  In this paper we propose to extend the separable temporal exponential random
graph model (STERGM) to account for time-varying network- and actor-specific
effects. Our application case is the network of international major
conventional weapons transfers, based on data from the Stockholm International
Peace Research Institute (SIPRI). The application is particularly suitable
since it allows to distinguish the potentially differing driving forces for
creating new trade relationships and for the endurance of existing ones. In
accordance with political economy models we expect security- and
network-related covariates to be most important for the formation of transfers,
whereas repeated transfers should prevalently be determined by the receivers'
market size and military spending. Our proposed modelling approach corroborates
the hypothesis and quantifies the corresponding effects. Additionally, we
subject the time-varying heterogeneity effects to a functional principal
component analysis. This serves as exploratory tool and allows to identify
countries that stand out by exceptional increases or decreases of their
tendency to import and export weapons.
