灾难性注意力偏好
Catastrophic Attention Preferences
AI总结：
本文为仅关注不利结果子集的灾难性思维建立了公理化的灾难性注意力偏好模型，完成了行为学刻画，参数可识别，还刻画了比较模糊厌恶，模型嵌套主观期望效用并收敛到最大最小期望效用。
AI中文摘要：
本文为灾难性思维提供了公理化基础，灾难性思维是一种悲观主义形式，其中主体仅关注不利结果的子集来评估不确定的备选方案。我们引入了灾难性注意力偏好（Catastrophic Attention Preferences, CAP），在此偏好下，行为是基于最坏结果的主观期望效用（以主体确定的概率阈值 q 为条件）进行评估的。由此产生的函数是期望短缺（Expected Shortfall）的主观对应物：主体的信念 μ 和阈值 q 均源自偏好而非假设，且无需将概率分布作为原始数据。我们的主要结果是一个完整的行为学刻画：六个公理（其中一个为灾难性互补性，承载了灾难性思维的行为学内容），加上两个标准的丰富性条件，等价于 CAP 表示的存在，且参数 (μ, q) 是唯一的。这些参数可从事件的概率等价物（即可通过实验 elicitation 的简单二元赌局）中完全识别。我们在该类中刻画了比较模糊厌恶：在共同信念下，模糊厌恶可通过 q 完全排序；在不同信念下，我们给出了两个信念-阈值对的充分必要条件。该模型具有等价的多先验表示，拥有闭式先验集合，当 q = 1 时嵌套主观期望效用，且当 q → 0 时收敛到最大最小期望效用。
英文摘要：
This paper provides an axiomatic foundation for catastrophic thinking, a form of pessimism in which an agent evaluates uncertain alternatives by attending only to a subset of adverse outcomes. We introduce Catastrophic Attention Preferences (CAP), under which an act is evaluated by its subjective expected utility conditional on the worst outcomes, up to a subjectively determined probability threshold $q$. The resulting functional is a subjective counterpart of Expected Shortfall: both the agent's belief $μ$ and her threshold $q$ are derived from preferences rather than assumed, without a probability distribution given as a primitive. Our main result is a complete behavioral characterization: six axioms, one of which, Catastrophic Complementarity, carries the behavioral content of catastrophic thinking, together with two standard richness conditions, are equivalent to the existence of a CAP representation, and the parameters $(μ, q)$ are unique. The parameters are fully identified from probability equivalents of events, simple binary bets that can be elicited experimentally. We characterize comparative ambiguity aversion within the class: with common beliefs, ambiguity aversion is completely ordered by $q$; with different beliefs, we provide a necessary and sufficient condition on the two belief-threshold pairs. The model admits an equivalent multiple priors representation with a closed-form set of priors, nests subjective expected utility at $q = 1$, and converges to maxmin expected utility as $q \rightarrow 0$.
