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The case study literature is ripe with examples of a positive association between inequality and civil war, but systematic country-level studies have largely failed to find a significant relationship. One reason for this discrepancy may be that large-N studies tend to ignore spatial variations in group welfare within countries, although civil wars often take place within limited areas. We address this gap in the literature by applying GIS operations to Demographic and Health Surveys to construct new disaggregated data on welfare and socioeconomic inequalities between and within subnational regions in 22 countries in Sub-Saharan Africa. These measures are coupled with geographical data on the location of conflict zones for the period 1986-2004. We find that conflict onsets are more likely in regions with (1) low levels of education; (2) strong relative deprivation regarding household assets; (3) strong intraregional inequalities; and (4) combined presence of natural resources and relative deprivation. Socioeconomic status has long been associated with engagement in violent conflict. Recent economic models of civil war focus on opportunity costs for rebel recruitment (e.g., Collier and Hoeffler 2004) whereas classical theories of relative 1 This article is part of the Polarization and Conflict Project

Understanding public risk perception related to possible consequences of climate change is of paramount importance. Not only does risk perception have an important role in shaping climate policy, it is also central in generating support for initiatives for adaptation and mitigation. In order to influence public knowledge and opinion, there is a need to know more about why people have diverging attitudes and perceptions related to climate change and its possible consequences. By using representative survey data for Norway and multivariate analysis, the authors of this article show that differences in attitudes and perceptions are partially explained by factors such as gender, educational background, and people's political preferences. However, an important factor

Whether qualitative or quantitative, contemporary civil-war studies have a tendency to over-aggregate empirical evidence. In order to open the black box of the state, it is necessary to pinpoint the location of key conflict parties. As a contribution to this task, this article describes a data project that geo-references ethnic groups around the world. Relying on maps and data drawn from the classical Soviet Atlas Narodov Mira (ANM), the ‘Geo-referencing of ethnic groups’ (GREG) dataset employs geographic information systems (GIS) to represent group territories as polygons. This article introduces the structure of the GREG dataset and gives an example for its application by examining the impact of group concentration on conflict. In line with previous findings, the authors show that groups with a single territorial cluster according to GREG have a significantly higher risk of conflict. This example demonstrates how the GREG dataset can be processed in the R statistical package without specific skills in GIS. The authors also provide a detailed discussion of the shortcomings of the GREG dataset, resulting from the datedness of the ANM and its unclear coding conventions. In comparing GREG to other datasets on ethnicity, the article makes an attempt to illustrate the strengths and weaknesses associated with the GREG database.

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Contemporary conflict research usually measures the influence of ethnicity on conflict by capturing ethnic constellations as country-based indices, such as ethnic fractionalization or polarization+ However, such aggregated measures are likely to conceal the actual operation of actor-specific mechanisms+ In this article, therefore, we introduce a disaggregated model that measures ethnic groups' access to power+ We do so by disaggregating both ethnicity and conflict to the level of explicitly geocoded center-periphery dyads+ This procedure allows us to measure the power balance between politically excluded ethnic groups and dominant actors in terms of group sizes, distances between the center and the periphery, and the roughness of the latter's terrain+ We rely on geographic information systems~GIS! to compute demographic and ethno-geographic variables+ The dyadic analysis enables us to show that exclusion of powerful ethnic minorities increases the likelihood of conflict considerably+ In addition, we show that the risk of conflict is positively associated with the extent of rough terrain in the peripheral group's home region and its distance from the political center+ Recent quantitative studies of civil wars have questioned the impact of ethnic grievances on the onset of civil wars+ As with so many other findings in the political-economy literature, however, this "nonresult" is based on highly aggregated proxies+ 1 In most cases, country-level indicators, such as gross domestic product~GDP! per capita or ethnic fractionalization indices, do not allow us to Earlier versions of this article were presented at

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Recent research on armed civil conflict has suggested that oil-producing countries tend to experience conflict more often than their non-oil-producing counterparts. However, this research relies on weak and incomplete measures of petroleum resources. To facilitate more rigorous research on the possible links between hydrocarbons and conflict, this paper presents and describes a new global dataset, PETRODATA. The dataset includes 890 onshore and 383 offshore locations with geographic coordinates and information on the first oil or gas discovery and production year. PETRODATA allows researchers to control for both the spatial and temporal overlap of regions with hydrocarbon reserves and armed conflict. To illustrate the use of data, we conduct a duration analysis on the types of armed civil conflict. The results suggest that oil and gas located in conflict area lengthen governmental conflicts but have no effect on conflicts over territory.