Can Forecasting Performance of the Bayesian Factor-Augmented VAR be Improved by Considering the Steady-State? An application to Swedish inflation
This paper investigates whether the forecasting performance of Bayesian factor-augmented VAR (BFAVAR) models can be improved by incorporating an informative prior on the steady-state of the time series in the system. The BFAVAR model is compared to the extended steady-state BFAVAR in an application to forecasting Swedish inflation, making use of data from 1996 to 2016. Results show that the out-of
