This paper aims to illustrate how a Mixed-Cross-Section Global Vector Autoregressive (MCS-GVAR) model can be set up and solved for the purpose of forecasting and scenario simulation. The application involves two cross-sections: sovereigns and banks for which we model their credit default swap spreads. Our MCS-GVAR comprises 23 sovereigns and 41 international banks from Europe, the US and Japan. The model is used to conduct systematic shock simulations and thereby compute a measure of spill-over potential for within and across the group of sovereigns and banks. The results point to a number of salient facts: i) Spill-over potential in the CDS market was particularly pronounced in 2008 and more recently in 2011-12; ii) while in 2008 contagion primarily went from banks to sovereigns, the direction reversed in 2011-12 in the course of the sovereign debt crisis; iii) the index of spill-over potential suggests that the system of banks and sovereigns has become more densely connected over time. Should large shocks of size similar to those experienced in the early phase of the crisis hit the system in 2011/2012, considerably more pronounced and more synchronized adverse responses across banks and sovereigns would have to be expected.
Contagion forecasting and simulation Global macroeconometric modeling macro-financial linkages models with panel data network analysis spill-overs