@techreport{publications22673,
          volume = {16-747},
           month = {December},
          author = {Daniel L. Chen and Xing Cui and Lanyu Shang and Junchao Zheng},
          series = {TSE Working Paper},
       booktitle = {TSE Working Paper},
            type = {Working Paper},
         address = {Toulouse},
           title = {What Matters: Agreement Between U.S. Courts of Appeals Judges},
       publisher = {TSE Working Paper},
            year = {2016},
     institution = {Universite Toulouse 1 Capitole},
             url = {https://publications.ut-capitole.fr/id/eprint/22673/},
        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.}
}