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Motivated Reasoning in the Field: Partisanship in Precedent, Prose, Vote, and Retirement in U.S. Circuit Courts, 1800-2013

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  • Ash, Elliott
  • Chen, Daniel L.
  • Lu, Wei

Abstract

We document motivated reasoning among U.S. judges. We employ a supervised learning approach to measure partisanship of text and citations of circuit court opinions. We find persistent but low partisanship of language overall, with the notable exception of civil rights and First Amendment, which liberals and conservatives have mobilized in certain periods. Citations display a significant level of partisanship and increase over time. We also document an increase in vote partisanship–dissenting only against judges appointed by the opposing party’s president. We show an increase in partisan retirement–strategically timing retirements that sclerotize the judiciary and stymie democratic churn. Finally, we show that motivated reasoning grows with judicial experience, but not age, and is more pronounced for Republican appointees.

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  • Ash, Elliott & Chen, Daniel L. & Lu, Wei, 2018. "Motivated Reasoning in the Field: Partisanship in Precedent, Prose, Vote, and Retirement in U.S. Circuit Courts, 1800-2013," IAST Working Papers 18-89, Institute for Advanced Study in Toulouse (IAST).
    • Handle: RePEc:tse:iastwp:33152
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    References listed on IDEAS

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    1. Matthew Gentzkow & Bryan T. Kelly & Matt Taddy, 2017. "Text as Data," NBER Working Papers 23276, National Bureau of Economic Research, Inc.
    2. Eileen Braman & Thomas E. Nelson, 2007. "Mechanism of Motivated Reasoning? Analogical Perception in Discrimination Disputes," American Journal of Political Science, John Wiley & Sons, vol. 51(4), pages 940-956, October.
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    4. David Autor & Nicole Maestas & Kathleen Mullen & Alexander Strand, 2011. "Does Delay Cause Decay? The Effect of Administrative Decision Time on the Labor Force Participation and Earnings of Disability Applicants," Working Papers wp258, University of Michigan, Michigan Retirement Research Center.
    5. A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012. "Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain," Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.
    6. Stephen J. Choi & G. Mitu Gulati, 2008. "Bias in Judicial Citations: A Window into the Behavior of Judges?," The Journal of Legal Studies, University of Chicago Press, vol. 37(1), pages 87-129, January.
    7. Jeffrey R. Kling, 2006. "Incarceration Length, Employment, and Earnings," American Economic Review, American Economic Association, vol. 96(3), pages 863-876, June.
    8. Carlos Berdejó & Daniel L. Chen, 2017. "Electoral Cycles among US Courts of Appeals Judges," Journal of Law and Economics, University of Chicago Press, vol. 60(3), pages 479-496.
    9. repec:cup:judgdm:v:8:y:2013:i:4:p:407-424 is not listed on IDEAS
    10. Nicholas Epley & Thomas Gilovich, 2016. "The Mechanics of Motivated Reasoning," Journal of Economic Perspectives, American Economic Association, vol. 30(3), pages 133-140, Summer.
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    Cited by:

    1. Hausladen, Carina I. & Schubert, Marcel H. & Ash, Elliott, 2020. "Text classification of ideological direction in judicial opinions," International Review of Law and Economics, Elsevier, vol. 62(C).

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