characteristic of volatility dynamics, making it a suitable choice for volatility forecasting. However, its complex structure … the RPDV model a competitive tool for volatility forecasting.To achieve this objective, the article proposes an innovative …

variables in the model, rather than just on future paths as it is usually done in the conditional forecasting literature. The … forecasting densities of a BVAR and a DSGE model on information about the marginal densities of future oil prices. The results …-inflation over the considered forecasting horizon. Finally, a real-time forecasting exercise yields that introducing market …

features of observed data and of forecasting oneperiod ahead output-gap and investment with a remarkable degree of accuracy. …

COVID-19 observations and discusses their impact on prior calibration for inference and forecasting purposes. It shows that … volatility. For forecasting, the choice among outlier-robust error structures is less important, however, when a large cross …

explores various specifications of decompositions and various forecasting experiments. The result from these horse-races is … for richer forecasting specifications, the paper shows, using Bayesian model averaging techniques (BMA), that the …