In this paper, we extend the standard Gaussian stochastic-volatility Bayesian VAR by employing the generalized hyperbolic skew Student’s t distribution for the innovations. Allowing the skewness parameter to vary over time, our specification permits flexible modelling of innovations in terms of both fat tails and – potentially dynamic – asymmetry. In an empirical application using US data on industrial production, consumer prices and economic policy uncertainty, we find support – although to a moderate extent – for time-varying skewness. In addition, we find that shocks to economic policy uncertainty have a negative effect on both industrial production growth and CPI inflation.
Hoang Nguyen, Stepan Mazur and Pär Österholm acknowledge financial support from the project ”Improved Economic Policy and Forecasting with High-Frequency Data” (Dnr: E47/22) funded by the Torsten Söderbergs Foundation. Stepan Mazur also acknowledges financial support from the internal research grants at Örebro University.