Aktuelle Publikationen

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Thus far, researchers working on ethnicity and resources as determinants of civil conflict have operated largely independently of each other. While there is plenty of evidence that natural resources may spur armed conflict, empirical evidence for the nexus between ethnic fractionalization and conflict remains inconclusive. Some authors conclude that ethnically fractionalized societies are actually spared from intrastate violence. Others find either a positive relationship or none at all between ethnic fragmentation and internal conflict. In this context, this paper serves two purposes: first, it shows that salience-based fractionalization indices are associated with a higher risk of ethnic conflict onset; second, it finds evidence that oil further increases the conflict potential within fractionalized countries. The combination of oil and a shared identity seems to help overcome the collective action problems associated with rebellion, by providing recruitment pools, strong motives and the necessary financial means for insurgency. Employing logit models for pooled time-series cross-sectional data, our quantitative analysis shows that various ethnic fractionalization indicators are robustly linked to a substantially increased risk of ethnic armed conflict onset in a subset of oil-abundant countries.

Traditional theories of economic voting focusing on retrospective evaluations about the economy have been shown to fare as expected in the Greek context. Nevertheless, the current economic crisis in Greece has not only challenged the structure of the party system but also our understanding of how economic voting works in such extraordinary situations. Drawing from the context of the May 2012 parliamentary election in Greece we argue that economic voting in times of an economic turmoil can be conceptualized as a position issue. Our findings suggest that economic voting conceptualized in terms of position taking does a good job in explaining vote intentions between the incumbent versus the opposition when valence models would have otherwise faced serious challenges in doing so.

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The quantitative study of violent conflict and its mechanisms has in recent years greatly benefited from the availability of detailed event data. With a number of highly visible studies both in the natural sciences and in political science using such data to shed light on the complex mechanisms underlying violent conflict, researchers have recently raised issues of systematic (reporting) biases. While many sources of bias are qualitatively known, biases in event data are usually not studied with quantitative methods. In this study we focus on a unique case - the conflict in Iraq - that is covered by two independently collected datasets: Iraq Body Count (IBC) reports of civilian casualties and Significant Action (SIGACT) military data. We systematically identify a number of key quantitative differences between the event reporting in the two datasets and demonstrate that even for subsets where both datasets are most consistent at an aggregate level, the daily time series and timing signatures of events differ significantly. This suggests that at any level of analysis the choice of dataset may substantially affect any inferences drawn, with attendant consequences for a number of recent studies of the conflict in Iraq. We further outline how the insights gained from our analysis of conflict event data have broader implications for studies using similar data on other social processes.

Die Beschreibung und Erklärung von Institutionenwandel ist eine zentrale Herausforderung des neoinstitutionalistischen Forschungsprogramms. Dieser Aufsatz diskutiert zentrale konzeptionelle, methodische und forschungspraktische Probleme bei der Analyse des Wandels formaler Institutionen. Konzeptionell werden vier Analyseansätze diskutiert, die sich hinsichtlich des Trade-Offs zwischen Breite und analytischer Tiefe unterscheiden. Methodisch entwickeln wir Werkzeuge, durch die sich die Identifikation von Änderungen in formalen Regeln weitgehend automatisieren und valide quantitative Indikatoren des Umfangs von Textänderungen erheben lassen. Wir demonstrieren die praktische Anwendung der Analyseansätze und Werkzeuge an Daten zum Wandel parlamentarischer Regeln in europäischen Demokratien und diskutieren weitere Anwendungsfelder.

What is the role of social interactions in the creation of price bubbles? Answering this question requires obtaining collective behavioural traces generated by the activity of a large number of actors. Digital currencies offer a unique possibility to measure socio-economic signals from such digital traces. Here, we focus on Bitcoin, the most popular cryptocurrency. Bitcoin has experienced periods of rapid increase in exchange rates (price) followed by sharp decline; we hypothesize that these fluctuations are largely driven by the interplay between different social phenomena. We thus quantify four socio-economic signals about Bitcoin from large datasets: price on online exchanges, volume of word-of-mouth communication in online social media, volume of information search and user base growth. By using vector autoregression, we identify two positive feedback loops that lead to price bubbles in the absence of exogenous stimuli: one driven by word of mouth, and the other by new Bitcoin adopters. We also observe that spikes in information search, presumably linked to external events, precede drastic price declines. Understanding the interplay between the socio-economic signals we measured can lead to applications beyond cryptocurrencies to other phenomena that leave digital footprints, such as online social network usage.