A tweet by Sarah Jacobson prompted a few discussion threads on current perspectives on statistical discrimination and efficiency/inefficiency. Here is the original tweet:
I used to think economists used the idea of statistical discrimination to understand how discrimination could be defeated – by info vs some other means. But it seems like instead some think of it as a justification – a reason discrimination is OK. Sometimes economists bum me out.— Sarah Jacobson (@SarahJacobsonEc) May 18, 2021
I have collected references to some of the papers that discussants mentioned as providing more refined takes on the original Arrow and Aigner-Cain analyses:
- Lundberg, Shelly J., and Richard Startz. “Private discrimination and social intervention in competitive labor market.” The American Economic Review 73.3 (1983): 340-347.
- Schwab, Stewart. “Is statistical discrimination efficient?.” The American Economic Review 76.1 (1986): 228-234.
- Coate, Stephen, and Glenn C. Loury. “Will affirmative-action policies eliminate negative stereotypes?.” The American Economic Review (1993): 1220-1240.
- Bohren, J. Aislinn, et al. Inaccurate statistical discrimination. No. w25935. National Bureau of Economic Research, 2019.
- Lang, Kevin, and Ariella Kahn-Lang Spitzer. “Race discrimination: An economic perspective.” Journal of Economic Perspectives 34.2 (2020): 68-89.
- Komiyama, Junpei, and Shunya Noda. “On Statistical Discrimination as a Failure of Social Learning: A Multi-Armed Bandit Approach.” arXiv preprint arXiv:2010.01079 (2020).
- Fosgerau, Mogens and Sethi, Rajiv and Weibull, Jorgen W., Costly Screening and Categorical Inequality (April 21, 2021). Available at SSRN: https://ssrn.com/abstract=3533952 or http://dx.doi.org/10.2139/ssrn.3533952