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Asian American Discrimination in Harvard Admissions

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  • Arcidiacono, Peter

    (Duke University)

  • Kinsler, Josh

    (University of Georgia)

  • Ransom, Tyler

    (University of Oklahoma)

Abstract

Detecting racial discrimination using observational data is challenging because of the presence of unobservables that may be correlated with race. Using data made public in the SFFA v. Harvard case, we estimate discrimination in a setting where this concern is mitigated. Namely, we show that there is a substantial penalty against Asian Americans in admissions with limited scope for omitted variables to overturn the result. This is because (i) Asian Americans are substantially stronger than whites on the observables associated with admissions and (ii) the richness of the data yields a model that predicts admissions extremely well. Our preferred model shows that Asian Americans would be admitted at a rate 19% higher absent this penalty. Controlling for one of the primary channels through which Asian American applicants are discriminated against — the personal rating — cuts the Asian American penalty by less than half, still leaving a substantial penalty.

Suggested Citation

  • Arcidiacono, Peter & Kinsler, Josh & Ransom, Tyler, 2020. "Asian American Discrimination in Harvard Admissions," IZA Discussion Papers 13172, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp13172
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    Cited by:

    1. Landaud, Fanny & Maurin, Eric, 2022. "Tracking When Ranking Matters," IZA Discussion Papers 15157, Institute of Labor Economics (IZA).
    2. Janys, Lena, 2020. "Evidence for a Two-Women Quota in University Departments across Disciplines," IZA Discussion Papers 13372, Institute of Labor Economics (IZA).
    3. Lena Janys, 2022. "Testing the Presence of Implicit Hiring Quotas with Application to German Universities," ECONtribute Discussion Papers Series 165, University of Bonn and University of Cologne, Germany.
    4. Gandil, Mikkel & Leuven, Edwin, 2022. "College Admission as a Screening and Sorting Device," IZA Discussion Papers 15557, Institute of Labor Economics (IZA).
    5. Lena Janys, 2021. "Testing the Presence of Implicit Hiring Quotas with Application to German Universities," Papers 2109.14343, arXiv.org, revised Nov 2021.
    6. Zachary Bleemer, 2022. "Affirmative Action, Mismatch, and Economic Mobility after California’s Proposition 209," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(1), pages 115-160.
    7. Nicolás Ajzenman & Bruno Ferman & Sant’Anna Pedro C., 2023. "Discrimination in the Formation of Academic Networks: A Field Experiment on #EconTwitter," Working Papers 235, Red Nacional de Investigadores en Economía (RedNIE).
    8. Choudhury, Prithwiraj & Ganguli, Ina & Gaulé, Patrick, 2023. "Top Talent, Elite Colleges, and Migration: Evidence from the Indian Institutes of Technology," Journal of Development Economics, Elsevier, vol. 164(C).
    9. Bertrand, Jérémie & Weill, Laurent, 2021. "Do algorithms discriminate against African Americans in lending?," Economic Modelling, Elsevier, vol. 104(C).
    10. Zhu, Maria, 2023. "New Evidence on the Underrepresentation of Asian Americans in Leadership Positions," IZA Discussion Papers 16230, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    college admissions; racial discrimination; higher education; admissions preference;
    All these keywords.

    JEL classification:

    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination

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