014 to 2017, and Associated Researcher at the Centre for Experimental Social Sciences (CESS) – Nuffield. He obtained his PhD degree in Economics from Claremont Graduate University (CA, USA) in 2014, and BA in Economics from Nankai University (Tianjin, China) in 2008. His research mainly focuses on behavioral and experimental finance/economics. His research papers traverse a number of disciplines, such as economics, finance, psychology and neuroscience, with a mixture of theoretical, empirical and experimental approaches.He currently focuses on three topics: (1) experience and memory-based learning; (2) information processing from the news and social media; (3) biases in belief formation and updating. His papers have been published in peer-reviewed journals such as the Management Science, the Economic Journal, Journal of Economic Behavior and Organization, Brain Research, etc. His projects have been funded by the NWO (Dutch Science Council) Vidi grant, the Marie Curie Individual Fellowship, the John Fell Fund, Harvard University Foundations of Human Behavior Grant, INQUIRE Europe research grant, etc.

摘要: When different stimuli belong to the same category, learning about their attributes should be guided by this categorical structure. Here, we demonstrate how an adaptive response to attention constraints can bias learning toward shared qualities and away from individual differences. In three preregistered experiments using an information sampling paradigm with mouse-tracking, we find that people preferentially attend to information at the category level when idiosyncratic variation is low, when time constraints are more severe, and when the category contains more members. While attention is more diffuse across all information sources than predicted by Bayesian theory, there are signs of convergence toward this optimal benchmark with experience. Our results thus indicate a novel way in which a focus on categories can be driven by rational principles.