Post-Cold War civil conflict and the role of history and religion: A stochastic search variable selection approach

Despite colossal economic and human losses caused by conflict and violence, designing effective policies to avoid conflict remains challenging. While the literature has proposed a voluminous set of candidate predictors, their robustness is questionable and model uncertainty masks the true drivers of conflicts and wars. Considering a comprehensive set of 34 potential determinants in 175 post-Cold-War countries, we employ stochastic search variable selection (SSVS) to sort through all 234 possible models to address model uncertainty. We find past conflict constitutes the most powerful predictor of current conflict: Path dependency matters. Also, larger shares of Jewish, Muslim, or Christian citizens are associated with increased conflict, while economic and political factors remain less relevant than colonial origin and religion. Our results help future researchers and policymakers by inching towards causality and providing a standard set of covariates that need to be accounted for in designing any relevant policies.