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Lady Justice: The impact of female judges on trials' verdicts in US

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  • Alessandra Foresta

Abstract

This work evaluates the role of judges' gender on jury trials verdicts in the US state of North Carolina. My identification strategy is based on judges' rotation across districts and fixed effects. The results indicate that, in trials presided by female judges, juries are more likely to express guilty verdicts. I implement a series of robustness checks (different models' specifications, defendants' characteristics, district sizes, judges' types, judges' experience and workloads) and a series of heterogeneity checks (judges' characteristics, types of crimes and jurors' gender). Finally, I discuss the possible mechanisms behind these findings and I explore the impact of the jury selection process, the role of judges' toughness and the attitudes of women towards courts and sentencing.

Suggested Citation

  • Alessandra Foresta, 2022. "Lady Justice: The impact of female judges on trials' verdicts in US," Discussion Papers 22/04, Department of Economics, University of York.
    • Handle: RePEc:yor:yorken:22/04
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    References listed on IDEAS

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    1. Markus Nagler & Marc Piopiunik & Martin R. West, 2020. "Weak Markets, Strong Teachers: Recession at Career Start and Teacher Effectiveness," Journal of Labor Economics, University of Chicago Press, vol. 38(2), pages 453-500.
    2. Scott E. Carrell & Marianne E. Page & James E. West, 2010. "Sex and Science: How Professor Gender Perpetuates the Gender Gap," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(3), pages 1101-1144.
    3. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    4. Francis X. Flanagan, 2018. "Race, Gender, and Juries: Evidence from North Carolina," Journal of Law and Economics, University of Chicago Press, vol. 61(2), pages 189-214.
    5. Joshua B. Fischman & Max M. Schanzenbach, 2011. "Do Standards of Review Matter? The Case of Federal Criminal Sentencing," The Journal of Legal Studies, University of Chicago Press, vol. 40(2), pages 405-437.
    6. Andrew V. Carter & Kevin T. Schnepel & Douglas G. Steigerwald, 2017. "Asymptotic Behavior of a t -Test Robust to Cluster Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 99(4), pages 698-709, July.
    7. Thomas S. Dee, 2007. "Teachers and the Gender Gaps in Student Achievement," Journal of Human Resources, University of Wisconsin Press, vol. 42(3).
    8. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    9. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    10. Shamena Anwar & Patrick Bayer & Randi Hjalmarsson, 2014. "The Role of Age in Jury Selection and Trial Outcomes," Journal of Law and Economics, University of Chicago Press, vol. 57(4), pages 1001-1030.
    11. Shamena Anwar & Patrick Bayer & Randi Hjalmarsson, 2012. "The Impact of Jury Race in Criminal Trials," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(2), pages 1017-1055.
    12. Matthew Spitzer & Eric Talley, 2013. "Left, Right, and Center: Strategic Information Acquisition and Diversity in Judicial Panels," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 29(3), pages 638-680, June.
    13. Thomas Fujiwara & Leonard Wantchekon, 2013. "Can Informed Public Deliberation Overcome Clientelism? Experimental Evidence from Benin," American Economic Journal: Applied Economics, American Economic Association, vol. 5(4), pages 241-255, October.
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    More about this item

    Keywords

    Gender; Judge; Trials behaviours;
    All these keywords.

    JEL classification:

    • K10 - Law and Economics - - Basic Areas of Law - - - General (Constitutional Law)
    • K40 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - General
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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