EconPapers    
Economics at your fingertips  
 

A new geography of civil war: a machine learning approach to measuring the zones of armed conflicts

Kyosuke Kikuta

Political Science Research and Methods, 2022, vol. 10, issue 1, 97-115

Abstract: Where do armed conflicts occur? In applied studies, we may take ad hoc approaches to answer this question. In some regression studies, for instance, a single conflict event can cause an entire province to be classified as a conflict zone. In this paper, I fill this void of knowledge by developing a machine learning method that is less dependent on the areal-unit assumptions and can flexibly estimate conflict zones. I apply the method to a conflict event dataset and create a new dataset of conflict zones. A replication of Daskin and Pringle (2018, Nature 553, 328–332) with the new dataset indicates that the effect of civil war on mammal populations is much smaller than the original estimate.

Date: 2022
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://www.cambridge.org/core/product/identifier/ ... type/journal_article link to article abstract page (text/html)

Related works:
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:cup:pscirm:v:10:y:2022:i:1:p:97-115_7

Access Statistics for this article

More articles in Political Science Research and Methods from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Bibliographic data for series maintained by Keith Waters ().

 
Page updated 2021-12-21
Handle: RePEc:cup:pscirm:v:10:y:2022:i:1:p:97-115_7