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Civil wars cluster in space as well as time. In this study, we develop and evaluate empirically alternative explanations for this observed clustering. We consider whether the spatial pattern of intrastate conflict simply stems from a similar distribution of relevant country attributes or whether conflicts indeed constitute a threat to other proximate states. Our results strongly suggest that there is a genuine neighborhood effect of armed conflict, over and beyond what individual country characteristics can account for. We then examine whether the risk of contagion depends on the degree of exposure to proximate conflicts. Contrary to common expectations, this appears not to be the case.Rather, we find that the conflict is more likely when there are ethnic ties to groups in a neighboring conflict and that contagion is primarily a feature of separatist conflicts. This suggests that transnational ethnic linkages constitute a central mechanism of conflict contagion.

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Why do some armed civil conflicts last longer than others? Drawing on a contest success function model, we show that geographic factors (such as location, terrain, and natural resources) interact with rebel fighting capacity and together play a crucial role in determining the duration of conflict. Using precisely dated duration data in event history models and geographic data for the conflict location, we find that conflicts located at considerable distance from the main government stronghold, along remote international borders and in regions with valuable minerals last substantially longer. In addition, we find that rebel military capacity in its own right increases the prospects of a civil conflict ending within a short time period. Our findings imply that the distances an army must travel to project power, rebel fighting capacity, and characteristics of conflict region affect how a civil war is fought and who will prevail.

Contributions to the quantitative civil war literature increasingly rely on geo-referenced data and disaggregated research designs. While this is a welcome trend, it necessitates geographic information systems (GIS) skills and imposes new challenges for data collection and analysis. So far, solutions to these challenges differ between studies, obstructing direct comparison of findings and hampering replication and extension of earlier work. This article presents a standardized structure for storing, manipulating, and analyzing high-resolution spatial data. PRIO-GRID is a vector grid network with a resolution of 0.5 x 0.5 decimal degrees, covering all terrestrial areas of the world. Gridded data comprise inherently apolitical entities; the grid cells are fixed in time and space, they are insensitive to political boundaries and developments, and they are completely exogenous to likely features of interest, such as civil war outbreak, ethnic settlement patterns, extreme weather events, or the spatial distribution of wealth. Moreover, unlike other disaggregated approaches, gridded data may be scaled up or down in a consistent manner by varying the resolution of the grid. The released dataset comes with cell-specific information on a large selection of political, economic, demographic, environmental, and conflict variables for all years, 1946-2008. A simple descriptive data assessment of population density and economic activity is offered to demonstrate how PRIO-GRID may be applied in quantitative social science research.

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Geographical factors play a critical role in determining how a civil war is fought and who will prevail. Drawing on the PRIO/Uppsala Armed Conflict dataset covering the period 1946-2000, the authors have determined the location of all battle-zones for all civil wars in this time period, thereby identifying the geographic extent and the center point of each conflict. Using ordinary least squares (OLS) and three-stage least squares (3SLS) estimation techniques, factors are analyzed that determine the scope of the conflict (area of the conflict zone) and the location of the conflict relative to the capital. It is found that in addition to geographical factors such as the total land area of the country, scope is strongly shaped by such factors as the adjacencies of a border of a neighboring country, the incidence of natural resources in the conflict zone, and the duration of the conflict. The distance of the conflict zone from the capital is influenced by the scope of the conflict, the size of the country, whether or not the objective of the rebels is to secede, and whether or not the rebel group has a religious or ethnic identity. Also, evidence is found of an endogenous relationship between scope and location.

Vocal actors within policy and practice contend that environmental variability and shocks, such as drought and prolonged heat waves, drive civil wars in Africa. Recently, a widely publicized scientific article appears to substantiate this claim. This paper investigates the empirical foundation for the claimed relationship in detail. Using a host of different model specifications and alternative measures of drought, heat, and civil war, the paper concludes that climate variability is a poor predictor of armed conflict. Instead, African civil wars can be explained by generic structural and contextual conditions: prevalent ethno-political exclusion, poor national economy, and the collapse of the Cold War system.