A Rothschild-Stiglitz Approach to Bayesian Persuasion
结合罗思柴尔德和斯蒂格利茨的随机变量表示法与布莱克韦尔定理，刻画了信号可诱导的后验均值分布，为分析贝叶斯说服问题提供了新方法。
Rothschild and Stiglitz (1970) represent random variables as convex functions (integrals of the cumulative distribution function). Combining this representation with Blackwell's Theorem (1953), we characterize distributions of posterior means that can be induced by a signal. This characterization provides a novel way to analyze a class of Bayesian persuasion problems.