
Patrick T. Brandt
My political science research employs time series analysis methods and machine learning in a variety of areas to study change in economic and political events.
972-883-4923
GR 2.802
Patrick Brandt's Webpage
Event Data Project Site
Google Scholar
Curriculum Vitae
ORCID
Not currently accepting graduate students
Professional Preparation
Indiana University - 2001
Northwestern University, - 1997
College of William and Mary, Williamsburg - 1994
Research Areas
Research Interests
My research on political and social dynamics focuses on the development and application of time series models to forecast international relations, to explicate relationships among public opinion, economic policy and the economy, and to explain patterns of conflict and terrorism. The main time series models employed in this research involve Bayesian statistics, multiple equation or vector autoregression models, methods for producing and evaluating the quality of forecasts, the derivation of new models for time series of counts, and modeling structural change and endogenous shifts in data over time.
This research agenda has been funded by the National Science Foundation and the Center for Economic and Risk Analysis of Terrorist Events (CREATE)
Publications
Awards
Appointments
University of Texas at Dallas [2015–Present]
University of Texas at Dallas [2010–2015]
University of Texas at Dallas [2007–2018]
Center for Global Collective Action
University of Texas at Dallas [2005–2010]
University of North Texas [2001–2005]
Projects
Event Count Time Series Models
2018–2018 Brandt, Patrick T. ITV series with students from the Universities of Minnesota, Illinois, Wisconsin and Ohio State. University of Minnesota, Minneapolis, MNAdvances in Bayesian Time Series Modeling and The Study of Politics: Theory Testing, Forecasting, and Policy Analysis
2018–2018 Brandt, Patrick T. and John R. Freeman. Konstanz University, Konstanz, GermanyModeling Macro Political Dynamics: The Pitfalls of Parsimony
2018–2018 Brandt, Patrick T. College of William and MaryMultiple Time Series Models
2018–2018 Brandt, Patrick T. Two-day workshop on dynamic simultaneous equation, vector autoregression (VAR), and Bayesian VAR models. University of Texas, Dallas, Richardson, TXIt's a Dynamic Multivariate Uncertain World: Policy Evaluation in Political Science
2018–2018 Brandt, Patrick T. and John R. Freeman. New Methods Series. University Of Pittsburgh, Pittsburgh, PAPresentations
Changepoint models: Statistics and Time Series for policy intervention and change identification
2022/11–2022/11Sustaining Modern Infrastructure For Political And Social Event Data
2022/09–2022/09 Brandt, Patrick T., Khan, Latifur, D’Orazio, Vito, and Osorio, JavierCSSI-PI Meeting, Alexandria, VA
Additional Information
Professional Memberships
- American Political Science Association
- Midwest Political Science Association
- International Studies Association
- Society for Political Methodology
Honors and other recognitions
- Robert H. Durr Award, Midwest Political Science Association's prize for the best paper applying quantitative methods to a substantive problem at the 2006 meeting. Published as Sattler, Thomas, John R. Freeman and Patrick T. Brandt. 2008. Popular Sovereignty and the Room to Maneuver: A Search for a Causal Chain" Comparative Political Studies
Awards and Fellowships
- Research Fellow, Workshop in Political Theory and Policy Analysis, Indiana University, Fall 1999.
- John V. Gillespie Memorial Scholarship, Department of Political Science, Indiana University, Summer 1999.
- Political Science Departmental Fellowship, Indiana University, 1994-1996.
- Governor's Fellow, Governor's Commission on Government Reform, Richmond, Virginia, Summer 1994.
- W. Warner Moss Prize, Department of Government, College of William and Mary, 1994.
News Articles
Study: Paying Terrorist Kidnappers Doesn't Pay Off for Countries

Countries that negotiated with terrorists to release hostages faced up to 87 percent more kidnappings than those that did not pay ransoms, according to the research, which was recently published in the European Journal of Political Economy.
“Every time you get one person back, and you did it by giving in, you’re going to have approximately another one taken. You’re essentially trading one for one,” said Dr. Todd Sandler, senior author of the study.