Statistical Science

Assessing the Potential Impact of a Nationwide Class-Based Affirmative Action System

Alice Xiang and Donald B. Rubin

Full-text: Open access

Abstract

We examine the possible consequences of a change in law school admissions in the United States from an affirmative action system based on race to one based on socioeconomic class. Using data from the 1991–1996 Law School Admission Council Bar Passage Study, students were reassigned attendance by simulation to law school tiers by transferring the affirmative action advantage for black students to students from low socioeconomic backgrounds. The hypothetical academic outcomes for the students were then multiply-imputed to quantify the uncertainty of the resulting estimates. The analysis predicts dramatic decreases in the numbers of black students in top law school tiers, suggesting that class-based affirmative action is insufficient to maintain racial diversity in prestigious law schools. Furthermore, there appear to be no statistically significant changes in the graduation and bar passage rates of students in any demographic group. The results thus provide evidence that, other than increasing their representation in upper tiers, current affirmative action policies relative to a socioeconomic-based system neither substantially help nor harm minority academic outcomes, contradicting the predictions of the “mismatch” hypothesis, which asserts otherwise.

Article information

Source
Statist. Sci., Volume 30, Number 3 (2015), 297-327.

Dates
First available in Project Euclid: 10 August 2015

Permanent link to this document
https://projecteuclid.org/euclid.ss/1439220715

Digital Object Identifier
doi:10.1214/15-STS514

Mathematical Reviews number (MathSciNet)
MR3383883

Zentralblatt MATH identifier
1332.91093

Keywords
Causal inference multiple imputation class-based affirmative action racial affirmative action law school admissions

Citation

Xiang, Alice; Rubin, Donald B. Assessing the Potential Impact of a Nationwide Class-Based Affirmative Action System. Statist. Sci. 30 (2015), no. 3, 297--327. doi:10.1214/15-STS514. https://projecteuclid.org/euclid.ss/1439220715


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References

  • Arcidiacono, P. (2005). Affirmative action in higher education: How do admission and financial aid rules affect future earnings? Econometrica 73 1477–1524.
  • Arcidiacono, P. et al. (2012). The effects of Proposition 209 on college enrollment and graduation rates in California. Paper presented at Princeton Applied Microeconomics Seminar.
  • Ayres, I. and Brooks, R. (2005). Does affirmative action reduce the number of black lawyers? Stanford Law Review 57 1807–1854.
  • Card, D. and Krueger, A. B. (2004). Would the elimination of affirmative action affect highly qualified minority applicants? Evidence from California and Texas. No. w10366. National Bureau of Economic Research, Cambridge, MA.
  • Epple, D., Romano, R. and Sieg, H. (2008). Diversity and affirmative action in higher education. Journal of Public Economic Theory 10 475–501.
  • Fallon, R. H. Jr. (1995). Affirmative action based on economic disadvantage. UCLA Law Review 43 1913–1951.
  • Gelman, A. et al. (2006). A default prior distribution for logistic and other regression models. Unpublished manuscript. Available at www.stat.columbia.edu/gelman.
  • Graham, J. W., Olchowski, A. E. and Gilreath, T. D. (2007). How many imputations are really needed? Some practical clarifications of multiple imputation theory. Prev. Sci. 8 206–213.
  • Ho, D. E. (2005). Why affirmative action does not cause black students to fail the bar. Yale Law Journal 117 1–8.
  • Holland, P. W. (1986). Statistics and causal inference. J. Amer. Statist. Assoc. 81 945–970.
  • Kahlenberg, R. D. (1996). Class-based affirmative action. California Law Review 84 1037–1100.
  • Law School Admissions Council (1991). National Longitudinal Bar Passage Study. Data prepared by Richard Sander.
  • Long, M. C. and Tienda, M. (2008). Winners and losers: Changes in Texas university admissions post-Hopwood. Educ. Eval. Policy Anal. 30 255–280.
  • Malamud, D. C. (1997). Assessing class-based affirmative action. J. Legal Educ. 47 452–471.
  • Brief of Empirical Scholars as Amici Curiae in Support of Respondents (2012). Fisher v. University of Texas. No. 11–345. Supreme Court of the US.
  • Rubin, D. B. (1980). Discussion of “Randomization analysis of experimental data in the Fisher randomization test” by D. Basu. J. Amer. Statist. Assoc. 75 591–593.
  • Rubin, D. B. (1987). Multiple Imputation for Nonresponse in Surveys. Wiley, New York.
  • Sander, R. H. (2004). A systemic analysis of affirmative action in American law schools. Stanford Law Review 57 367–483.
  • Wightman, L. F. (1997). Threat to diversity in legal education: An empirical analysis of the consequences of abandoning race as a factor in law school admission decisions. NYUL Rev. 72 1–53.
  • Wightman, L. F. and Ramsey, H. Jr. (1998). LSAC Research report series: LSAC National Longitudinal Bar Passage Study.