IDEAS home Printed from https://ideas.repec.org/p/tse/wpaper/33155.html
   My bibliography  Save this paper

Attorney Voice and the U.S. Supreme Court

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://users.nber.org/~dlchen/papers/Attorney_Voice_and_the_US_Supreme_Court_LawAsData.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marianne Bertrand & Esther Duflo, 2016. "Field Experiments on Discrimination," NBER Working Papers 22014, National Bureau of Economic Research, Inc.
    2. Chen, Daniel L. & Halberstam, Yosh & Yu, Alan, 2016. "Covering: Mutable Characteristics and Perceptions of (Masculine) Voice in the U.S. Supreme Court," IAST Working Papers 16-38, Institute for Advanced Study in Toulouse (IAST), revised Feb 2020.
    3. David Neumark, 2018. "Experimental Research on Labor Market Discrimination," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 799-866, September.
    4. Jeffrey Grogger, 2011. "Speech Patterns and Racial Wage Inequality," Journal of Human Resources, University of Wisconsin Press, vol. 46(1), pages 1-25.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Daniel L., 2018. "Attorney Voice and the U.S. Supreme Court," IAST Working Papers 18-91, Institute for Advanced Study in Toulouse (IAST).
    2. Chen, Daniel L. & Sethi, Jasmin, 2016. "Insiders, Outsiders, and Involuntary Unemployment: Sexual Harrassment Exacerbates Gender Inequality," IAST Working Papers 16-44, Institute for Advanced Study in Toulouse (IAST).
    3. repec:hal:spmain:info:hdl:2441/26s2fhqla9901btt78qnrel14d is not listed on IDEAS
    4. Piopiunik, Marc & Schwerdt, Guido & Simon, Lisa & Woessmann, Ludger, 2020. "Skills, signals, and employability: An experimental investigation," European Economic Review, Elsevier, vol. 123(C).
    5. Andreas Ferrara & Price Fishback, 2024. "Discrimination, Migration, and Economic Outcomes: Evidence from World War I," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1201-1219, September.
    6. repec:spo:wpmain:info:hdl:2441/26s2fhqla9901btt78qnrel14d is not listed on IDEAS
    7. Baert, Stijn, 2017. "Hiring Discrimination: An Overview of (Almost) All Correspondence Experiments Since 2005," GLO Discussion Paper Series 61, Global Labor Organization (GLO).
    8. Berson, Clémence & Laouénan, Morgane & Valat, Emmanuel, 2020. "Outsourcing recruitment as a solution to prevent discrimination: A correspondence study," Labour Economics, Elsevier, vol. 64(C).
    9. Lisa Simon, 2019. "Microeconometric Analyses on Determinants of Individual Labour Market Outcomes," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 83.
    10. Doris Weichselbaumer, 2020. "Multiple Discrimination against Female Immigrants Wearing Headscarves," ILR Review, Cornell University, ILR School, vol. 73(3), pages 600-627, May.
    11. Diaz, Ana Maria & Salas, Luz Magdalena, 2020. "Do firms redline workers?," Regional Science and Urban Economics, Elsevier, vol. 83(C).
    12. Francisco B. Galarza, 2017. "Trust and Trustworthiness in College: An Experimental Analysis," Working Papers 17-03, Centro de Investigación, Universidad del Pacífico.
    13. Principe, Francesco & van Ours, Jan C., 2022. "Racial bias in newspaper ratings of professional football players," European Economic Review, Elsevier, vol. 141(C).
    14. Deng, Weiguang & Li, Dayang & Zhou, Dong, 2019. "Beauty and Job Accessibility: New Evidence from a Field Experiment," GLO Discussion Paper Series 369, Global Labor Organization (GLO).
    15. Henning Hermes & Philipp Lergetporer & Fabian Mierisch & Frauke Peter & Simon Wiederhold, 2023. "Discrimination on the Child Care Market: A Nationwide Field Experiment," Working Papers 225, Bavarian Graduate Program in Economics (BGPE).
    16. J. Michelle Brock & Ralph De Haas, 2023. "Discriminatory Lending: Evidence from Bankers in the Lab," American Economic Journal: Applied Economics, American Economic Association, vol. 15(2), pages 31-68, April.
    17. Dileni Gunewardena & Abdoulaye Seck, 2020. "Heterogeneity in entrepreneurship in developing countries: Risk, credit, and migration and the entrepreneurial propensity of youth and women," Review of Development Economics, Wiley Blackwell, vol. 24(3), pages 713-725, August.
    18. Baert, Stijn & Picchio, Matteo, 2021. "A signal of (Train)ability? Grade repetition and hiring chances," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 867-878.
    19. Benjamin Marx & Vincent Pons & Tavneet Suri, 2021. "Diversity and Team Performance in a Kenyan Organization," NBER Working Papers 28655, National Bureau of Economic Research, Inc.
    20. Laetitia Challe & Yannick L'Horty & Pascale Petit & François-Charles Wolff, 2018. "Les discriminations dans l'accès à l'emploi privé et public : les effets de l'origine, de l'adresse, du sexe et de l'orientation sexuelle," Working Papers halshs-01878469, HAL.
    21. Daniel Martin & Philip Marx, 2022. "A Robust Test of Prejudice for Discrimination Experiments," Management Science, INFORMS, vol. 68(6), pages 4527-4536, June.
    22. Graml, Regine & Hagen, Tobias & Ziegler, Yvonne & Khachatryan, Kristine & Herman, Ricky Astrida, 2020. "Lesbische Frauen in der Arbeitswelt: The L-Word in Business," Working Paper Series 15, Frankfurt University of Applied Sciences, Faculty of Business and Law.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tse:wpaper:33155. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/tsetofr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.