Finding Certainty in Cert: An Empirical Analysis of the Factors Involved in Supreme Court Certiorari Decisions from 2001-2015
48 Pages Posted: 18 Jan 2016 Last revised: 20 Jan 2017
Date Written: February 4, 2016
Abstract
The Supreme Court annually grants approximately 5% of the petitions to hear cases it receives. It denies petitions from the federal government, from large corporations, and from high-profile attorneys. The decisions of which petitions for writ of certiorari the Court grants sets the Court's agenda each term and defines the issues which the Court will engage. With such a low likelihood that the Court hears any particular case, what makes a petition more or less likely to be granted? The focus of much of the existing scholarship on certiorari deals with the theoretical underpinnings of these judicial decisions. In this paper we set out to add to the empirical study of certiorari by examining an expansive, original dataset of the 93,000 petitions for certiorari between the 2001 and the start of the 2015 Supreme Court Terms. This allows us to investigate decisions made during and directly preceding the Roberts Court. The empirical examination focuses on several factors that are thought to affect certiorari decisions, mainly focusing on the individuals and entities involved in the certiorari petitions. These include the lower court that most recently heard the case, the parties, the attorneys, law firms, and the participation of amicus curiae. We look at success from both sides of the litigation: both in respect to petitioners and respondents. The findings in this paper are designed to add to our understanding of the extent that these individuals and entities factor into the likelihood of certiorari grants and denials. They are also designed to locate the specific individuals and entities that made the largest impact on certiorari decisions for the 2001 through 2015 Supreme Court Terms.
Keywords: Supreme Court, attorneys, firms, grants, responses, certiorari, petitions, amicus, empirical legal studies, big data analysis
JEL Classification: K41
Suggested Citation: Suggested Citation