EconPapers    
Economics at your fingertips  
 

The Hard Problem of Prediction for Conflict Prevention

Hannes Mueller and Christopher Rauh

No 02-2019, Cahiers de recherche from Centre interuniversitaire de recherche en économie quantitative, CIREQ

Abstract: There is a rising interest in conflict prevention and this interest provides a strong motivation for better conflict forecasting. A key problem of conflict forecasting for preventionis that predicting the start of conflict in previously peaceful countries is extremely hard.To make progress in this hard problem this project exploits both supervised and unsupervised machine learning. Specifically, the latent Dirichlet allocation (LDA) model is usedfor feature extraction from 3.8 million newspaper articles and these features are then usedin a random forest model to predict conflict. We find that several features are negativelyassociated with the outbreak of conflict and these gain importance when predicting hardonsets. This is because the decision tree uses the text features in lower nodes where theyare evaluated conditionally on conflict history, which allows the random forest to adapt tothe hard problem and provides useful forecasts for prevention.

Date: 2019-04
New Economics Papers: this item is included in nep-big, nep-cmp and nep-for
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.cireqmontreal.com/wp-content/uploads/cahiers/02-2019-cah.pdf (application/pdf)

Related works:
Journal Article: The Hard Problem of Prediction for Conflict Prevention (2022) Downloads
Working Paper: The Hard Problem of Prediction for Conflict Prevention (2021) Downloads
Working Paper: The Hard Problem of Prediction for Conflict Prevention (2021) Downloads
Working Paper: The Hard Problem of Prediction for Conflict Prevention (2020) Downloads
Working Paper: The Hard Problem of Prediction for Conflict Prevention (2019) Downloads
Working Paper: The hard problem of prediction for conflict prevention (2019) Downloads
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:mtl:montec:02-2019

Access Statistics for this paper

More papers in Cahiers de recherche from Centre interuniversitaire de recherche en économie quantitative, CIREQ Contact information at EDIRC.
Bibliographic data for series maintained by Sharon BREWER ().

 
Page updated 2025-03-30
Handle: RePEc:mtl:montec:02-2019