Statistical discrimination and statistical informativeness
Matteo Escudé, Paula Onuchic, Ludvig Sinander, Quitzé Valenzuela-Stookey
Abstract
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Matteo Escudé, Paula Onuchic, Ludvig Sinander, Quitzé Valenzuela-Stookey
Abstract
Open-access reader
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.
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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.
Key concepts: Corollary, Statistical discrimination, Statistical analysis, Statistical evidence, Interpretation (philosophy), Statistical model, Type (biology), Characterization (materials science)