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| The theory was pioneered by ] <ref>Arrow, K. J. (1973), "The Theory of Discrimination", in O. Ashenfelter and A. Rees (eds.), ''Discrimination in Labor Markets'', Princeton, NJ: Princeton University Press. | The theory was pioneered by ] <ref>Arrow, K. J. (1973), "The Theory of Discrimination", in O. Ashenfelter and A. Rees (eds.), ''Discrimination in Labor Markets'', Princeton, NJ: Princeton University Press. | ||
| </ref> and ]<ref>{{cite journal | author=] | title=The Statistical Theory of Racism and Sexism | journal=American Economic Review| year=1972 | volume=62 | pages=659–661}}</ref> | </ref> and ].<ref>{{cite journal | author=] | title=The Statistical Theory of Racism and Sexism | journal=American Economic Review| year=1972 | volume=62 | pages=659–661}}</ref> | ||
| The theory is based on lack of information. For instance, labor market discrimination may exist because employers don't know with certainty workers' ability, therefore they may resort to basing employment decisions on the workers' visible features, such as group identity. | The theory is based on lack of information. For instance, labor market discrimination may exist because employers don't know with certainty workers' ability, therefore they may resort to basing employment decisions on the workers' visible features, such as group identity. | ||
Revision as of 08:00, 9 March 2014
Statistical discrimination is an economic theory of racial or gender inequality based on stereotypes. According to this theory, inequality may exist and persist between demographic groups even when economic agents (consumers, workers, employers, etc.) are rational and non-prejudiced. This type of preferential treatment is labeled "statistical" because stereotypes may be based on the discriminated group's average behavior.
The theory was pioneered by Kenneth Arrow and Edmund Phelps.
The theory is based on lack of information. For instance, labor market discrimination may exist because employers don't know with certainty workers' ability, therefore they may resort to basing employment decisions on the workers' visible features, such as group identity.
Another way statistical discrimination might be applied is due to differing amount of knowledge about different groups. For instance, a large amount of data may be available for group A in comparison to group B. But say these two groups have the same distribution and average ability. If two groups, A and B, have average test scores well above the average for the entire population, but group A's estimate is considered more reliable, then if two people, one from A and one from B interview for a job, using statistical discrimination, A is hired, because it is perceived that his group score is a good estimate, but group B's group score is 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.
Statistical discrimination is often used and tolerated, for example, when older people are charged more for life insurance, or when a college diploma is required for a job (because it is believed that college graduates perform, on average, better). Some well-documented instances of statistical discrimination for involuntary group membership also do exist and are tolerated. For example, many countries allow auto insurance companies to charge men and women with identical driving records different rates (or factor in gender when deciding whether to deny coverage). The same society may not tolerate statistical discrimination when it is applied to protected groups. For example, it has been suggested that home mortgage lending discrimination against African Americans, which is illegal in the United States, may be partly caused by statistical discrimination.
References
Cited in the article
- Arrow, K. J. (1973), "The Theory of Discrimination", in O. Ashenfelter and A. Rees (eds.), Discrimination in Labor Markets, Princeton, NJ: Princeton University Press.
- Phelps, Edmund S. (1972). "The Statistical Theory of Racism and Sexism". American Economic Review. 62: 659–661.
- Rooting Out Discrimination in Home Mortgage Lending -
Other references and suggestion for further readings
- Coate, Steven and Glenn Loury, 1993, Will affirmative-action policies eliminate negative stereotypes?,The American Economic Review, 1220--1240.
- Fang, Hanming and Andrea Moro, 2010, "Theories of Statistical Discrimination and Affirmative Action: A Survey," NBER Working Papers 15860, National Bureau of Economic Research, Inc.
- Glenn Loury, The Anatomy of Racial Inequality, Princeton University Press. Informally illustrates the theory in the context of United States' racial differences.