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.

现有的扩散工作未能考虑到冲突事件可能对战斗人员方面的作战能力造成的丧失能力的影响，以及这些影响如何决定冲突的发展。我假设是那些在美国方面造成损失的事件很可能与地理时空溢出有关，而具有叛乱性损失的事件则不太可能与附近的未来混乱有关。为了检验我的论点，我首先介绍一个关于土耳其长期内战的新的，全面而详细的事件数据集。土耳其国家PKK冲突事件数据库（TPCONED）包含土耳其国家与反叛组织PKK自1984年成立以来发生的武装冲突致命事件的确切日期和县级位置，并提供了有关战斗人员伤亡的详细信息。然后，我采用了分裂人口双概率模型，该模型使我能够通过确认，估计和解释潜在的跨地点潜在冲突倾向的变化，将其作为塑造事件扩散的潜在变量，来全面描述冲突的地时演化。统计分析的结果为我的假设提供了支持，并揭示了事件如何在空间和时间上演变取决于战斗员双方遭受的损害。