Recent articles suggest that a Bayesian vector autoregression (BVAR) with shrinkage is a good forecast device even when … the number of variables is large. In this paper we evaluate different variants of the BVAR with respect to their forecast … optimally does not improve forecast accuracy; (e) all variants except the large BVAR tend to be well calibrated for inflation …

model a more difficult task under the VARMA specification, our analysis, based on forecast error and spectral decompositions …

across all variables and forecast horizons, the two-sector model provides a far better fit to the data. Some other key … results are first, that Hicks-neutral shocks explain a greater share of output and consumption variation at shorter-forecast …

and demand. Supply disruptions turn out to be a bigger factor in historical oil price movements and inventory accumulation … a significant lag, whereas shocks to oil demand do not …

evidence and economic theory, the substantive results of earlier oil market studies are reaffirmed. We also refute BH’s claim …

We investigate the effect of forecast uncertainty in a cointegrating vector error correction model for Switzerland …. Forecast uncertainty is evaluated in three different dimensions. First, we investigate the effect on forecasting performance of … whether using weighting schemes from the machine learning literature improves the average forecast. Compared to equal weights …

. It builds on the idea that the import demand of the domestic country should be reflected in the expected export …