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Interpreting Circuit Court Voting Patterns: A Social Interactions Framework

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  • Joshua B. Fischman

Abstract

Many empirical studies have found that circuit judges’ votes are significantly influenced by their panel colleagues. Although this influence is typically measured in terms of colleagues’ characteristics, this article argues that it is better understood as an effect of colleagues’ votes. Applying the latter interpretation, this article reanalyzes 11 prior studies of panel voting, as well as three novel data sets, and reveals the impact of colleagues’ votes to be strikingly uniform. In almost every type of case, each colleague’s vote increases the likelihood that a judge will vote in the same direction by roughly 40 percentage points. This result is consistent with a strong norm of consensus and can account for nearly all of the perceived impact of colleagues’ party, gender, and race. This finding raises questions about strategic and deliberative models of panel voting and helps clarify measurement issues regarding the relationship between judicial characteristics and voting behavior (JEL C31, K40).

Suggested Citation

  • 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.
  • Handle: RePEc:oup:jleorg:v:31:y:2015:i:4:p:808-842.
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    File URL: http://hdl.handle.net/10.1093/jleo/ews042
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    Citations

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    Cited by:

    1. Keith Carlson & Michael A. Livermore & Daniel N. Rockmore, 2020. "The Problem of Data Bias in the Pool of Published U.S. Appellate Court Opinions," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 17(2), pages 224-261, June.
    2. Freyens, Benoit Pierre & Gong, Xiaodong, 2017. "Judicial decision making under changing legal standards: The case of dismissal arbitration," Journal of Economic Behavior & Organization, Elsevier, vol. 133(C), pages 108-126.
    3. Robert S. Erikson, 2022. "Appellate court assignments as a natural experiment: Gender panel effects in sex discrimination cases," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 19(2), pages 423-446, June.
    4. Richard Holden & Michael Keane & Matthew Lilley, 2021. "Peer effects on the United States Supreme Court," Quantitative Economics, Econometric Society, vol. 12(3), pages 981-1019, July.
    5. Xiaohong Yu & Zhaoyang Sun, 2022. "The company they keep: When and why Chinese judges engage in collegiality," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 19(4), pages 936-1002, December.
    6. Freyens, Benoit Pierre & Gong, Xiaodong, 2020. "Judicial arbitration of unfair dismissal cases: The role of peer effects," International Review of Law and Economics, Elsevier, vol. 64(C).
    7. 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).

    More about this item

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • K40 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - General

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