Before Billy Bean and the sabermetric revolution upended baseball and ushered in a new era of statistically driven baseball analysis, old-timers insisted that the young eggheads and their spreadsheets were no match for a time-worn scout. Experience, gut feeling, and a sense of the intangible qualities that make up a quality prospect -- these were the things that the old guard argued could never be captured by an Excel spreadsheet, let alone a statistical model.
By and large, they were wrong, and Billy Bean's scrappy Oakland Athletics squads showed that the so-called eggheads could see further into the future and with greater clarity than had previously been thought possible.
The same statistical revolution that changed baseball has now entered American politics, and no one has been more successful in popularizing a statistical approach to political analysis than New York Times blogger Nate Silver, who of course cut his teeth as a young sabermetrician. And on Nov. 6, after having faced a torrent of criticism from old-school political pundits -- Washington's rough equivalent of statistically illiterate tobacco chewing baseball scouts -- the results of the presidential election vindicated Silver's approach, which correctly predicted the electoral outcome in all 50 states.
That kind of nay-saying -- epitomized by Joe Scarborough's comments that anyone who thinks the presidential race was anything but a toss-up is a joke -- is exactly what the baseball establishment said to Billy Bean before this approach became popular in professional athletics, where it has spread far beyond a few losing baseball teams to a wide range of sports. And it is exactly what some parts of the political world said to the poll aggregators even during the most recent presidential election.
But the statistical revolution in presidential politics begs the question: Why can't the same predictive tools be applied to world politics? The amount of data that exist on world politics is enormous. Perhaps it is time to focus on making more sense of it.
The first real attempt to ask whether conflicts could be predicted can be found in Quincy Wright's 1942 magnum opus A Study of War. Interestingly, he believed short-term forecasting should be based on public opinions rather than economic and political indices. But if forecasts were to be based on indices, Wright wrote, they "should have a value for statesmen, similar to that of weather maps for farmers or of business indices for businessmen ... Such indices could be used not only for studying the probability of war between particular pairs of states but also for ascertaining the changes in the general tension level within a state of throughout the world."
But on Nov. 8, Jay Ulfelder, himself a forecaster, tried to throw a bucket of cold water on this idea, arguing in Foreign Policy why it is impossible to have a "Nate Silver" in world politics. (The fact that Nate Silver's name can now be used as a metaphor for a perfect predictive model is one indication of his enormous success and popularity.)
First, Ulfelder tells us that election forecasting is the leading edge of statistical forecasting and that the things that foreign policymakers want to know are far from that edge. Perhaps, but this is not transparently clear. Today, there are several dozen ongoing, public projects that aim to in one way or another forecast the kinds of things foreign policymakers desperately want to be able to predict: various forms of state failure, famines, mass atrocities, coups d'état, interstate and civil war, and ethnic and religious conflict. So while U.S. elections might occupy the front page of the New York Times, the ability to predict instances of extreme violence and upheaval represent the holy grail of statistical forecasting -- and researchers are now getting close to doing just that. In 2010 scholars from the Political Instability Task Force published a report that demonstrated the ability to correctly predict onsets of instability two years in advance in 18 of 21 instances (about 85%), including the prediction of instability in Iran in 2004 and Côte d'Ivoire in 2002, for example. None other than Jay Ulfelder was a co-author of this study, so he may just suffer from excessive modesty.
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