Diversity within Mission Leadership

This chapter explores the issue of diversity within mission’s leadership: between the Special Representatives of the Secretary-General (SRSG) and the Force Commanders (FC). It asks how this affects operational performances. In three case studies, UNIFIL II, MINUSMA and MINUSCA, the chapter finds the presence of communication and coordination problems, mainly related to personalities rather than diversity. Occasionally, the problem was a lack of experience of leadership. Another issue that emerges is the difficulty of SRSGs to act as the principal in relation to security issues. Yet, with learning and expert advisors these dimensions can easily be overcome. The chapter then introduces new data on SRSGs and FCs for all the operations in the post-Cold War period. The quantitative analysis shows a negative correlation between diversity within a mission’s leadership and the level of civilian victimization and battle deaths. As such, diversity seems to have beneficial conflict reduction effects.

Making disorder more manageable: The short-term effectiveness of local mediation in Darfur

Much of the quantitative conflict resolution literature focuses on mediation between states or on efforts to end a civil war through a comprehensive peace agreement that brings peace to the entire country. This article instead analyses the effectiveness of mediation between a wide range of armed actors on a subnational level. Utilizing unique data on Darfur covering the January 2008–August 2009 period, this article finds that mediation efforts following armed clashes in a given area significantly prolong local lulls in fighting in this area. This finding remains robust when controlling for the presence of a peacekeeping base, battle-deaths and the type of armed actors engaged in armed clashes. In addition, the finding remains robust when accounting for the non-random assignment of mediation efforts through matching similar observations in the dataset. Finally, anecdotal evidence from sites of armed conflict beyond Darfur suggest that the findings from this study might also hold in other armed conflicts.

Statistical sightings of better angels: Analysing the distribution of battle-deaths in interstate conflict over time

Have great wars become less violent over time, and is there something we might identify as the long peace? We investigate statistical versions of such questions, by examining the number of battle-deaths in the Correlates of War dataset, with 95 interstate wars from 1816 to 2007. Previous research has found this series of wars to be stationary, with no apparent change over time. We develop a framework to find and assess a change-point in this battle-deaths series. Our change-point methodology takes into consideration the power law distribution of the data, models the full battle-deaths distribution, as opposed to focusing merely on the extreme tail, and evaluates the uncertainty in the estimation. Using this framework, we find evidence that the series has not been as stationary as past research has indicated. Our statistical sightings of better angels indicate that 1950 represents the most likely change-point in the battle-deaths series – the point in time where the battle-deaths distribution might have changed for the better.

Urban Concentration and Civil War

The explosion of cities and megacities has increased scholars’ and policy markers’ attention to the effects such changes might have on conflict: increasingly, urban environments may alter the nature of warfare but not necessarily the incidence of intrastate war. We argue that high levels of urban concentration—the concentration of populations in one or relatively few urban centers—increases both the likelihood of civil wars and their intensity. Urban concentration limits the ability of the state to project power across space, exacerbating grievances in rural areas, easing rebel control of territory, and enhancing their military strength. At the same time, cities become high-value loci of contestation even as urban warfare constrains conventional state military strength. The result is more symmetrical fighting producing more battle deaths. Cross-national regressions show that urban concentration exerts a crucial effect on the likelihood, nature, and intensity of intrastate warfare.

Peace for our time? Examining the effect of power-sharing on postwar rebellions

Does power-sharing promote peace? Relying on credible commitment theory, past research has predominantly focused on one aspect of this question – namely, whether power-sharing prevents the recurrence of battle violence between agreement signatories. However, this disregards a phenomenon that plagues postwar countries across the globe: battle violence perpetrated by armed groups outside of the negotiated settlement against the postwar order. To explain this violence, I argue that we have to focus on how power-sharing redistributes power and access to resources across elites in a postwar country. By determining who gets what, when, and how, power-sharing determines the state’s counterinsurgency capabilities and thus shapes incentives and constrains for extra-agreement battle violence. Personalized power-sharing, for instance, gives elites privileged access to state resources, facilitates effective counterinsurgency strategies, and thus decreases extra-agreement violence. In contrast, structural power-sharing limits elites’ access to resources and their ability to prevent armed challenges resulting in higher levels of violence. To empirically test these propositions, I combine data from the Power-Sharing Event Dataset (PSED) with the UCDP Georeferenced Event Dataset (GED) for peace agreements in Africa and Asia signed between 1989 and 2006. I analyze these data using count models, matching procedures, and correlated random effects models. The empirical results support my expectation that personalized power-sharing is associated with fewer extra-agreement battle-deaths while structural arrangements facilitate postwar rebellions. This study contributes to an improved understanding of power-sharing as a conflict resolution tool and highlights its divergent effects on actors inside and outside of peace agreements.

Why Are Some Civil Wars More Lethal Than Others? The Effect of Pro-Regime Proxies on Conflict Lethality

Previous large-N studies on conflict lethality have focused in large part either on structural factors or on the properties of key conflict protagonists – governments and rebels. This article challenges the dyadic two-actor approach to studying conflict lethality that examines exclusively the key actors of the dyad, and – on the example of pro-regime militias – hypothesises that participation of extra-state actors in civil wars can exert significant influence on battlefield lethality. It is proposed here that pro-regime militias can swell the number of combat deaths through, first of all, acting as ‘extra boots’ on the ground, providing governments with auxiliary forces and local intelligence, and enabling incumbents to launch more effective and often more deadly attacks on insurgents. Militias also affect the number of battle deaths by forcing rebels to protect their civilian support bases, which exposes insurgents to lethal government attacks. This assumption is empirically tested on 88 civil wars from 1981 to 2015 with militia presence. The findings show that the presence of pro-regime militias in civil wars is highly conducive to the incidence of high-casualty conflicts.

Predicting the costs of war

The expected cost of war is a foundational concept in the study of international conflict. However, the field currently lacks a measure of the expected costs of war, and thereby any measure of the bargaining range. In this paper, I develop a proxy for the expected costs of war by focusing on one aspect of war costs – battle deaths. I train a variety of machine learning algorithms on battle deaths for all countries participating in fatal military disputes and interstate wars between 1816 and 2007 in order to maximize out-of-sample predictive performance. The best performing model (random forest) improves performance over that of a null model by 25% and a linear model with all predictors by 9%. I apply the random forest to all interstate dyads in the Correlates of War dataverse from 1816 to 2007 in order to produce an estimate of the expected costs of war for all existing country pairs in the international system. The resulting measure, which I refer to as Dispute Casualty Expectations, can be used to fully explore the implications of the bargaining model of war, as well as allow applied researchers to develop and test new theories in the study of international relations.