Suchergebnisse

This article introduces a new dyadic dataset measuring formal diplomatic relations. These data were coded from the Europa World Yearbook annually from 1960 to 2013 for 18,317 unique country dyads, and include the level of diplomatic representation (whether the diplomatic connection is focused on a single or multiple target countries) as well as a summary measure that captures both directed and shared dyadic level of representation. We compare the new data with data gathered previously by the Correlates of War project and find significant specific discrepancies in the period between 1970 and 1985. We then test the new data by replicating Neumayer (2008) generally validating those findings: distance, power, and ideological affinity each matter when sending and receiving formal diplomatic relations. However, using the new annual diplomatic representation data, we demonstrate a different relationship between power, affinity, and probability of diplomatic connection: dyadic foreign policy affinity is a more important driver of diplomatic exchange if both the sending and receiving countries have average relative material capabilities and matters little if one or both countries in the dyad are very powerful or very weak relative to previous model results.

AbstractPrevious research by Goldstone et al. (2010) generated a highly accurate predictive model of state-level political instability. Notably, this model identifies political institutions – and partial democracy with factionalism, specifically – as the most compelling factors explaining when and where instability events are likely to occur. This article reassesses the model's explanatory power and makes three related points: (1) the model's predictive power varies substantially over time; (2) its predictive power peaked in the period used for out-of-sample validation (1995–2004) in the original study and (3) the model performs relatively poorly in the more recent period. The authors find that this decline is not simply due to the Arab Uprisings, instability events that occurred in autocracies. Similar issues are found with attempts to predict nonviolent uprisings (Chenoweth and Ulfelder 2017) and armed conflict onset and continuation (Hegre et al. 2013). These results inform two conclusions: (1) the drivers of instability are not constant over time and (2) care must be exercised in interpreting prediction exercises as evidence in favor or dispositive of theoretical mechanisms.

AbstractQuantitative methods have been used to: (1) better predict civil conflict onset; and (2) understand causal mechanisms to inform policy intervention and theory. However, an exploration of individual conflict onset cases illustrates great variation in the characteristics describing the outbreak of civil war, suggesting that there is not one single set of factors that lead to intrastate war. In this article, we use descriptive statistics to explore persistent clusters in the drivers of civil war onset, finding evidence that some arrangements of structural drivers cluster robustly across multiple model specifications (such as young, poorly developed states with anocratic regimes). Additionally, we find that approximately one-fifth of onset cases cannot be neatly clustered across models, suggesting that these cases are difficult to predict and multiple methods for understanding civil conflict onset (and state failure more generally) may be necessary.