We introduce a Bayesian approach to model assessment in the class of graphical vector autoregressive (VAR) processes. Due to the very large number of model structures that may be considered, simulation based inference, such as Markov chain Monte Carlo, is not feasible. Therefore, we derive an...

This is a simulation-based warning note for practitioners who use the M GLS MGLS unit root tests in the context of structural change using different selection lag length criteria. With T=100 T=100 , we find severe oversize problems when using some criteria, while other criteria produce an...

We provide a simulation smoother to a exible state-space model with lagged states and lagged dependent variables. Qian (2014) has introduced this state-space model and proposes a fast Kalman filter with time-varying state dimension in the presence of missing observations in the data. In this...