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Forecasting State Failure King, Gary Zeng, Langche Uploaded 04-19-2000 Keywords forecast neural network committee methods case-control Abstract We offer the first independent scholarly evaluation of the claims, forecasts, and causal inferences of the State Failure Task Force and their efforts to forecast when states will fail. This Task Force, set up at the behest of Vice President Gore in 1994, has been led by a group of distinguished academics working as consultants to the U.S. Government. State failure is a grave condition that includes civil wars, revolutionary wars, genocides, politicides, and adverse or disruptive regime transitions. State Failure Task Force reports and publications have received widespread attention in the media, in academia, and from public policy decision-makers. In this paper, we identify several methodological errors in the Task Force work that cause their reported forecast probabilities of conflict to be much too large, their causal inferences to be biased in unpredictable directions, and their claims of forecasting performance to be exaggerated. However, we also find that the Task Force has amassed the best and most carefully collected data on state failure in existence, and the required corrections, although very large in effect, are easy to implement. We also reanalyze their data with better statistical and other procedures and demonstrate how to improve forecasting performance to levels significantly greater than even corrected versions of their models. We hope that this work leads to better use of political science and statistical analyses in public policy, but most of the claims analyzed are also of direct relevance to ongoing scholarly debates in political science, public health, and other disciplines.