The Hard Problem of Prediction for Conflict Prevention
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Authors
Mueller, H.
Rauh, C.
Publication Date
2021-01-06Series
Cambridge Working Papers in Economics
Cambridge-INET Working Paper Series
Publisher
Faculty of Economics, University of Cambridge
Type
Working Paper
Previous Version(s)
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Mueller, H., & Rauh, C. (2021). The Hard Problem of Prediction for Conflict Prevention. https://doi.org/10.17863/CAM.81918
Abstract
In this article we propose a framework to tackle conflict prevention, an issue which has received interest in several policy areas. A key challenge of conflict forecasting for prevention is that outbreaks of conflict in previously peaceful countries are rare events and therefore hard to predict. To make progress in this hard problem, this project summarizes more than four million newspaper articles using a topic model. The topics are then fed into a random forest to predict conflict risk, which is then integrated into a simple static framework in which a decision maker decides on the optimal number of interventions to minimize the total cost of conflict and intervention. According to the stylized model, cost savings compared to not intervening pre-conflict are over US$1 trillion even with relatively ineffective interventions, and US$13 trillion with effective interventions.
Identifiers
CWPE2103, C-INET2102
This record's DOI: https://doi.org/10.17863/CAM.81918
This record's URL: https://www.repository.cam.ac.uk/handle/1810/334500
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