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SBE 2020: Submission Detail

ID Number: 157
Title: Predictive Models for Political Instability
Lead Author: Schrodt, Philip A.
Abstract: Over the past decade, two very large-scale U.S. government projectsthe multi-agency Political Instability Task Force (PITF) and DARPAs Integrated Conflict Early Warning Systems (ICEWS)have invested tens of millions of dollars in the development of statistical early warning systems for forecasting a variety of measures of political instability. While both systems have had considerable input from political scientists, there has been little interaction between this work and NSF-funded academic research. PITF and ICEWS have been very successful in demonstrating that we now have sufficient data and appropriate statistical methods to create forecasting models that have substantially higher out-of-sample accuracy than traditional expert forecasting, but a substantial number of basic research questions remain unanswered. These include development of ensemble methods for the integration of multiple models, further work on statistical time series and pattern recognition models, assessing causality and counter-factual inference issues, and integration of qualitative assessments into the quantitative models. These basic research issues cross a number of disciplinary and substantive boundaries, would contribute substantially to the intellectual infrastructure in the field, and assist in the transfer of this U.S. contract research to both the academic methodology community and the larger non-governmental organization community.
PDF: Schrodt_Philip_157.pdf

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