TY  - RPRT
        AU  - Arcidiacono, Peter
AU  - Kinsler, Josh
AU  - Ransom, Tyler
        TI  - Asian American Discrimination in Harvard Admissions
        PY  - 2020/Apr/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 13172
        UR  - https://www.iza.org/publications/dp13172
        AB  - 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.
        KW  - college admissions
KW  - racial discrimination
KW  - higher education
KW  - admissions preference
        ER  -