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Existing works on diffusion fail to account for the incapacitating effects conflict events may have on the operational capability of the combatant sides and how these effects may determine the evolution of a conflict. I hypothesize that it is those events with losses on the state side that are likely to be associated with geo-temporal spillovers, whereas events with insurgency losses are less likely to be associated with future mayhem in their vicinity. To test my arguments, I first introduce a new, comprehensive and detailed event dataset on the long-running civil conflict in Turkey. The Turkish State–PKK Conflict Event Database (TPCONED) includes the exact date and county-level location for the fatal events of the armed conflict between the Turkish state and the rebel organization PKK since its very beginning in 1984 with detailed information on combatant casualties. I then employ a split population bi-probit model which allows me to comprehensively depict the geotemporal evolution of the conflict by acknowledging, estimating and accounting for the variation in the underlying conflict proneness across locations as a latent variable that shapes the diffusion of events. The results of the statistical analyses offer support for my hypotheses and reveal that how events evolve over space and time is conditioned by the damages suffered by the combatant sides. I demonstrate the robustness of these results on a matched sample I obtain by employing the Coarsened Exact Matching (CEM) on the data.

AbstractMany modern armed conflicts contain more than two fighting parties, or armed opposition groups that have factions within them. It is the moderates in an armed opposition that governments negotiate with. But the agreement's fate depends on the approval of all other significant actors within the opposition. We construct a dynamic model of conflict in which such an actor is to decide whether to accept a peace agreement signed by the moderates or not. Using this model we analyze the behavior of our decision maker, focusing on outcomes like the optimal settlement strategy, expected duration of the conflict, and the decision maker's expected payoff from conflict. We then determine how these outcomes are affected by changes in the conflict environment. Finally, we extend our model to analyze the implications of commitment problems, and the possibility that the conflict ends with military victory of either side.