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Attorney Voice and the U.S. Supreme Court

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  • Chen, Daniel L.

Abstract

Using data from 1946–2014, we show that audio features of lawyers’ introductory statements improve the performance of the best prediction models of Supreme Court outcomes. We infer voice attributes using a 15-year sample of human-labeled Supreme Court advocate voices. Audio features improved prediction of case outcomes by 1.1 percentage points. Lawyer traits receive approximately half the weight of the most important feature from the models without audio features.

Suggested Citation

  • Chen, Daniel L., 2018. "Attorney Voice and the U.S. Supreme Court," TSE Working Papers 18-978, Toulouse School of Economics (TSE).
    • Handle: RePEc:tse:wpaper:33155
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    References listed on IDEAS

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    1. David Neumark, 2018. "Experimental Research on Labor Market Discrimination," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 799-866, September.
    2. Chen, Daniel L. & Halberstam, Yosh & Yu, Alan, 2016. "Covering: Mutable Characteristics and Perceptions of Voice in the U.S. Supreme Court," TSE Working Papers 16-680, Toulouse School of Economics (TSE), revised Feb 2020.
    3. William J. Mayew & Mohan Venkatachalam, 2012. "The Power of Voice: Managerial Affective States and Future Firm Performance," Journal of Finance, American Finance Association, vol. 67(1), pages 1-44, February.
    4. Marianne Bertrand & Esther Duflo, 2016. "Field Experiments on Discrimination," NBER Working Papers 22014, National Bureau of Economic Research, Inc.
    5. Jeffrey Grogger, 2011. "Speech Patterns and Racial Wage Inequality," Journal of Human Resources, University of Wisconsin Press, vol. 46(1), pages 1-25.
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