论文标题
统计歧视和统计信息
Statistical discrimination and statistical informativeness
论文作者
论文摘要
我们研究了菲尔普斯 - aizher-Cain型统计歧视与统计信息熟悉的概念之间的联系。我们的主要见解是,布莱克韦尔的定理(适当地重新标记)在统计信息方面的统计歧视表征。这提供了一半的钱伯斯和Echenique(2021)将统计歧视作为推论的表征,并提出了对它的不同解释:不可避免的是歧视。此外,Blackwell的定理还对统计歧视的性质提供了许多细粒度的见解。我们认为,歧视信息链接是相当笼统的,这说明了不同类型的歧视的信息表征。
We study the link between Phelps-Aigner-Cain-type statistical discrimination and familiar notions of statistical informativeness. Our central insight is that Blackwell's Theorem, suitably relabeled, characterizes statistical discrimination in terms of statistical informativeness. This delivers one-half of Chambers and Echenique's (2021) characterization of statistical discrimination as a corollary, and suggests a different interpretation of it: that discrimination is inevitable. In addition, Blackwell's Theorem delivers a number of finer-grained insights into the nature of statistical discrimination. We argue that the discrimination-informativeness link is quite general, illustrating with an informativeness characterization of a different type of discrimination.