凸序与矩说服

中文摘要 AI 辅助

如果一个概率测度是另一个概率测度的均值保持压缩，则这两个测度被称为处于凸序关系。本文提供了多维背景下均值保持压缩及其极值点的完整刻画，将Kleiner、Moldovanu、Strack和Whitmeyer（2024）的结果扩展到包含完全揭示区域和低维合并区域的情形。我们刻画的一个核心特征是“集中”结构：每个状态只能映射到其自身不可约分量内的后验均值。我们将这些结果应用于矩说服问题。

英文摘要

If a probability measure is a mean-preserving contraction of another, the two measures are said to be in convex order. This paper provides a complete characterization of mean-preserving contractions and their extreme points in the multidimensional setting, extending the results of Kleiner, Moldovanu, Strack, and Whitmeyer (2024) to incorporate fully revealing regions and lower-dimensional pooling regions. A central feature of our characterization is a "concentration " structure: each state can be mapped only to posterior means lying within its own irreducible component. We apply these results to the moment persuasion problem.

发表机构

• Western University（韦仕敦大学）

机构由 AI 辅助整理，请以论文原文为准。