EViews 8 introduced Bayesian VARs to EViews, but due to their poularity, version 11 has completely reworked the calculation engine.
In particular, EViews now offers a choice of priors of:
- Independent normal-Wishart.
- Giannone, Lenza and Primiceri.
All priors allow options for choice of initial covariance matrix calculation, and for the inclusion of the dummy observation priors.
The VAR forecasting and impulse response engines have also been expanded to allow for Bayesian sampling when performing these procedures from Bayesian VARs.
MIXED FREQUENCY VARS EViews 11 now supports estimation of mixed-frequency VARs using the Ghysels (2016) U-MIDAS and Bayesian estimation approaches.
With Bayesian mixed-frequency VAR estimation, the VAR forecasting and impulse response engines allow simulation through an MCMC algorthim.
Expanding upon the popular single equation simple and Markov switching models added in EViews 9, EViews 11 EViews 11 offers support for estimation of nonlinear VAR models where the nonlinearity is the result of simple and Markov switching.