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Statistical discrimination (economics)

Statistical discrimination is a theorized behavior in which racial or gender inequality 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 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 (1973) and Edmund Phelps (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 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 variances 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; 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. 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, which is illegal in the United States, 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.[verification needed]

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.

  1. Mankiw, N. Gregory (2020). Principle of Economics (9 ed.). Cengage Learning. pp. 392–393. ISBN 9780357133804. Retrieved19 September 2021.
  2. Fang, Hanming and Andrea Moro, 2011, "Theories of Statistical Discrimination and Affirmative Action: A Survey," in Jess Benhabib, Matthew Jackson and Alberto Bisin, eds: Handbook of Social Economics, Vol. 1A, Chapter 5, The Netherlands: North Holland, 2011, pp. 133-200. Available as NBER Working Papers 15860, National Bureau of Economic Research, Inc.
  3. Lang, Lehmann (2012). "Racial Discrimination in the Labour Market: Theory and Empirics"(PDF). Journal of Economic Literature. 50 (4): 959–1006. doi:10.1257/jel.50.4.959. JSTOR 23644909.
  4. William M. Rodgers (2009). Handbook on the Economics of Discrimination. Edward Elgar Publishing. p. 223. ISBN 978-1-84720-015-0.
  5. K. G. Dau-Schmidt (2009). Labor and Employment Law and Economics. Edward Elgar Publishing. p. 304. ISBN 978-1-78195-306-8.
  6. Wainer & Brown 2006, "Three Statistical Paradoxes in the Interpretation of Group Differences: Illustrated with Medical School Admission and Licensing Data"
  7. Paula England (1992). Comparable Worth: Theories and Evidence. Transaction Publishers. pp. 58–60. ISBN 978-0-202-30348-2.
  8. Phelps, Edmund (1972). "The Statistical Theory of Racism and Sexism". The American Economic Review. 62 (4): 659–661. JSTOR 1806107.
  9. Rooting Out Discrimination in Home Mortgage Lending -
  10. Thomas J. Nechyba (2010). Microeconomics: An Intuitive Approach. Cengage Learning. p. 514. ISBN 978-0-324-27470-7.
  11. Tilcsik, András (2020-12-11). "Statistical Discrimination and the Rationalization of Stereotypes". American Sociological Review. 86: 93–122. doi:10.1177/0003122420969399. ISSN 0003-1224.
  • Arrow, K. J. (1973), "The Theory of Discrimination", in O. Ashenfelter and A. Rees (eds.), Discrimination in Labor Markets, Princeton, NJ: Princeton University Press. ISBN 0-691-04170-9
  • Coate, Steven and Glenn Loury, 1993, Will affirmative-action policies eliminate negative stereotypes?, The American Economic Review, 1220–1240. JSTOR 2117558
  • Glenn Loury, The Anatomy of Racial Inequality, Princeton University Press. Informally illustrates the theory in the context of United States' racial differences.
  • Phelps, Edmund S. (1972). "The Statistical Theory of Racism and Sexism". American Economic Review. 62 (4): 659–661. JSTOR 1806107.

Statistical discrimination (economics)
Statistical discrimination economics Language Watch Edit Statistical discrimination is a theorized behavior in which racial or gender inequality results when economic agents consumers workers employers etc have imperfect information about individuals they interact with 1 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 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 1973 and Edmund Phelps 1972 2 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 3 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 4 or from improving their skills as their average return on investment education etc is less than for the non discriminated group 5 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 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 6 Discrimination can also occur on group variances 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 such a decision maker will prefer the group with the lower variance 7 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 7 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 8 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 9 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 10 verification needed 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 11 See also EditCoate Loury modelReferences Edit Mankiw N Gregory 2020 Principle of Economics 9 ed Cengage Learning pp 392 393 ISBN 9780357133804 Retrieved 19 September 2021 Fang Hanming and Andrea Moro 2011 Theories of Statistical Discrimination and Affirmative Action A Survey in Jess Benhabib Matthew Jackson and Alberto Bisin eds Handbook of Social Economics Vol 1A Chapter 5 The Netherlands North Holland 2011 pp 133 200 Available as NBER Working Papers 15860 National Bureau of Economic Research Inc Lang Lehmann 2012 Racial Discrimination in the Labour Market Theory and Empirics PDF Journal of Economic Literature 50 4 959 1006 doi 10 1257 jel 50 4 959 JSTOR 23644909 William M Rodgers 2009 Handbook on the Economics of Discrimination Edward Elgar Publishing p 223 ISBN 978 1 84720 015 0 K G Dau Schmidt 2009 Labor and Employment Law and Economics Edward Elgar Publishing p 304 ISBN 978 1 78195 306 8 Wainer amp Brown 2006 Three Statistical Paradoxes in the Interpretation of Group Differences Illustrated with Medical School Admission and Licensing Data a b Paula England 1992 Comparable Worth Theories and Evidence Transaction Publishers pp 58 60 ISBN 978 0 202 30348 2 Phelps Edmund 1972 The Statistical Theory of Racism and Sexism The American Economic Review 62 4 659 661 JSTOR 1806107 Rooting Out Discrimination in Home Mortgage Lending Thomas J Nechyba 2010 Microeconomics An Intuitive Approach Cengage Learning p 514 ISBN 978 0 324 27470 7 Tilcsik Andras 2020 12 11 Statistical Discrimination and the Rationalization of Stereotypes American Sociological Review 86 93 122 doi 10 1177 0003122420969399 ISSN 0003 1224 Further reading EditArrow K J 1973 The Theory of Discrimination in O Ashenfelter and A Rees eds Discrimination in Labor Markets Princeton NJ Princeton University Press ISBN 0 691 04170 9 Coate Steven and Glenn Loury 1993 Will affirmative action policies eliminate negative stereotypes The American Economic Review 1220 1240 JSTOR 2117558 Glenn Loury The Anatomy of Racial Inequality Princeton University Press Informally illustrates the theory in the context of United States racial differences Phelps Edmund S 1972 The Statistical Theory of Racism and Sexism American Economic Review 62 4 659 661 JSTOR 1806107 Retrieved from https en wikipedia org w index php title Statistical discrimination economics amp oldid 1045270939, wikipedia, wiki, book,

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