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Racial Animosity and Black Financial Advisor Underrepresentation

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  • DiBartolomeo, Jeffrey A.
  • Kothakota, Michael G.
  • Parks-Stamm, Elizabeth
  • Tharp, Derek

Abstract

This study investigates whether racial animosity across metropolitan markets is associated with Black financial advisor underrepresentation. Using a dataset of all U.S. securities-licensed individuals (N = 642,543), we first estimate the racial and ethnic composition of the industry using an algorithm that accounts for name, gender, and location. Second, we use a dataset enhanced by a commercial vendor to restrict the analysis to only those identified as working as financial advisors (n = 237,435). Using racially charged Google search queries as a proxy for racial animosity, we find that greater racial animosity is associated with greater Black advisor underrepresentation. We estimate lower underrepresentation of 0.9 percentage points when comparing markets with the highest and lowest levels of animosity. For the average market with an estimated 11.4% Black advisor representation, an increase of 0.9 percentage points would represent a 7.9% increase in Black advisor representation.

Suggested Citation

  • DiBartolomeo, Jeffrey A. & Kothakota, Michael G. & Parks-Stamm, Elizabeth & Tharp, Derek, 2021. "Racial Animosity and Black Financial Advisor Underrepresentation," SocArXiv dkh5v, Center for Open Science.
    • Handle: RePEc:osf:socarx:dkh5v
    DOI: 10.31219/osf.io/dkh5v
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    References listed on IDEAS

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    1. Stephens-Davidowitz, Seth, 2014. "The cost of racial animus on a black candidate: Evidence using Google search data," Journal of Public Economics, Elsevier, vol. 118(C), pages 26-40.
    2. Black, Harold A & Robinson, Breck L. & Schlottmann, Alan M. & Schweitzer, Robert L., 2003. "Is Race an Important Factor in Bank-Customer Preferences? The Case of Mortgage Lending," The Journal of Real Estate Finance and Economics, Springer, vol. 26(1), pages 5-26, January.
    3. Imai, Kosuke & Khanna, Kabir, 2016. "Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records," Political Analysis, Cambridge University Press, vol. 24(2), pages 263-272, April.
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