Convex Order and Moment Persuasion

2026-09-12

AI Summary

本文解决了多维环境下均值保持收缩的特征问题，通过引入‘集中’结构方法，并将结果应用于矩说服问题。

Abstract

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.

Problem

• convex order
• mean-preserving contractions
• multidimensional setting
• moment persuasion

Innovation

• convex order
• mean-preserving contraction
• concentration structure
• moment persuasion