The Importance of Heterogeneity in Dynamic Network Models Applied to European Systemic Risk

Spatial models have been used increasingly in recent literature to describe financial and economic networks. We show that the typical lack of flexibility of these empirical models to accommodate heterogeneity and dynamic behavior of economic relationships masks important salient features in the data. This paper proposes a novel dynamic network model with heterogeneous spillover dynamics to avoid these pitfalls. We apply the model to three different datasets on Eurozone sovereign credit risk spillover during the sovereign debt crisis. We depart from earlier model set-ups by allowing network players to have their own idiosyncratic, time-varying sensitivity to other players in the network. While highly flexible, the model is still straightforward to estimate. Accounting for both heterogeneity and time-variation in financial network models turns out to be empirically important. The new model uncovers intuitive patterns that would go unnoticed in currently available homogeneous and/or static spatial network models. This includes the anchoring role of Germany and the interconnectedness of important other players during the sovereign debt crisis, such as Italy, Spain, Ireland, and Portugal. Allowing for both heterogeneity and time-variation in empirical financial network work is thus empirically relevant