Not a New Gold Standard: Even Big Data Cannot Predict the Future

Critical Review, Vol. 28, Issue 3-4, pp. 335-355, 2016

27 Pages Posted: 16 Nov 2017

See all articles by Kai Jäger

Kai Jäger

King’s College London - Department of Political Economy

Date Written: 2016

Abstract

Many scholars believe that the proliferation of large-scale datasets will spur scientific advancement and help us to predict the future using sophisticated statistical techniques. Indeed, a team of researchers achieved astonishing success using the world’s largest event dataset, produced by the ICEWS project, to predict complex social outcomes such as civil wars and irregular government turnovers. However, the secret of their success lay in transforming epistemically difficult questions into easy ones. Forecasting the onset of civil wars becomes an easy task if one relies on explanatory variables that measure how often newspapers report on tensions, fights, or killings shortly before. But news reports on prewar conflicts are just variations of the variable that researchers want to predict; the finding that more conflicts are likely to occur when journalists report about conflicts carries little scientific value. A similar success rate in “predicting” interstate wars can also be achieved by a simple Google News search for country names and conflict-related news shortly before a conflict is coded as a war. Big data can help researchers to make predictions in simple situations, but there is no evidence that predictions will also succeed in uncertain environments with complex outcomes — such as those characteristic of politics.

Keywords: Big Data, Event Data, ICEWS, Ideational Factors, Machine Coding, Nassim Taleb, Peace and Conflict Studies, Thai Conflict, Unpredictability

JEL Classification: C53, C55

Suggested Citation

Jäger, Kai, Not a New Gold Standard: Even Big Data Cannot Predict the Future (2016). Critical Review, Vol. 28, Issue 3-4, pp. 335-355, 2016, Available at SSRN: https://ssrn.com/abstract=3070889

Kai Jäger (Contact Author)

King’s College London - Department of Political Economy ( email )

Strand Building
London
United Kingdom

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