Mercenaries in civil wars, 1950-2000

"This paper investigates the determinants of mercenary participation in civil wars during the second half of the 20th century. The authors present a new dataset on mercenary activities and use it to test hypotheses derived from a simple game-theoretic model of demand and supply in the market for force. They find that higher GDP and diamond deposits in a country increase the probability that mercenaries fight in an internal war. Military interventions also increase the risk of mercenary involvement, with the exception of UN interventions." (author's abstract)"Diese Arbeit untersucht die Determinanten von Söldneraktivitäten in Bürgerkriegen in der zweiten Hälfte des 20ten Jahrhunderts. Die Autoren präsentieren einen neuen Datensatz über Söldneraktivitäten und verwenden ihn, um Hypothesen zu testen, die aus einem einfachen spieltheoretischen Modell von Angebot und Nachfrage auf dem Söldnermarkt hergeleitet werden. Die Hauptergebnisse sind wie folgt: Ein höheres BIP pro Kopf und Diamantenvorkommen in einem Land erhöhen die Wahrscheinlichkeit, dass Söldner in einem Bürgerkrieg kämpfen. Militärische Interventionen steigern ebenfalls das Risiko von Söldnern, mit Ausnahme von UN Interventionen." (Autorenreferat

Who Joins and Who Fights? Explaining Tacit Coalition Behavior among Civil War Actors

Which armed organizations form coalitions despite the inherent difficulties of cooperation in civil wars? We introduce the concept of tacit coalitions, which pertains to strategic and informal coalition behavior between civil war actors to address this puzzle. Our theoretical model of coalition behavior takes in theater-wide conflict behavior to allow for predictions that coalitions are more likely to form. It provides novel insights into the way military synergies within potential coalitions affect the trade-off between pooling resources and worrying about the division of gains. The empirical section finds considerable support for our theoretical argument that actors are more likely to engage in tacit coalition behavior (1) if potential coalitions are power balanced, (2) if joint capability of potential coalitions is not too high, and (3) when coalitions can unlock synergies. In addition, it produces evidence for the important role of geography and ethnic ties in generating military synergies

Multiple Imputation Using Gaussian Copulas

Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use method for generating multiple imputations using a Gaussian copula. The Gaussian copula for multiple imputation (Hoff, 2007) allows scholars to attain estimation results that have good coverage and small bias. The use of copulas to model the dependence among variables will enable researchers to construct valid joint distributions of the data, even without knowledge of the actual underlying marginal distributions. Multiple imputations are then generated by drawing observations from the resulting posterior joint distribution and replacing the missing values. Using simulated and observational data from published social science research, we compare imputation via Gaussian copulas with two other widely used imputation methods: MICE and Amelia II. Our results suggest that the Gaussian copula approach has a slightly smaller bias, higher coverage rates, and narrower confidence intervals compared to the other methods. This is especially true when the variables with missing data are not normally distributed. These results, combined with theoretical guarantees and ease-of-use suggest that the approach examined provides an attractive alternative for applied researchers undertaking multiple imputations

Ethnicity, the State, and the Duration of Civil War

Previous research has focused primarily on how ethnicity may trigger civil war, and its effect on conflict duration remains disputed. Rather than treating conflict as a direct consequence of ethnic cleavages, the authors argue that ethnicity per se does not affect civil war duration. Instead, its effect depends on its relationship to political institutions. They employ a dyadic approach that emphasizes the political context in which both government leaders and nonstate challengers can capitalize on the ascriptive nature of ethnicity. They show that although states can initially benefit from politicizing ethnic relations, once violent conflict breaks out, such policies may backfire on the government and make it difficult for incumbent governments to accept settlements that could terminate conflicts. Past policies of ethnic exclusion also benefit rebel organizations fighting the government, since the resulting grievances increase collective group solidarity and render individual fighters more cost tolerant. Using a new data set that codes the nexus between rebel organizations and ethnic groups, as well as information on ethnopolitical exclusion, the authors find considerable support for their propositions.</jats:p

Antigovernment networks in civil conflicts : how network structures affect conflictual behavior

In this article, we combine a game-theoretic treatment of public goods provision in networks with a statistical network analysis to show that fragmented opposition network structures lead to an increase in conflictual actions. Current literature concentrates on the dyadic relationship between the government and potential challengers. We shift the focus toward exploring how network structures affect the strategic behavior of political actors. We derive and examine testable hypotheses and use latent space analysis to infer actors’ positions vis-à-vis each other in the network. Network structure is examined and used to test our hypotheses with data on conflicts in Thailand from 2001 to 2010. We show the influential role of network structure in generating conflictual behavior

Learning from the past and stepping into the future : toward a new generation of conflict prediction

Developing political forecasting models not only increases the ability of political scientists to inform public policy decisions, but is also relevant for scientific advancement. This article argues for and demonstrates the utility of creating forecasting models for predicting political conflicts in a diverse range of country settings. Apart from the benefit of making actual predictions, we argue that predictive heuristics are one gold standard of model development in the field of conflict studies. As such, they shed light on an array of important components of the political science literature on conflict dynamics. We develop and present conflict predictions that have been highly accurate for past and subsequent events, exhibiting few false-negative and false-positive categorizations. Our predictions are made at the monthly level for 6-month periods into the future, taking into account the social–spatial context of each individual country. The model has a high degree of accuracy in reproducing historical data measured monthly over the past 10 years and has approximately equal accuracy in making forecasts. Thus, forecasting in political science is increasingly accurate. At the same time, by providing a gold standard that separates model construction from model evaluation, we can defeat observational research designs and use true prediction as a way to evaluate theories. We suggest that progress in the modeling of conflict research depends on the use of prediction as a gold standard of heuristic evaluation

Networked international politics

Network theory and methods are becoming increasingly used to study the causes and consequences of conflict. Network analysis allows researchers to develop a better understanding of the causal dynamics and structural geometry of the complex web of interdependencies at work in the onset, incidence, and diffusion of conflict and peace. This issue features new theoretical and empirical research demonstrating how properly accounting for networked interdependencies has profound implications for our understanding of the processes thought to be responsible for the conflict behavior of state and non-state actors. The contributors examine the variation in networks of states and transnational actors to explain outcomes related to international conflict and peace. They highlight how networked interdependencies affect conflict and cooperation in a broad range of areas at the center of international relations scholarship. It is helpful to distinguish between three uses of networks, namely: (1) as theoretical tools, (2) as measurement tools, and (3) as inferential tools. The introduction discusses each of these uses and shows how the contributions rely on one or several of them. Next, Monte Carlo simulations are used to illustrate one of the strengths of network analysis, namely that it helps researchers avoid biased inferences when the data generating process underlying the observed data contains extradyadic interdependencies. </jats:p

STEPPING INTO THE FUTURE: THE NEXT GENERATION OF CRISIS FORECASTING MODELS

Abstract. Developing political forecasting models is not only relevant for scientific advancement, but also increases the ability of political scientists to inform public policy decisions. Taking this perspective seriously, the International Crisis Early Warning System (ICEWS) was developed under a DARPA initiative to provide predictions of international crisis, domestic crisis, rebellion, insurgency, and ethnic violence (Events of Interest/EOIs) in about two-dozen countries in the US PACOM Area of Responsibility. As part of a larger project coordinated by Lockheed Martin Advanced Technology Labs, a team at Duke University created a series of geographically informed statistical models for these EOIs. The generated predictions have been highly accurate, with few false negative and positive categorizations. Predictions are made at the monthly level for three months periods into the future. The major variables to generate the predictions include 1) event data culled from FACTIVA reports, 2) structural political characteristics of states, 3) economic characteristics of states, and 4) contextual features of each country. These later characteristics take into account the social-spatial context of each individual country, thereby allowing the models to escape the limitations of treating each country as independent from the influence of events and forces in nearby countries. For each EOI we present a separate prediction model, which captures the unique dynamics of each outcome. Each of these models has a high degree of accuracy in reproducing historical data measured monthly over the past 10 years, and is approximately equally accurate in making three-month forecasts out-of-sample

Endogenous networks and international cooperation

The rise of social network analyses in the social sciences has allowed empirical work to better account for interdependencies among actors and among their actions. However, this work has been, to a large extent, descriptive: it has treated these actions as exogenous and immutable. In many cases these networks describe actions like alliance formation or trade phenomena that are the outcome variables for programs of social scientific research. In this paper, I attempt to account for both interdependencies and the endogenous nature of networks by incorporating formal theory; helping answer the question of how these networks arise by looking at the incentives of actors to form links with each other. I discuss the appropriate solution concept for a network formation game, and present an algorithm for finding the equilibrium of these networks computationally as well as ways to compare the theoretical networks to observed ones in order to evaluate the fit of the theory. I apply these methods to the study of international cooperation a subject where both the interdependencies and purposive nature of actors must be accounted for. The theoretical network is able to reproduce a number of important observed characteristics. Still, there are more factors that must be accounted for if we want to understand how the network of international cooperation is formed