The Hard Problem of Prediction for Conflict Prevention
Hannes Mueller and
Christopher Rauh
Journal of the European Economic Association, 2022, vol. 20, issue 6, 2440-2467
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.
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)
Downloads: (external link)
http://hdl.handle.net/10.1093/jeea/jvac025 (application/pdf)
Access to full text is restricted to subscribers.
Related works:
Working Paper: The Hard Problem of Prediction for Conflict Prevention (2021) 
Working Paper: The Hard Problem of Prediction for Conflict Prevention (2021) 
Working Paper: The Hard Problem of Prediction for Conflict Prevention (2020) 
Working Paper: The Hard Problem of Prediction for Conflict Prevention (2019) 
Working Paper: The hard problem of prediction for conflict prevention (2019) 
Working Paper: The Hard Problem of Prediction for Conflict Prevention (2019) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:oup:jeurec:v:20:y:2022:i:6:p:2440-2467.
Access Statistics for this article
Journal of the European Economic Association is currently edited by Romain Wacziarg
More articles in Journal of the European Economic Association from European Economic Association
Bibliographic data for series maintained by Oxford University Press ().