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Systemic Discrimination Among Large U.S. Employers

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  • Patrick M. Kline
  • Evan K. Rose
  • Christopher R. Walters

Abstract

We study the results of a massive nationwide correspondence experiment sending more than 83,000 fictitious applications with randomized characteristics to geographically dispersed jobs posted by 108 of the largest U.S. employers. Distinctively Black names reduce the probability of employer contact by 2.1 percentage points relative to distinctively white names. The magnitude of this racial gap in contact rates differs substantially across firms, exhibiting a between-company standard deviation of 1.9 percentage points. Despite an insignificant average gap in contact rates between male and female applicants, we find a between-company standard deviation in gender contact gaps of 2.7 percentage points, revealing that some firms favor male applicants while others favor women. Company-specific racial contact gaps are temporally and spatially persistent, and negatively correlated with firm profitability, federal contractor status, and a measure of recruiting centralization. Discrimination exhibits little geographical dispersion, but two digit industry explains roughly half of the cross-firm variation in both racial and gender contact gaps. Contact gaps are highly concentrated in particular companies, with firms in the top quintile of racial discrimination responsible for nearly half of lost contacts to Black applicants in the experiment. Controlling false discovery rates to the 5% level, 23 individual companies are found to discriminate against Black applicants. Our findings establish that discrimination against distinctively Black names is concentrated among a select set of large employers, many of which can be identified with high confidence using large scale inference methods.

Suggested Citation

  • Patrick M. Kline & Evan K. Rose & Christopher R. Walters, 2021. "Systemic Discrimination Among Large U.S. Employers," NBER Working Papers 29053, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:29053
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    3. Lippens, Louis & Vermeiren, Siel & Baert, Stijn, 2023. "The state of hiring discrimination: A meta-analysis of (almost) all recent correspondence experiments," European Economic Review, Elsevier, vol. 151(C).
    4. 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).
    5. , 2021. "Racial Wealth Disparities: Reconsidering the Roles of Human Capital and Inheritance," Working Papers 22-3, Federal Reserve Bank of Boston.
    6. Patrick Kline, 2023. "A Comment on: “Invidious Comparisons: Ranking and Selection as Compound Decisions” by Jiaying Gu and Roger Koenker," Econometrica, Econometric Society, vol. 91(1), pages 47-52, January.
    7. Athey, Susan & Karlan, Dean & Palikot, Emil & Yuan, Yuan, 2022. "Smiles in Profiles: Improving Fairness and Efficiency Using Estimates of User Preferences in Online Marketplaces," Research Papers 4071, Stanford University, Graduate School of Business.
    8. Lauren R. Gullett & Dana M. Alhasan & W. Braxton Jackson & Chandra L. Jackson, 2022. "Employment Industry and Occupational Class in Relation to Serious Psychological Distress in the United States," IJERPH, MDPI, vol. 19(14), pages 1-26, July.
    9. Mann, Samuel, 2021. "Transgender employment and gender marker laws," Labour Economics, Elsevier, vol. 73(C).
    10. Ewens, Michael, 2022. "Race and Gender in Entrepreneurial Finance," SocArXiv djf8z, Center for Open Science.
    11. Ruzzier, Christian A. & Woo, Marcelo D., 2023. "Discrimination with inaccurate beliefs and confirmation bias," Journal of Economic Behavior & Organization, Elsevier, vol. 210(C), pages 379-390.
    12. Enrico Rubolino, 2022. "Taxing the Gender Gap: Labor Market Effects of a Payroll Tax Cut for Women in Italy," Cahiers de Recherches Economiques du Département d'économie 22.01, Université de Lausanne, Faculté des HEC, Département d’économie.
    13. Wursten, Jesse & Reich, Michael, 2023. "Racial inequality in frictional labor markets: Evidence from minimum wages," Labour Economics, Elsevier, vol. 82(C).

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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • J7 - Labor and Demographic Economics - - Labor Discrimination
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • J78 - Labor and Demographic Economics - - Labor Discrimination - - - Public Policy (including comparable worth)
    • K31 - Law and Economics - - Other Substantive Areas of Law - - - Labor Law
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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