This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).
Conflicts continue to rage in the Levant, South Asia, and elsewhere. Governmental, nongovernmental, and intergovernmental organizations are seeking a technology that will help them anticipate the outbreak of violence. Some progress has been made predicting single events and political instability two years ahead. But we lack scientifically sound tools for gauging the statistical uncertainty of these and other forecasts, making predictions in real-time, analyzing the behavior of groups of belligerents, and making contingent forecasts (forecasts conditional on possible interventions by third parties). We develop a scientifically advanced technology that meets these desiderata: a tool that produces on an open source website in real-time, ex ante forecasts of intra- and international conflict and cooperation for three parts of the world. The time series data is produced by state-of-the art TABARI automated coding software using the CAMEO event and actor coding system; the source are news feed aggregators such as Google News and the European Monitor accessed via real simple syndication feeds (RSS). Bayesian multivariate time series models with Markov-switching are fit to these data. These models then produce forecast probability densities for systems of directed dyadic behaviors. Model performance is based on density evaluation; model refinements are made via developed recalibration methods. The website will report forecasts for selected systems of belligerents in the Levant, South Asia, and East Asia; it will disseminate the coded event data, real-time forecasts of these cases with measures of forecast uncertainty, contingent forecasts based on possible interventions, information on model performance.
The technology will meet most, if not all, of the desiderata for forecasting in international relations. Three specific contributions are be made. First, the feasibility and value of automated real-time events coding is demonstrated. Until now, this coding has lagged real-time; and the value of the data has not been realized. The application of current statistical work on forecasting is a second contribution. For the first time in political science we produce and evaluate density (not point) forecasts. And we refine our forecasting models with newly developed recalibration techniques. Third, the well known tendency for conflict and cooperation phase shifts are explicitly analyzed and incorporated in our forecasts. The Markov-switching element of our model capture these nonlinearities. Using the Teragrid we produce probability weighted forecasts of behavioral systems occupying certain states, report transition probabilities, and include estimates of the uncertainty of both. Thus the final forecasting models will be original in international relations.
The forecasts we produce will be available for use by NGOs, IGOs, and any party interested in anticipating conflict in the Levant, South Asia, and East Asia. To help these parties use our forecasts we will make presentations at meetings held by the A.P.S.A, I.S.A, and I.P.S.A. We also will present our work and publicize our website in countries like Taiwan via institutions like the Academia Sinica. Eventually, our website will report contingent forecasts based on inputs from scholars and policy makers' forecasts of what will transpire in the short-term if certain kinds of intervention occur. Estimates of the probability of phase shifts and of forecast densities will accompany these contingent forecasts.
