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An Empirical Justification for the Use of Racially Distinctive Names to Signal Race in Experiments

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  • Butler, Daniel M.
  • Homola, Jonathan

Abstract

Researchers studying discrimination and bias frequently conduct experiments that use racially distinctive names to signal race. The ability of these experiments to speak to racial discrimination depends on the excludability assumption that subjects’ responses to these names are driven by their reaction to the individual’s putative race and not some other factor. We use results from an audit study with a large number of aliases and data from detailed public records to empirically test the excludability assumption undergirding the use of racially distinctive names. The detailed public records allow us to measure the signals about socioeconomic status and political resources that each name used in the study possibly could send. We then reanalyze the audit study to see whether these signals predict legislators’ likelihood of responding. We find no evidence that politicians respond to this other information, thus providing empirical support for the excludability assumption.

Suggested Citation

  • Butler, Daniel M. & Homola, Jonathan, 2017. "An Empirical Justification for the Use of Racially Distinctive Names to Signal Race in Experiments," Political Analysis, Cambridge University Press, vol. 25(1), pages 122-130, January.
  • Handle: RePEc:cup:polals:v:25:y:2017:i:01:p:122-130_00
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    Cited by:

    1. Nicholas R. Jenkins & Michelangelo Landgrave & Gabriel E. Martinez, 2020. "Do political donors have greater access to government officials? Evidence from a FOIA field experiment with US municipalities," Journal of Behavioral Public Administration, Center for Experimental and Behavioral Public Administration, vol. 3(2).
    2. Gaddis, S. Michael, 2018. "An Introduction to Audit Studies in the Social Sciences," SocArXiv e5hfc, Center for Open Science.
    3. Mladen Adamovic & Andreas Leibbrandt, 2024. "Is there a glass ceiling for ethnic minorities to enter leadership positions? Evidence from a large-scale field experiment with over 12,000 job applications," Monash Economics Working Papers 2024-06, Monash University, Department of Economics.
    4. Dara Kay Cohen & Connor Huff & Robert Schub, 2021. "At War and at Home: The Consequences of US Women Combat Casualties," Journal of Conflict Resolution, Peace Science Society (International), vol. 65(4), pages 647-671, April.
    5. Druckman, James N. & Levy, Jeremy & Sands, Natalie, 2021. "Bias in education disability accommodations," Economics of Education Review, Elsevier, vol. 85(C).
    6. Gaddis, S. Michael & DiRago, Nicholas V., 2021. "Audit Studies of Housing in the United States: Established, Emerging, and Future Research," SocArXiv fn4ta, Center for Open Science.
    7. Mladen Adamovic & Andreas Leibbrandt, 2023. "A large‐scale field experiment on occupational gender segregation and hiring discrimination," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 62(1), pages 34-59, January.
    8. Christopher T. Bennett, 2023. "Labor Market Returns to MBAs From Less‐Selective Universities: Evidence From a Field Experiment During COVID‐19," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(2), pages 525-551, March.

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