This article presents a novel index assessing regional conflict exposure in countries, suggesting implications for civil war dynamics and political instability.
This article introduces the Geographical Proximity to Conflict Index (GPCI), a novel approach to quantify a country’s regional conflict exposure. I develop the GPCI drawing on the Uppsala Conflict Data Program (UCDP) Battle-Related Deaths Dataset v25.1, the Dyadic Dataset v25.1, and CEPII geospatial distance matrices. The GPCI combines three core conflict dimensions – intensity (battle deaths), frequency (conflict dyads), and type (civil vs. international) – with three types of spatial proximity: centroid-to-centroid, capital-to-capital, and population-weighted distances. The GPCI covers 188 UN member states from 1989 to 2024 and offers 18 composite indicators and 18 disaggregated variables that can be used to analyse cross-national and fine-grained conflict dynamics. I apply the GPCI in civil war onset models to demonstrate its empirical utility using the UCDP Armed Conflict Dataset (ACD) and the Correlates of War (COW) Civil War Dataset. Results across multiple modelling strategies and measures of proximity and intensity demonstrate that countries with higher regional conflict exposure are significantly more likely to experience civil war onset, even after accounting for economic, demographic, and institutional factors. This study suggests the utility of GPCI in studying civil war onset, duration, diffusion, political instability, terrorism, forced displacement, humanitarian risk, international security, and peacebuilding.
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Anurug Chakma (2025) studied this question.
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