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The Aggregate Dynamics of Lower Court Responses to the US Supreme Court

Published online by Cambridge University Press:  21 October 2022

Ali S. Masood ,
Benjamin J. Kassow  and
Donald R. Songer
Ali S. Masood*
Affiliation:
Rhodes College
Benjamin J. Kassow
Affiliation:
University of North Dakota
Donald R. Songer
Affiliation:
University of South Carolina
*
Contact the corresponding author, Ali Masood, at masooda@rhodes.edu.
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Abstract

We argue that given finite resources to review the large number of lower court decisions, Supreme Court justices should primarily be interested in aggregate responses to their precedents. We offer a theory in which the US Supreme Court drives aggregate responses to its decisions by signaling the utility of its precedents to judges on the lower courts. Specifically, we argue that lower court judges have a greater propensity to rely on a Supreme Court decision when the justices explicitly direct a lower court to consider a formally argued decision in its summary decisions. Our results demonstrate that such signals significantly increase the frequency with which the lower courts adopt the precedents of the US Supreme Court. We corroborate the causality of these links through qualitative analyses, distance matching methods, and simultaneous sensitivity analysis. Our study offers new and important insights on judicial impact and decision-making behavior in the American courts.

Type
Research Article
Information
Journal of Law and Courts , Volume 7 , Issue 2 , Fall 2019 , pp. 159 - 186
Copyright
© 2019 by the Law and Courts Organized Section of the American Political Science Association. All rights reserved.

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Footnotes

We dedicate this article to the memory of Don Songer, who passed away while working on this project. We would like to thank Matthew Blackwell, Tobias Heinrich, David Klein, Amanda Licht, Monica Lineberger, and the anonymous reviewers for helpful comments and suggestions. Data and supporting materials necessary to reproduce the results in the article are available in the JLC Dataverse at https://doi.org/10.7910/DVN/DZZY7G.

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