U Iowa Home Page

Political Science

Contact Info

347 Schaeffer Hall

319-335-2348

timothy-hagle@uiowa.edu

Twitter: @ProfHagle

Spring 2023 Office Hours

Tue & Th: 4:45-6:15

Mailing Address

Dept of Political Science

341 Schaeffer Hall

20 E. Washington Street

The University of Iowa

Iowa City, Iowa 52242

Posted Fall 2023 book info on Courses page

Posted syllabi for Fall 2023 courses (POLI:3101 and POLI:3121)

Posted evaluations for Fall 2022 courses

Posted 15 papers in Warren Court Agenda Setting series

Posted updated Prelaw FAQ for UI students

Published updated and expanded edition of Prelaw Advisor in paperback and for Kindle readers

New book, Riding the Caucus Rollercoaster 2020, published in paperback and for Kindle readers.

New book, Supreme Court Agenda Setting: The Vinson Court, published for Kindle devices and computers with Kindle reader.

My books

(some paid links, here and elsewhere)

As an Amazon Associate I earn from qualifying purchases.

This page contains some miscellaneous judicial papers that have not been published elsewhere.

Should I Stay or Should I Go?  The Clash of Views on Supreme Court Retirements

Note: The paper below is an update and revisiting of my earlier paper "Strategic Retirements: A Political Model of Turnover on the United States Supreme Court" which you can find on JSTOR here.  The earlier paper was published in 1993.  The one below updates the data through 2008 and presents a new model.

Abstract: Hagle (1993) constructed a model to test whether Supreme Court justices engage in strategic behavior in their retirements. The model included several political variables that proved highly significant and supported the hypothesis. Since Hagle’s study, research works by Atkinson (1999), Brenner (1999), and Ward (2003) have examined the departures of Supreme Court justices in detail and have called into question whether political motivations influence the justices’ retirement decisions. Using Hagle’s model as a starting point, this study examines recent research, updates the data, and tests two new variables. The model is again estimated using Poisson regression. The model and the political variables, continue to be highly significant with the new data and one of the two new variables adds to the model’s explanatory power.