International conflict and strategic games
The pervasiveness of international conflict makes of it one of the main topics of discussionamong IR scholars. The discipline has extensively attempted to model the conditions andsettings under which armed conflict emerges, at sometimes resorting to formal models as toolsto generate hypotheses and predictions. In this paper, I analyse two distinct approaches toformal modelling in IR: one that fits data into mathematical models and another that derivesstatistical equations directly from a model’s assumption. In doing so, I raise the followingquestion: how should maths and stats be linked in order to consistently test the validity offormal models in IR? To answer this question, I scrutinise James Fearon’s audience costsmodel and Curtis Signorino’s strategic interaction game, highlighting their mathematicalassumptions and implications to testing formal models. I argue that Signorino’s approachoffer a more consistent set of epistemological and methodological tools to model testing,for it derives statistical equations that respect a model’s assumptions, whereas the data-fitapproach tends to ignore such considerations.