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Bias in White: A Longitudinal Natural Experiment Measuring Changes in Discrimination

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  • Brian Rubineau

    (ILR School, Cornell University, Ithaca, New York 14853)

  • Yoon Kang

    (Weill Cornell Medical College, Cornell University, New York, New York 10021)

Abstract

Many professions are plagued by disparities in service delivery. Racial disparities in policing, mortgage lending, and healthcare are some notable examples. Because disparities can result from a myriad of mechanisms, crafting effective disparity mitigation policies requires knowing which mechanisms are active and which are not. In this study we can distinguish whether one mechanism--statistical discrimination--is a primary explanation for racial disparities in physicians' treatment of patients. In a longitudinal natural experiment using repeated quasi-audit studies of medical students, we test for within-cohort changes in disparities from medical student behaviors as they interact with white and black patient actors. We find significant increases in medical students' disparate behaviors by patient race between their first and second years of medical school. This finding is inconsistent with statistical discrimination predictions and challenges the idea that statistical discrimination is primarily responsible for racial disparities in patient care. This paper was accepted by Jesper SØrensen, organizations.

Suggested Citation

  • Brian Rubineau & Yoon Kang, 2012. "Bias in White: A Longitudinal Natural Experiment Measuring Changes in Discrimination," Management Science, INFORMS, vol. 58(4), pages 660-677, April.
    • Handle: RePEc:inm:ormnsc:v:58:y:2012:i:4:p:660-677
    DOI: 10.1287/mnsc.1110.1439
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    References listed on IDEAS

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    Cited by:

    1. Leung, Ming D., 2016. "Learning to hire? Hiring as a dynamic experiential process in an online market for contract labor," Institute for Research on Labor and Employment, Working Paper Series qt6z86b2vx, Institute of Industrial Relations, UC Berkeley.
    2. Adina D. Sterling, 2014. "Friendships and Search Behavior in Labor Markets," Management Science, INFORMS, vol. 60(9), pages 2341-2354, September.
    3. Chen Liang & Yili Hong & Bin Gu, 2017. "Home Bias in Global Employment," Working Papers 17-06, NET Institute.
    4. Letian Zhang, 2019. "Who Loses When a Team Wins? Better Performance Increases Racial Bias," Organization Science, INFORMS, vol. 30(1), pages 40-50, February.
    5. Subhasish M. Chowdhury & Sarah Jewell & Carl Singleton, 2023. "Can Awareness Reduce (and Reverse) Identity-driven Bias in Judgement? Evidence from International Cricket," Economics Discussion Papers em-dp2023-10, Department of Economics, University of Reading.
    6. Benjamin Edelman & Micahel Luca, 2014. "Digital Discrimination: The Case of Airbnb.com," Harvard Business School Working Papers 14-054, Harvard Business School.
    7. Adina D. Sterling & Roberto M. Fernandez, 2018. "Once in the Door: Gender, Tryouts, and the Initial Salaries of Managers," Management Science, INFORMS, vol. 64(11), pages 5444-5460, November.

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