Statistical discrimination is a theorized behavior in which racial or gender

inequality Inequality may refer to: Economics * Attention inequality, unequal distribution of attention across users, groups of people, issues in etc. in attention economy * Economic inequality, difference in economic well-being between population groups * ...

results when economic agents (consumers, workers, employers, etc.) have imperfect information about individuals they interact with. According to this theory, inequality may exist and persist between demographic groups even when economic agents are rational and non-prejudiced. It stands in contrast with

taste-based discrimination Taste-based discrimination is an economic model of labor market discrimination which argues that employers' prejudice or dislikes in an organisational culture rooted in prohibited grounds can have negative results in hiring minority workers, mea ...

which uses racism, sexism and the likes to explain different labour market outcomes of groups. The theory of statistical discrimination was pioneered by

Kenneth Arrow Kenneth Joseph Arrow (23 August 1921 – 21 February 2017) was an American economist, mathematician, writer, and political theorist. He was the joint winner of the Nobel Memorial Prize in Economic Sciences with John Hicks in 1972. In economics ...

(1973) and

Edmund Phelps Edmund Strother Phelps (born July 26, 1933) is an American economist and the recipient of the 2006 Nobel Memorial Prize in Economic Sciences. Early in his career, he became known for his research at Yale's Cowles Foundation in the first half of ...

(1972). The name "statistical discrimination" relates to the way in which employers make employment decisions. Since their information on the applicants' productivity is imperfect, they use statistical information on the group they belong to in order to infer productivity. If the minority group is less productive initially (due to historic discrimination or having navigated a bad equilibrium), each individual in this group will be assumed to be less productive and discrimination arises. This type of discrimination can result in a self-reinforcing vicious circle over time, as the atypical individuals from the discriminated group are discouraged from participating in the market, or from improving their skills as their (average) return on investment (education etc.) is less than for the non-discriminated group. A related form of (theorized) statistical discrimination is based on differences in the signals that applicants send to employers. These signals report the applicant's productivity, but they are noisy. Discrimination can occur if groups differ on means, even if applicants have identical nominal above-average signals:

regression to the mean In statistics, regression toward the mean (also called reversion to the mean, and reversion to mediocrity) is the fact that if one sample of a random variable is extreme, the next sampling of the same random variable is likely to be closer to it ...

will imply that a member of a higher-mean group will regress less as they are more likely to have a higher true value, while the lower-mean group member will regress more and the signal will overestimate their value if the group membership is ignored ("Kelley's paradox"). Discrimination can also occur on group

variance In probability theory and statistics, variance is the expectation of the squared deviation of a random variable from its population mean or sample mean. Variance is a measure of dispersion, meaning it is a measure of how far a set of numbe ...

s in the signals (i.e. in how noisy the signal is), even assuming equal averages. For variance-based discrimination to occur, the decision maker needs to be

risk averse In economics and finance, risk aversion is the tendency of people to prefer outcomes with low uncertainty to those outcomes with high uncertainty, even if the average outcome of the latter is equal to or higher in monetary value than the more c ...

; such a decision maker will prefer the group with the lower variance. Even assuming two theoretically identical groups (in all respects, including average and variance), a risk averse decision maker will prefer the group for which a measurement (signal, test) exists that minimizes the signal

error term In mathematics and statistics, an error term is an additive type of error. Common examples include: * errors and residuals in statistics, e.g. in linear regression * the error term in numerical integration In analysis, numerical integration ...

. For example, assume two individuals, A and B, have theoretically identical test scores well above the average for the entire population, but individual A's estimate is considered more reliable because a large amount of data may be available for their group in comparison to the group of B. Then if two people, one from A and one from B, apply for the same job, A is hired, because it is perceived that their score is a more reliable estimate, so a risk-averse decision maker sees B's score as more likely to be luck. Conversely, if the two groups are below average, B is hired, because group A's negative score is believed to be a better estimate. This generates differences in employment chances, but also in the average wages of different groups - a group with a lower signal precision will be disproportionately employed to lower paying jobs. It has been suggested that home mortgage lending discrimination against

African Americans African Americans (also referred to as Black Americans and Afro-Americans) are an ethnic group consisting of Americans with partial or total ancestry from sub-Saharan Africa. The term "African American" generally denotes descendants of ens ...

, which is illegal in the

United States The United States of America (U.S.A. or USA), commonly known as the United States (U.S. or US) or America, is a country primarily located in North America. It consists of 50 states, a federal district, five major unincorporated territorie ...

, may be partly caused by statistical discrimination. Market forces are expected to penalize some forms of statistical discrimination; for example, a company capable and willing to test its job applicants on relevant metrics is expected to do better than one that relies only on group averages for employment decisions. According to a 2020 study, managers who had experience with statistical discrimination theory were more likely to believe in the accuracy of stereotypes, accept stereotyping, and engage in gender discrimination in hiring. When managers were informed of criticisms against statistical discrimination, these effects were reduced.

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