本期学术沙龙分为两场，第一场是面向学生的讲座，简要介绍了行为经济学的出现和发展。第二场是面向研究者的讲座，介绍了wakker教授最新的研究成果。

主讲人： Peter P. Wakker教授任教于荷兰鹿特丹伊拉斯姆斯大学经济学院，是在决策理论和行为经济学方面的著名学者，尤其不确定性环境下决策领域造诣深厚。他在Quarterly Journal of Economics, Econometrica, American Economic Review, Review of Economic Studies等顶级经济学期刊发表论文十余篇，发表论文总数超过150篇。2003年，根据ISI的引用量数据，Wakker教授入选全世界在经济学和商学领域一百名最有影响力的学者。近年来Wakker教授在国际上屡获殊荣：2007年他获得了医学决策分析终身成就奖；2013年又获得了决策分析协会（INFORMS Decision Analysis Society）最高荣誉——Frank P. Ramsey奖章；2016年因他在行为经济学领域的卓越贡献被瑞士圣加仑大学（University of St. Gallen）授予荣誉博士学位。

Wakker教授不仅本人造诣精深，而且还非常重视培养学生。他的学生中很多人已经成长为学界的中坚力量，在国际一流商学院和经济学院任教（如INSEAD，鹿特丹管理学院RSM，北大光华管理学院，上海财经大学经济学院等等）。

讲座概要:

Lecture 1How the Ordinal Revolution in Economics Led to the Behavioral Approach”

时间：2018年9月29日 上午9:00-11:00（周六）

地点：学术会堂606（学院南路）

For many ideas, the historical line of their development is also the best didactical line to learn about them. This lecture presents the history and birth of the behavioral approach. To prepare, it first describes the preceding revolution in economics, which took place in the 1930s, and led to the ordinal approach. This approach is still the prevailing paradigm throughout economics today, and is implicitly at the basis of most theories-and courses-in economics and finance. We then discuss the accumulating problems for the ordinal approach, and why Kahneman & Tversky (1979) ‘Prospect Theory” was a breakthrough and the birth of the ordinal approach. We finally discuss the becoming mature of the behavioral approach, its current value, and we speculate on future developments.

Lecture 2 “Belief Hedges: A New and Easy Method for Directly Measuring Uncertainties of Application-Relevant Events if no Probabilities are Known”

Peter P. Wakker

(with Aurélien Baillon, Han Bleichrodt, & Chen Li)

时间： 2018年9月30日 上午9:00-11:00（周日）

地点： 学术会堂606（学院南路）

Uncertainties usually don’t come with objective statistical probabilities, and subjective probabilities usually don’t work either (Ellsberg 1961). Gilboa & Schmeidler’s break-through at the end of the 1980s brought fundamentally new models, opening up the field of ambiguity, sorely needed in behavioral disciplines. Ambiguity attitudes have so far been measured almost exclusively for artificial events (Ellsberg urns and experimenter-specified probability intervals) because researchers did not know how to control for unknown beliefs otherwise. Ellsberg (2011) and many others emphasized the importance of the extension to natural events as in applications and everyday life. We introduce belief hedges, which control for beliefs even if unknown, and deliver the desired extension. They hedge against unknown beliefs in the same way as financial markets hedge against unknown money streams. Ambiguity attitudes can now be measured for natural events (e.g., referring directly to the financial market), greatly enhancing external validity and the motivations of subjects and clients.

Belief hedges deliver indexes of ambiguity aversion and ambiguity perception (or sensitivity) for natural events that are easy to measure in experiments, taking only a few minutes. Thus, these indexes can easily be used as an add-on in regressions. We prove that our indexes generalize and unify many indexes proposed before under various ambiguity theories, including multiple priors and prospect theory. Our indexes generalize their predecessors by: (a) being directly observable; (b) not requiring expected utility for risk; (c) being valid for a large number of ambiguity theories; (d) requiring no assessment of subjective likelihoods and, hence, which is our main novelty, (e) being applicable to natural ambiguities. An experiment on ambiguity under time pressure demonstrates the tractability of our indexes, giving plausible and validating results.xes.