"Turning points" in the Iraq conflict: Reversible jump Markov chain Monte Carlo in political science

We consider and explore structural breaks in a day-by-day time series of civilian casualties for the current Iraq conflict: an undertaking of potential interest to scholars of international relations, comparative politics, and American politics. We review Bayesian change-point techniques already used by political methodologists before advocating and briefly describing the use of reversible-jump Markov chain Monte Carlo techniques to solve the estimation problem at hand. We find evidence of four change points, all associated with increasing violence, approximately contemporaneous with some important state building events. We conclude with a discussion of avenues for future research.