Dyadic effects to a large extent account for the difficulty of explaining and predicting international conflict. In this study, I derive a statistical model to estimate unobserved dyadic effects in the dyadic analysis of conflict. The proposed model employs a hierarchical modeling approach to estimate dyadic effects, thereby avoiding the problems caused by the use of fixed effects models. Furthermore, it simultaneously addresses the important sample selection issue of identifying relevant dyads. I show that the estimation of dyadic effects significantly improves the model fit and generates several interesting findings. Substantively, this study makes an important contribution to the empirical evaluation of the Kantian peace. It argues that international organizations increase the likelihood of conflict of interest between member states but reduce the probability of militarized conflict. I demonstrate that the positive coefficient of international organizations in Oneal and Russett (1999) is biased in the positive direction. When the proposed statistical model is used, international organizations, together with trade and democracy, reduce the probability of conflict.
All Science Journal Classification (ASJC) codes
- Political Science and International Relations
- Dyadic effects
- Kantian peace
- hierarchical model
- international organizations
- split population model