Executive Constraints and Civil Conflict Onset

Do institutional constraints on a regime's executive decrease the likelihood of civil conflict onset? An unconstrained executive is free to loot state resources undermining the state's capacity to effectively deal with nascent rebellions, and may be more likely to engage in violent repression, especially in the form of indiscriminate violence. This can encourage political grievances, lead to a loss of legitimacy for the regime, and provide the opportunity for would be rebel groups to attract new members by offering protection against government violence. Furthermore, the lack of guaranteed checks to executive power may incentivise actors to avoid bargained solutions if they fear future extralegal retributions. Taken together, where there is a lack of effective constraints against the executive there may be an increased risk for the onset of civil conflict. To test this proposition I employ a bayesian latent variable model which estimates executive constraint as a latent factor derived from several manifest variables and relate it to a binary measure of civil conflict onset through a logistic regression. The primary finding is that there is a negative relationship such that the predicted probability for civil conflict is lower where there exists higher levels of executive constraints. However, this is conditional on the level of GDP per capita; for low-income country-years the relationship between executive constraints and civil conflict onset is indeterminate possibly because it is easier to recruit and mobilize fighters in such settings regardless of the overall level of executive constraints. The model, however, is a poor fit to the data meaning that the presented results should be considered tentative at best. Nonetheless, this study helps to further the work on examining specific political institutions as potential risk factors for the onset of civil conflict

Executive Constraints and Civil Conflict Onset

Do institutional constraints on a regime's executive decrease the likelihood of civil conflict onset? An unconstrained executive is free to loot state resources undermining the state's capacity to effectively deal with nascent rebellions, and may be more likely to engage in violent repression, especially in the form of indiscriminate violence. This can encourage political grievances, lead to a loss of legitimacy for the regime, and provide the opportunity for would be rebel groups to attract new members by offering protection against government violence. Furthermore, the lack of guaranteed checks to executive power may incentivise actors to avoid bargained solutions if they fear future extralegal retributions. Taken together, where there is a lack of effective constraints against the executive there may be an increased risk for the onset of civil conflict. To test this proposition I employ a bayesian latent variable model which estimates executive constraint as a latent factor derived from several manifest variables and relate it to a binary measure of civil conflict onset through a logistic regression. The primary finding is that there is a negative relationship such that the predicted probability for civil conflict is lower where there exists higher levels of executive constraints. However, this is conditional on the level of GDP per capita; for low-income country-years the relationship between executive constraints and civil conflict onset is indeterminate possibly because it is easier to recruit and mobilize fighters in such settings regardless of the overall level of executive constraints. The model, however, is a poor fit to the data meaning that the presented results should be considered tentative at best. Nonetheless, this study helps to further the work on examining specific political institutions as potential risk factors for the onset of civil conflict

The V-Dem Measurement Model: Latent Variable Analysis for Cross-National and Cross-Temporal Expert-Coded Data

The Varieties of Democracy (V-Dem) project relies on country experts who code a host of ordinal variables, providing subjective ratings of latent- that is, not directly observable- regime characteristics over time. Sets of around five experts rate each case (country-year observation), and each of these raters works independently. Since raters may diverge in their coding because of either differences of opinion or mistakes, we require systematic tools with which to model these patterns of disagreement. These tools allow us to aggregate ratings into point estimates of latent concepts and quantify our uncertainty around these point estimates. In this paper we describe item response theory models that can that account and adjust for differential item functioning (i.e. differences in how experts apply ordinal scales to cases) and variation in rater reliability (i.e. random error). We also discuss key challenges specific to applying item response theory to expert-coded cross-national panel data, explain the approaches that we use to address these challenges, highlight potential problems with our current framework, and describe long-term plans for improving our models and estimates. Finally, we provide an overview of the different forms in which we present model output.This material is based upon work supported by the National Science Foundation (SES-1423944, PI: Daniel Pemstein), Riksbankens Jubileumsfond (Grant M13-0559:1, PI: Staffan I. Lindberg), the Swedish Research Council (2013.0166, PI: Staffan I. Lindberg and Jan Teorell), the Knut and Alice Wallenberg Foundation (PI: Staffan I. Lindberg), and the University of Gothenburg (E 2013/43); as well as internal grants from the Vice-Chancellor’s office, the Dean of the College of Social Sciences, and the Department of Political Science at University of Gothenburg. Marquardt acknowledges research support from the Russian Academic Excellence Project ‘5-100.’ We performed simulations and other computational tasks using resources provided by the Notre Dame Center for Research Computing (CRC) through the High Performance Computing section and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre in Sweden (SNIC 2016/1-382, SNIC 2017/1-406 and 2017/1-68). We specifically acknowledge the assistance of In-Saeng Suh at CRC and Johan Raber and Peter Mu ̈nger at SNIC in facilitating our use of their respective systems

The Methodology of “Varieties of Democracy” (V-Dem)1

This article describes and discusses the new generation of methodological responses to measuring democracy and related issues generated by Varieties of Democracy (V-Dem). V-Dem is distinct in several regards in addition to its unique level of disaggregation, by the combination of: historical data extending back to 1900 and for a large selection among them to 1789 for many countries in the world; use of multiple, independent coders for each evaluative question; inter-coder reliability tests incorporated into a custom designed Bayesian item-response theory measurement model; provision of confidence bounds for all point estimates associated with expert-coded questions as well as for all indices; multiple indices reflecting varying theories of democracy; fully transparent aggregation procedures; and that all data are made freely available, including original coder-level judgments (exclusive of any personal identifying information)