A Global Model for Forecasting Political Instability

By Jack Goldstone, R. Bates, David L. Epstein, T. Gurr, M. Lustik, Monty G. Marshall, Jay Ulfelder, Mark Woodward. 2010

806 citations recorded by the source corpus.

Examining onsets of political instability in countries worldwide from 1955 to 2003, we develop a model that distinguishes countries that experienced instability from those that remained stable with a two-year lead time and over 80% accuracy. Intriguingly, the model uses few variables and a simple specification. The model is accurate in forecasting the onsets of both violent civil wars and nonviolent democratic reversals, suggesting common factors in both types of change. Whereas regime type is typically measured using linear or binary indicators of democracy/autocracy derived from the 21-point Polity scale, the model uses a nonlinear five-category measure of regime type based on the Polity components. This new measure of regime type emerges as the most powerful predictor of instability onsets, leading us to conclude that political institutions, properly specified, and not economic conditions, demography, or geography, are the most important predictors of the onset of political instability.

Subfields: Demography, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/5642a582b9a9a238e0211ca85e796e9238cd6057

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Citations in the corpus

Foreign Aid Shocks as a Cause of Violent Armed Conflict (2011, neutral): “Perhaps surprisingly, we find that in the presence of the other controls, GDP per capita, population, and mountainous terrain have no apparent effect (in agreement with Goldstone et al. [2010]), although it is probably inappropriate to interpret the coefficients for any of the control variables caus”
Can Structural Conditions Explain the Onset of Nonviolent Uprisings? (2017, background): “Following Goldstone et al. (2010), regimes that hold competitive elections (EXREC 7) and have competitive political participation (PARCOMP 1⁄4 0 or PARCOMP > 2) are identified as democracies and all other regimes are not.”
Seven deadly sins of contemporary quantitative political analysis (2014, background): “’ This is a perfectly understandable human impulse – if you can’t make the goal with frequentist models (Ward, Greenhill & Bakke, 2010), move the goal posts – though less understandable in this context since it is quite straightforward to develop successful predictive models of political conflict be”
Square Pegs in Round Holes: Inequalities, Grievances, and Civil War (2014, neutral): “…models of civil war and the aspirations of forecasting conflict through efforts such as the Political Instability Task Force project (see Goldstone et al. 2010; Ward, Greenhill and Bakke 2010), we wish to consider whether more theoretically grounded measures and disaggregated…”
The practice and study of civil resistance (2013, background): “4 But see the important policy-relevant work of Goldstone et al. (2010) on political instability and state breakdown.”
News events prediction using Markov logic networks (2018, background): “[24] developed a model for identifying countries that experienced instability, by examining onsets of political instability in countries.”
Political order, development and social violence (2012, methodology): “In line with recent developments in the conflict literature, we classify countries in our sample according to two characteristics of their political-institutional arrangements: the terms of executive recruitment and the degree of political participation (Goldstone et al., 2010). Countries with non-c”
Autocratic Elections: Stabilizing Tool or Force for Change? (2017, background): “, 2001; Goldstone et al., 2010). One common way to mix autocratic with nominally democratic institutions is through introducing multi-party elections, with a minimum semblance of competition, in otherwise autocratic regimes. However, Knutsen and Nyg̊ard (2015) show that such institutional combinatio”
Economic Development, Violent Leader Removal, and Democratization (2012, background): “Economic development reduces violent political instability in both democracies and dictatorships, particularly the use of violence against regime leaders (Feng 1997; Goldstone et al. 2010; Jones and Olken 2009; Londregan and Poole 1990; Sanders 1981).4 Looking at 1950–82, Londregan and Poole (1990) ”
Comparing Random Forest with Logistic Regression for Predicting Class-Imbalanced Civil War Onset Data (2016, background): “2014; Clayton and Gleditsch 2014), interstate disputes (Gleditsch and Ward 2012), and political instability (Goldstone et al. 2010).”