Dynamic Random Subjective Expected Utility (DR-SEU) allows to model choice data observed from an agent or a population of agents whose beliefs about objective payoff-relevant states and tastes can both evolve stochastically. Our observable, the augmented Stochastic Choice Function (aSCF) allows, in contrast to previous work in decision theory, for a direct test of whether the agent's beliefs reflect the true data-generating process conditional on their private information as well as identification of the possibly incorrect beliefs. We give an axiomatic characterization of when an agent satisfies the model, both in a static as well as in a dynamic setting. We look at the case when the agent has correct beliefs about the evolution of objective states as well as at the case when her beliefs are incorrect but unforeseen contingencies are impossible.
We also distinguish two subvariants of the dynamic model which coincide in the static setting: Evolving SEU, where a sophisticated agent's utility evolves according to a Bellman equation and Gradual Learning, where the agent is learning about her taste. We prove easy and natural comparative statics results on the degree of belief incorrectness as well as on the speed of learning about taste.
Auxiliary results contained in the online appendix extend previous decision theory work in the menu choice and stochastic choice literature from a technical as well as a conceptual perspective.
在随机期望效用（Gul and Pesendorfer，2006）中，偏好的分布可以从随机选择中唯一地恢复。本文通过两个例子说明，如果风险偏好是随机的，但不符合期望效用理论，则这种唯一性一般不成立。在第一种情况下，即使所有偏好都局限于介数类（Dekel，1986）并且是适当单调的，也会获得非唯一性。第二个例子说明了与随机期望效用一致的随机选择行为，该随机选择行为也与随机非期望效用一致。另一方面，我们发现，如果风险偏好符合加权效用理论（Chew，1983），并且在一阶随机优势下是单调的，那么随机选择再次唯一地确定了偏好的分布。最后，我们认为，根据域的风险偏好，唯一性可能会恢复，如果联合分布的选择在有限数量的可行集。
我们研究不确定性下的跨期决策。我们充分的特点贴现期望效用在一个框架à la Savage。尽管该模型很受欢迎，但在此设置中没有可用的表征。平稳性的概念，介绍了确定性贴现效用库普曼斯，起着核心作用，对时间和不确定性的态度。我们证明了一个强平稳性公理表征贴现期望效用。当考虑对冲因素时，较弱的平稳性公理将贴现期望效用推广到Choquet贴现期望效用，允许对不确定性的非中性态度。
Strategy-Proof Probabilistic Social Choice Correspondences under Conditional Expected Utility
Indian Institute of Management Calcutta（印度管理学院加尔各答分校）；Hausdorff Center for Mathematics and Institute for Microeconomics, University of Bonn（波恩大学豪斯多夫数学中心与微观经济学研究所）；Indian Institute of Technology Kanpur（坎普尔印度理工学院）
