Most quantitative assessments of civil conflict draw on yearly country-level data to determine a baseline hazard of conflict onset. The first problem with such analyses is that they assume that civil conflicts are distributed uniformly throughout the country. This is rarely the case; most intrastate armed conflicts take place in the periphery of the country, well away from the capital and often along international borders. The second problem with most quantitative analyses of conflict is that they ignore factors associated with the precipitation of violence, such as elections
and natural disasters and other trigger mechanisms. Given that baseline hazards are relatively static, most of the temporal variation in risk is associated with such precipitating factors. Analysts fail to disaggregate temporally as well as spatially.
To more adequately assess the base-line hazard and specific population at risk of armed conflict, geo-referenced data from Asia are analyzed with simulation models of both national and sub-national conflict. The two models are integrated to generate maps of the predicted risk of armed conflict, within and across countries. Aspects of social, economic and political exclusion as well as endemic poverty and physical geography are featured as the principal indicators of latent conflict. A closer presentation of the results for Nepal and the Philippines serves to highlight the advantages of focusing on the location of conflict. This paper attempts to address these two problems by identifying these precipitating factors in combination with subnational data makes it possible to explain both the timing and location of civil conflict.