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THE GROWING CORRELATION BETWEEN RACE AND SAT SCORES: New Findings from California

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  • Geiser, Saul

Abstract

This paper presents new and surprising findings on the relationship between race and SAT scores. The findings are based on the population of California residents who applied for admission to the University of California from 1994 through 2011, a sample of over 1.1 million students. The UC data show that socioeconomic background factors – family income, parental education, and race/ethnicity – account for a large and growing share of the variance in students’ SAT scores over the past twenty years. More than a third of the variance in SAT scores can now be predicted by factors known at students’ birth, up from a quarter of the variance in 1994. Of those factors, moreover, race has become the strongest predictor. Rather than declining in salience, race and ethnicity are now more important than either family income or parental education in accounting for test score differences. It must be cautioned that these findings are preliminary, and more research is needed to determine whether the California data reflect a broader national trend. But if these findings are representative, they have important implications for the ongoing debate over both affirmative action and standardized testing in college admissions.

Suggested Citation

  • Geiser, Saul, 2015. "THE GROWING CORRELATION BETWEEN RACE AND SAT SCORES: New Findings from California," University of California at Berkeley, Center for Studies in Higher Education qt9gs5v3pv, Center for Studies in Higher Education, UC Berkeley.
  • Handle: RePEc:cdl:cshedu:qt9gs5v3pv
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    1. Neal, Derek, 2006. "Why Has Black-White Skill Convergence Stopped?," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 1, chapter 9, pages 511-576, Elsevier.
    2. Kristin Klopfenstein & M. Kathleen Thomas, 2009. "The Link between Advanced Placement Experience and Early College Success," Southern Economic Journal, John Wiley & Sons, vol. 75(3), pages 873-891, January.
    3. Rothstein, Jesse M, 2004. "College performance predictions and the SAT," Department of Economics, Working Paper Series qt59s4j4m4, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    4. Caroline Hoxby, 2000. "Peer Effects in the Classroom: Learning from Gender and Race Variation," NBER Working Papers 7867, National Bureau of Economic Research, Inc.
    5. Rothstein, J.M.Jesse M., 2004. "College performance predictions and the SAT," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 297-317.
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    Cited by:

    1. Brint, Steven & Frey, Komi, 2023. "Is the University of California Drifting Toward Conformism? The Challenges of Representation and the Climate for Academic Freedom," University of California at Berkeley, Center for Studies in Higher Education qt3pt9m168, Center for Studies in Higher Education, UC Berkeley.
    2. Clara Belitz & Jaclyn Ocumpaugh & Steven Ritter & Ryan S. Baker & Stephen E. Fancsali & Nigel Bosch, 2023. "Constructing categories: Moving beyond protected classes in algorithmic fairness," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(6), pages 663-668, June.
    3. Sandh, Simon & Donaldson, Vernisa M. & Katz, Colleen C., 2020. "Students connected to foster care: An overview of high school experiences," Children and Youth Services Review, Elsevier, vol. 113(C).

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