Reeder, Bryce, Hendricks, Michael and Goldring, Edward Peter Alan (2022) All Peacekeeping is Local:Measuring Subnational Variation in Peacekeeping Effectiveness. International Studies Quarterly. sqac010. ISSN 1468-2478
Abstract
Understanding whether peacekeepers reduce fatalities at the local level is an important question. We can have increased confidence in peacekeepers’ capabilities by testing whether deaths decrease in the locations where peacekeepers are present. However, commonly used modeling techniques cannot easily test peacekeepers’ local effectiveness. Coefficients from methods such as linear regression, logit, and count models provide average estimates of peacekeepers’ effects on violence. We argue that a solution lies in geographically weighted regression (GWR). GWR can more clearly reveal subnational spatial heterogeneity in peacekeepers’ (in)effectiveness at reducing violence. We conduct an illustrative test of our argument using data on the Democratic Republic of the Congo between 2001 and 2014 and replicate an existing study to show that GWR can also help resolve seemingly contradictory findings of whether peacekeepers are better at reducing violence by government or rebel actors. The article contains important implications for how scholars can more accurately measure peacekeeping effectiveness.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) (2022). This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Social Sciences (York) > Politics (York) |
Depositing User: | Pure (York) |
Date Deposited: | 11 May 2022 13:10 |
Last Modified: | 13 Feb 2025 05:28 |
Published Version: | https://doi.org/10.1093/isq/sqac010 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1093/isq/sqac010 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:186727 |
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