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- Hegre, Håvard, 1964-, et al.
(author)
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ViEWS : A political violence early-warning system
- 2019
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In: Journal of Peace Research. - : SAGE Publications. - 0022-3433 .- 1460-3578. ; 56:2, s. 155-174
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Journal article (peer-reviewed)abstract
- This article presents ViEWS – a political violence early-warning system that seeks to be maximally transparent, publicly available, and have uniform coverage, and sketches the methodological innovations required to achieve these objectives. ViEWS produces monthly forecasts at the country and subnational level for 36 months into the future and all three UCDP types of organized violence: state-based conflict, non-state conflict, and one-sided violence in Africa. The article presents the methodology and data behind these forecasts, evaluates their predictive performance, provides selected forecasts for October 2018 through October 2021, and indicates future extensions. ViEWS is built as an ensemble of constituent models designed to optimize its predictions. Each of these represents a theme that the conflict research literature suggests is relevant, or implements a specific statistical/machine-learning approach. Current forecasts indicate a persistence of conflict in regions in Africa with a recent history of political violence but also alert to new conflicts such as in Southern Cameroon and Northern Mozambique. The subsequent evaluation additionally shows that ViEWS is able to accurately capture the long-term behavior of established political violence, as well as diffusion processes such as the spread of violence in Cameroon. The performance demonstrated here indicates that ViEWS can be a useful complement to non-public conflict-warning systems, and also serves as a reference against which future improvements can be evaluated.
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2. |
- Vestby, Jonas, et al.
(author)
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Why do some poor countries see armed conflict while others do not? : A dual sector approach
- 2021
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In: World Development. - : Elsevier. - 0305-750X .- 1873-5991. ; 138
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Journal article (peer-reviewed)abstract
- Low level of GDP per capita is a robust and widely applied predictor of civil war. Yet, GDP is a crude macro-level indicator that masks considerable heterogeneity in economic structures, and it is less well able to explain variation in conflict risk among low-income countries. Here, we consider the merit of classic dual sector theory in improving common economic models of civil war. Two basic expectations are derived: the relative size of the traditional sector increases conflict risk via low opportunity cost and high share of immobile wealth, whereas high relative labor productivity (RLP) in the modern sector compared to the traditional sector facilitates labor mobility and wage growth, thus reducing the viability of rebellion. We evaluate these expectations via out-of-sample prediction analysis of civil conflict involvement, drawing on a unique 10-sector dataset of economic activity among 40 countries across the world since 1969. The analysis provides robust evidence that poor countries with a comparatively productive modern sector are less conflict prone than countries at similar income levels with lower RLP ratios. However, further probing into potential mechanisms producing this relationship does not provide decisive evidence in favor of any potential mechanism. We conclude that replacing GDP per capita with indicators of sector size and relative productivity improves the predictive performance of common civil war models, although more research is needed to assess the generalizability of these findings and to gain further insight into the underlying causal pathways linking relative labor productivity with reduced conflict risk.
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