An Expert-Sourced Measure of Judicial Ideology

Posted: 1 Dec 2020 Last revised: 2 Dec 2020

See all articles by Kevin L. Cope

Kevin L. Cope

University of Virginia School of Law

Charles Crabtree

Dartmouth College

Date Written: November 29, 2020

Abstract

We introduce the first ideology measure covering every non-Supreme-Court Article III judge on a single scale. The dataset comprises dynamic, interval-level, and potentially multi-dimensional data of every federal district and appellate judge serving since 1985. The measure is derived from many thousands of qualitative evaluations by a representative sample of legal experts familiar with those judges’ approaches to judging. By drawing on expert evaluations, our method overcomes many of the issues that limit existing methods, including endogeneity, sample bias, lack of dynamic capability, and difficulty measuring the lower courts. Notably, our scores are perhaps the first to take account of the subtle differences in judges’ opinions and other law-making behavior, allowing them to differentiate between the vast majority of judges in the dataset. Our data also cover several times as many judges as the next largest dataset and are dynamic, include standard errors, and cover judicial traits that no existing measure captures. Analysis of a set of appellate-decision data indicates that our time-aggregated point estimates predict appellate outcomes more accurately than existing appellate-judge ideology measures.

Suggested Citation

Cope, Kevin L. and Crabtree, Charles, An Expert-Sourced Measure of Judicial Ideology (November 29, 2020). Virginia Law and Economics Research Paper No. 2020-19, Available at SSRN: https://ssrn.com/abstract=3739518

Kevin L. Cope (Contact Author)

University of Virginia School of Law ( email )

580 Massie Road
WB345
Charlottesville, VA 22903
United States

HOME PAGE: http://www.kevinlcope.com

Charles Crabtree

Dartmouth College ( email )

211 Silsby Hall, 3 Tuck Mall
Hanover, NH 03755
United States

HOME PAGE: http://charlescrabtree.com

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