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Political Forecasting Methods: Challenges and Potential Solutions
Sat, September 7, 12:00 to 1:30pm, Marriott Philadelphia Downtown, 402Session Submission Type: Created Panel
Session Description
Political forecasting faces many methodological challenges. Small data sets, limited valid data, outliers are just a few of the many challenges facing forecasters. The papers on this panel each address a different forecasting challenge and present potential solutions.
Sub Unit
Individual Presentations
A Solution to Overfitted Forecasts: An Application to U.S. Governors - Ryan Carlin, Georgia State University; Gregory Love, University of Mississippi; Matthew Singer, University of Connecticut
Expanding the N: Election Forecasting in Difficult Environments - Ross E. Burkhart
Mapping Escalatory Patterns of Violent Conflict with Deep Learning and News Text - Mihai Croicu, Uppsala University, Dept. of Peace and Conflict Research; Simon Polichinel von der Maase, Peace Research Institute Oslo
Forecasting Electoral Violence in 2024 and 2025 - David Randahl, Department of Peace and Conflict Research, Uppsala University; Maxine Leis; Tim Gåsste, Uppsala University; Staffan I. Lindberg, V-Dem Institute, University of Gothenburg; Håvard Hegre, Peace Research Institute Oslo; Hanne Fjelde, Uppsala University; Steven Lloyd Wilson, University of Nevada, Reno
Findings from a Prediction Challenge to Forecast Conflict with Uncertainty - Paola Vesco, Peace Research Institute Oslo (PRIO); Michael P. Colaresi, University of Pittsburgh; Jonas Vestby, PRIO; Håvard Hegre, Peace Research Institute Oslo