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

Daniel Chen, Xing Cui, Lanyu Shang and Junchao Zheng

No 16-747, TSE Working Papers from Toulouse School of Economics (TSE)

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.

Date: 2016-12
New Economics Papers: this item is included in nep-law
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