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Statistical Discrimination

📈 Economics By CampusDown Wiki Editorial Team Last updated
Statistical discrimination occurs when employers who cannot observe an applicant's productivity rely on group averages tied to traits such as gender or race. Its key point is that discrimination can arise from rational calculation even without prejudice.
Contents
  1. 1. Concept
  2. 2. Testing
  3. 3. Implications
  4. 4. FAQ
  5. 5. References

Concept

Gary Becker explained discrimination by employers' tastes, whereas Phelps and Arrow (1973) showed it can arise from rationally using group averages under limited information. Aigner and Cain (1977) modelled differences in how reliable employers believe signals are, linking to signalling theory.

Testing

Altonji and Pierret (2001) showed employers learn true productivity over time. Bertrand and Mullainathan (2004) found white-sounding names got about 50% more callbacks. Neumark (2018) reviewed experiments, and Guryan and Charles (2013) discussed distinguishing taste-based from statistical discrimination.

Implications

Statistical discrimination can create self-fulfilling cycles by discouraging human capital investment. Fang and Moro (2011) surveyed models and affirmative action. It is discussed with stereotype threat.

FAQ

What is it in simple terms?
Judging people by their group's average when individual information is lacking.
How does it differ from taste-based discrimination?
Taste-based discrimination stems from prejudice; statistical discrimination can arise from information gaps without it.

Sources reviewed: 2026-10-26

References

  1. Arrow, K. J. (1973). The theory of discrimination. In O. Ashenfelter & A. Rees (Eds.), Discrimination in labor markets (pp. 3–33). Princeton University Press. A foundational statement of the theory.
  2. Aigner, D. J., & Cain, G. G. (1977). Statistical theories of discrimination in labor markets. Industrial and Labor Relations Review, 30(2), 175–187. Classic formalisation.
  3. Altonji, J. G., & Pierret, C. R. (2001). Employer learning and statistical discrimination. The Quarterly Journal of Economics, 116(1), 313–350. Employer learning over time.
  4. Bertrand, M., & Mullainathan, S. (2004). Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination. American Economic Review, 94(4), 991–1013. Famous résumé field experiment.
  5. Fang, H., & Moro, A. (2011). Theories of statistical discrimination and affirmative action: A survey. In J. Benhabib, A. Bisin, & M. O. Jackson (Eds.), Handbook of social economics (Vol. 1A, pp. 133–200). North-Holland. Survey including affirmative action.
  6. Guryan, J., & Charles, K. K. (2013). Taste-based or statistical discrimination: The economics of discrimination returns to its roots. The Economic Journal, 123(572), F417–F432. Contrasts taste-based and statistical accounts.
  7. Neumark, D. (2018). Experimental research on labor market discrimination. Journal of Economic Literature, 56(3), 799–866. Review of experimental studies.

Reports and materials that use this theory (Korean)

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This article was last updated on October 27, 2026. It is based on widely recognized original works and textbooks; when citing it in a paper, please check the original sources listed in the references.