Misperception and Informativeness in Statistical Discrimination

Escudé, Matteo, Paula Onuchic, Ludvig Sinander and Valenzuela-Stookey, Quitzé

No 20603, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: We study the interplay of information and prior (mis)perceptions in a Phelps--Aigner--Cain-type model of statistical discrimination in the labor market. We decompose the effect on average pay of an increase in how informative observables are about workers' skill into a non-negative instrumental component, reflecting increased surplus due to better matching of workers with tasks, and a perception-correcting component capturing how extra information diminishes the importance of prior misperceptions about the distribution of skills in the worker population. We sign the perception-correcting term: it is non-negative (non-positive) if the population was ex-ante under-perceived (over-perceived). We then consider the implications for pay gaps between equally-skilled populations that differ in information, perceptions, or both, and identify conditions under which improving information narrows pay gaps.

Keywords: Statistical discrimination; Misperceptions; Informativeness (search for similar items in EconPapers)
JEL-codes: D60 D80 (search for similar items in EconPapers)
Date: 2025-08
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