Is There More Violence in the Middle?

Abstract

Is there more violence in the middle? Over 100 studies have analyzed whether violent outcomes such as civil war, terrorism, and repression are more common in regimes that are neither full autocracies nor full democracies, yet findings are inconclusive. While this hypothesis is ultimately about functional form, existing work uses models in which a particular functional form is assumed. Existing work also uses arbitrary operationalizations of “the middle.” This article aims to resolve the empirical uncertainty about this relationship by using a research design that overcomes the limitations of existing work. We use a random forest‐like ensemble of multivariate regression and classification trees to predict multiple forms of conflict. Our results indicate the specific conditions under which there is or is not more violence in the middle. We find the most consistent support for the hypothesis with respect to minor civil conflict and no support with respect to repression.

Multinational Corporations and Political Violence: Trends and Forecasts

“…Random forests have been used and shown to be effective in several conflict forecasting applications (Hegre et al, 2019;Jones and Lupu, 2018;Colaresi and Mahmood, 2017;Hill and Jones, 2014). In addition to forecasting well, the algorithm can detect non-linear relationships in the data, and non-linearities are a well-known feature in conflict models (Muchlinski et al, 2016;Lagazio and Marwala, 2006;Beck et al, 2000).…”

Leftist Insurgency in Democracies

“…Finkel and Gehlbach (2020) advance a related proposition, arguing that revolt follows reform when local state actors undermine reform efforts and citizens turn to violence because of unmet expectations. There is an ongoing debate about civil war onset and repression in democracies over whether “anocracies” and other regime types that mix aspects of democracy and autocracy are most prone to political violence (Hegre et al, 2001; Jones and Lupu, 2018; Vreeland, 2008); advocates of the claim that violence is most likely in hybrid/anocratic regimes make arguments that overlap with this hypothesis.…”

What Drives State-Sponsored Violence?: Evidence from Extreme Bounds Analysis and Ensemble Learning Models

“…Unlike parametric methods such as ordinary least squares or logistic regressions, the analyst does not have to impose any distributional form to the data-generating process. As a result, random forest is able to effectively uncover complex, nonlinear interaction effects in the data without prespecification (Jones and Linder 2015;Jones and Lupu 2018).…”

“…For discussion on these important differences in conceptualisation see (Straus 2007;Finkel and Straus 2012) inants of state-sponsored atrocities. Our approach is similar to Hegre and Sambanis (2006) seminal analysis on the causes of civil war onset, but we provide additional tests to verify whether complex interactions and nonlinearities are driving the statistical results (Bell 2015;Jones and Linder 2015;Jones and Lupu 2018;Muchlinski et al 2015). In conducting this analysis, we address three debates in the mass violence literature:…”