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What Matters: Agreement Between U.S. Courts of Appeals Judges

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  • Chen, Daniel L.
  • Cui, Xing
  • Shang, Lanyu
  • Zheng, Junchao

Abstract

Federal courts are a mainstay of the justice system in the United States. In this study, we analyze 387,898 cases from U.S. Courts of Appeals, where judges are randomly assigned to panels of three. We predict which judge dissents against co-panelists and analyze the dominant features that predict such dissent with a particular attention to the biographical features that judges share. Random forest, a method developed in Breiman (2001), achieves the best classification. Dissent is predominantly driven by case features, though personal features also predict agreement.

Suggested Citation

  • Chen, Daniel L. & Cui, Xing & Shang, Lanyu & Zheng, Junchao, 2016. "What Matters: Agreement Between U.S. Courts of Appeals Judges," TSE Working Papers 16-747, Toulouse School of Economics (TSE).
    • Handle: RePEc:tse:wpaper:31299
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    References listed on IDEAS

    as
    1. Chen, Daniel L., 2016. "Priming Ideology: Why Presidential Elections Affect U.S. Judges," TSE Working Papers 16-681, Toulouse School of Economics (TSE), revised Aug 2016.
    2. Joshua B. Fischman, 2015. "Interpreting Circuit Court Voting Patterns: A Social Interactions Framework," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 31(4), pages 808-842.
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    Cited by:

    1. Ramos Maqueda,Manuel & Chen,Daniel Li, 2021. "The Role of Justice in Development : The Data Revolution," Policy Research Working Paper Series 9720, The World Bank.
    2. Chen, Daniel L. & Yeh, Susan, 2016. "Government Expropriation Increases Economic Growth and Racial Inequality: Evidence from Eminent Domain," TSE Working Papers 16-693, Toulouse School of Economics (TSE).

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