347 Schaeffer Hall
Fall 2022 Office Hours
Tue & Th: 4:45-6:15
Dept of Political Science
341 Schaeffer Hall
20 E. Washington Street
The University of Iowa
Iowa City, Iowa 52242
Posted book info and syllabi for Spring 2023 courses in Courses section
Posted Course Evaluations for Spring 2022 courses, POLI:3113 and POLI:3120
Posted two books in What I'm Reading
Posted book info for Fall 2022 courses
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.
(paid links, here and elsewhere)
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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.