Taking the Measure of Ideology: Empirically Measuring Supreme Court Cases

86 Pages Posted: 19 Feb 2009 Last revised: 24 May 2012

Multiple version iconThere are 2 versions of this paper

Date Written: April 9, 2009


Empirical legal studies have become increasingly popular and influential, but empirical analysis is only as good as its tools. Until recently, no sophisticated measure of case outcomes existed. Jacobi (2009) developed three possible measures of case outcomes, based on three common theories of how Justices balance the trade-off between outcome optimization and coalition maximization. This Article extends Jacobi's earlier theoretical work by empirically testing those competing measures of case outcomes.

The competing measures are initially assessed against a dataset of over 8000 Supreme Court cases decided between 1953 and 2006. The measures are also assessed in a more targeted fashion in relation to Supreme Court intellectual property cases spanning the same period. The large-n data enables us to make statistically robust assessments, whereas the small-n data facilitates alternative measurement strategies and coherent doctrinal analysis. We find a viable measure of case outcomes exists that is reliable and valid. As well as suggesting the best means of scoring case outcomes, our results enhance scholars' understandings of Supreme Court jurisprudence and inform the debate over how courts decide cases.

Keywords: Judicial behavior, Empirical legal studies, Measurement, Ideology, Collegiality, Strategic behavior, Intellectual property, Supreme Court

JEL Classification: K00, K10

Suggested Citation

Jacobi, Tonja and Sag, Matthew, Taking the Measure of Ideology: Empirically Measuring Supreme Court Cases (April 9, 2009). Georgetown Law Journal, Forthcoming, Available at SSRN: https://ssrn.com/abstract=1345982

Tonja Jacobi

Northwestern University - Pritzker School of Law ( email )

375 E. Chicago Ave
Chicago, IL 60611
United States

Matthew Sag (Contact Author)

Emory University- Law School ( email )

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics