marginal likelihood and deviance information criterion (DIC) for TVP-VARs with stochastic volatility. The proposed estimators … with stochastic volatility compared to a conventional constant coefficients VAR with homoscedastic innovations. Most of the … gains, however, appear to have come from allowing for stochastic volatility rather than time variation in the VAR …

vector autoregressive (GVAR) specification with drifting coefficients and factor stochastic volatility in the errors to model …

We propose a new variational approximation of the joint posterior distribution of the log-volatility in the context of … proposed methodology with an application of a 96-variable VAR with stochastic volatility to measure global bank network …

estimating trivariate hybrid time-varying parameter Bayesian VAR models with stochastic volatility for the three-month Treasury …

We consider structural vector autoregressions identified through stochastic volatility. Our focus is on whether a …

volatility and Student-t disturbances outperforms restricted alternatives that feature either attributes. The VAR model with …

VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine … transitory and persistent changes in volatility. The resulting density forecasts are much less sensitive to outliers in the data … the pandemic period, as well as for earlier subsamples of relatively high volatility. In historical forecasting, outlier …

The estimation of large vector autoregressions with stochastic volatility using standard methods is computationally … on a common stochastic volatility factor, we derive the posterior densities for the parameters of the resulting BVAR with … common stochastic volatility (BVAR-CSV). Under the chosen prior, the conditional posterior of the VAR coefficients features a …