Lars-Erik Cederman

Why Do Ethnic Groups Rebel?: New Data and Analysis

Much of the quantitative literature on civil wars and ethnic conflict ignores the role of the state or treats it as a mere arena for political competition among ethnic groups. other studies analyze how the state grants or withholds minority rights and faces ethnic protest and rebellion accordingly, while largely overlooking the ethnic power configurations at the states center. drawing on a new data set on ethnic power relations (EPR ) that identifies all politically relevant ethnic groups and their access to central state power around the world from 1946 through 2005, the authors analyze outbreaks of armed conflict as the result of competing ethnonationalist claims to state power. the findings indicate that representatives of ethnic groups are more likely to initiate conflict with the government (1) the more excluded from state power they are, especially if they have recently lost power, (2) the higher their mobilizational capacity, and (3) the more they have experienced conflict in the past.

Ethnic Politics and Armed Conflict: A Configurational Analysis of a New Global Data Set

Quantitative scholarship on civil wars has long debated whether ethnic diversity breeds armed conflict. We go beyond this debate and show that highly diverse societies are not more conflict prone. Rather, states characterized by certain ethnopolitical configurations of power are more likely to experience violent conflict. First, armed rebellions are more likely to challenge states that exclude large portions of the population on the basis of ethnic background. Second, when a large number of competing elites share power in a segmented state, the risk of violent infighting increases. Third, incohesive states with a short history of direct rule are more likely to experience secessionist conflicts. We test these hypotheses for all independent states since 1945 using the new Ethnic Power Relations (EPR) data set. Cross-national analysis demonstrates that ethnic politics is as powerful and robust in predicting civil wars as is a countrys level of economic development. Using multinomial logit regression, we show that rebellion, infighting, and secession result from high degrees of exclusion, segmentation, and incohesion, respectively. More diverse states, on the other hand, are not more likely to suffer from violent conflict.

Horizontal Inequalities and Ethnonationalist Civil War: A Global Comparison

Contemporary research on civil war has largely dismissed the role of political and economic grievances, focusing instead on opportunities for conflict. However, these strong claims rest on questionable theoretical and empirical grounds. Whereas scholars have examined primarily the relationship between individual inequality and conflict, we argue that horizontal inequalities between politically relevant ethnic groups and states at large can promote ethnonationalist conflict. Extending the empirical scope to the entire world, this article introduces a new spatial method that combines our newly geocoded data on ethnic groups’ settlement areas with spatial wealth estimates. Based on these methodological advances, we find that, in highly unequal societies, both rich and poor groups fight more often than those groups whose wealth lies closer to the country average. Our results remain robust to a number of alternative sample definitions and specifications.

Beyond Fractionalization: Mapping Ethnicity onto Nationalist Insurgencies

This paper theorizes the link between ethnicity and conflict. Conventional research relies on the ethnolinguistic fractionalization index (ELF) to explore a possible causal connection between these two phenomena. However, such approaches implicitly postulate unrealistic, individualist interaction topologies. Moreover, ELF-based studies fail to articulate explicit causal mechanisms of collective action. To overcome these difficulties, we introduce the new index N* of ethnonationalist exclusiveness that maps ethnic configurations onto political violence. This formalization is confirmed statistically in regression analysis based on data from Eurasia and North Africa.

Modeling the Size of Wars: From Billiard Balls to Sandpiles

Richardsons finding that the severity of interstate wars is power law distributed belongs to the most striking empirical regularities in world politics. This is a regularity in search of a theory. Drawing on the principles of self-organized criticality, I propose an agent-based model of war and state formation that exhibits power-law regularities. The computational findings suggest that the scale-free behavior depends on a process of technological change that leads to contextually dependent, stochastic decisions to wage war.Early drafts of this paper were prepared for presentation at the University of Michigan, the University of Chicago, Ohio State University, Yale University, the University of Pennsylvania, and Cornell University. I am grateful to the participants in those meetings and to Robert Axelrod, Claudio Cioffi-Revilla, Fredrik Liljeros, and the editor and the anonymous reviewers of this journal for excellent comments. Laszlo Gulyas helped me reimplement the model in Java and Repast. Finally, I would like to acknowledge the generous support of the John M. Olin Institute for Strategic Studies. Nevertheless, I bear the full responsibility for any inaccuracies and omissions.

Politically Relevant Ethnic Groups across Space and Time: Introducing the GeoEPR Dataset1

This article introduces GeoEPR, a geocoded version of the Ethnic Power Relations (EPR) dataset that charts politically relevant ethnic groups across space and time. We describe the dataset in detail, discuss its advantages and limitations, and use it in a replication of Cederman, Wimmer and Min’s (2010) study on the causes of ethno-nationalist conflict. We show that territorial conflicts are more likely to involve groups that settle far away from the capital city and close to the border, while these spatial variables have no effect for governmental conflicts.

Representing ethnic groups in space: A new dataset

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.

Ethno-Nationalist Dyads and Civil War A GIS-Based Analysis

Previous quantitative research on ethnic civil war relies on macro-level proxies in an attempt to specify the conditions under which ethnic minorities rebel. Going beyond an exclusive focus on minorities, the present study employs Geographic Information Systems (GIS) as a way to model ethnic center—periphery dyads that confront governments with excluded groups. We construct and analyze a new dataset of geo-referenced politically relevant ethnic groups, covering the entire world during the period from 1951 through 2005. Our results show that the conflict probability of marginalized groups increases with the demographic power balance compared to the group(s) in power. Furthermore, the risk of conflict increases with the distance from the group to the capital, and the roughness of the terrain in the groups settlement area. We also find that while the results for demographic group strength hold for all ethnic civil wars, the geographic factors apply for territorial ethnic conflicts only.

Computational Models of Social Forms: Advancing Generative Process Theory1

Building on Simmel’s theoretical foundations, sociological process theorists continue to challenge mainstream social theory. So far, however, they have rarely relied on formal modeling. The author argues that recent advances in computational modeling offer tools to explore the emergence of social forms in the Simmelian tradition. Thanks to common foundations in both epistemology and ontology, these two fields can benefit from drawing more explicitly on each other. The process‐theoretic tradition in social theory and contemporary agent‐based models shift theorizing from nomothetic to generative explanations of social forms, and from variable‐based to configurative ontologies. In order to formalize sociational theory, the author focuses on how to model dynamic social networks and emergent actor configurations.

Democratization and civil war: Empirical evidence

The hypothesis that democratization triggers political violence has been proposed repeatedly in the quantitative literature, but it remains controversial with respect to both interstate and civil wars. Current empirical research continues to be afflicted by methodological and data problems related to the measurement of democracy and the task of detecting changes in such scores. In order to gain further clarity into the link between democratization and civil war, the current study introduces a new period-finding algorithm that is able to detect periods of democratization and autocratization. This allows for a more flexible way of finding directional changes in governance indicators than is possible with the rigid lag structures commonly employed in previous studies. When regressed on various measures of civil-war onset, the indicator for the initiation of a period of democratization has a strong and robust effect on conflict even in the presence of static measures of regime type. The same applies to autocratization, but its impact is much more sudden than that of democratization. Moreover, we find that the democratization effect is limited to governmental rather than territorial conflicts. Further research will be needed to confirm these results in terms of the relevant causal mechanisms, especially in ethno-nationalist civil wars.