Forecasting in International Relations

What is it about?

As a discipline matures, prediction becomes one of its standard and routine practices. The field of international relations is no exception. The growing attention to forecasting within academic research accompanies increasing expectations by the policy community that international relations research should be able to provide early warning of conflict and other human disasters and should therefore actively be engaged in forecasting exercises. Many international relations scholars nevertheless continue to see prediction as an inferior task in comparison to explanation and buy into the lamentation that forecasting is impossible. Even a pioneer in forecasting such as Oskar Morgenstern could not always resist such impulses: “Economic prognosis is . . . . impossible for objective reasons” (Morgenstern, 1928: 108, our translation). A growing number of sophisticated forecasts show, by contrast, that the discipline has come of age and increasingly includes ex-post and ex-ante predictions in the presentation of the research results. A particularly encouraging sign is the multitude of approaches that scholars have developed over recent years to improve the predictive capacity of their models and to offer early warning schemes to the policy community (Schneider, Gleditsch and Carey, 2010). These achievements acknowledge that forecasting international trends and events is no panacea. Tragic events such as genocides, massive terrorist attacks, and large-scale wars still occur, but fortunately quite rarely (Mack, 2007). However, it is exactly this rarity that makes such events so hard to anticipate. Prediction is at least as difficult for the social scientist as for the seismologist who tries to forecast the most devastating earthquakes. The two share the ambition to identify potential events among a class of similarly anticipated instances that carry the seeds of the extreme. It is not very helpful for the attempts to forecast structural breaks and sudden changes that the prediction is frequently based on data that change only slowly over time and therefore are only suitable for the prediction of minor changes. Furthermore, scientific predictions are only possible in fields where the forecasters can rely on prior knowledge and accumulated evidence in the form of systematically collected data or the insights of experts who possess privileged knowledge about an otherwise impenetrable decision making process.

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