This paper studies how to combine real-time forecasts from a broad range of Bayesian vector autoregression (BVAR …-term forecast horizons using both univariate and multivariate forecasting metrics. Results show that the Survey of Professional … Forecasters (SPF) provides good point forecast performance, but also that SPF forecasts perform poorly in terms of densities for …

-Wide Model (NAWM) that has been designed for use in the macroeconomic projections at the European Central Bank. The forecast … growth over the forecast evaluation period and, therefore, it tends to overestimate nominal wages. As a consequence, both the … BVAR can outperform the NAWM. - Bayesian inference ; DSGE models ; euro area ; forecasting ; open-economy macroeconomics …

beat the BVAR for a few selected maturities and forecast horizons, but they perform much worse than the BVAR in the … information contained in a large panel of yields. In particular, we use a large Bayesian Vector Autoregression (BVAR) with an … existing evidence focuses on statistical measures of forecast accuracy, we also evaluate the performance of the alternative …

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 …

forecast comparison exercise. This paper discusses how the predictive likelihood can be estimated for any subset of the … compare the density forecast performance of a DSGE model to DSGE-VARs and reduced-form linear Gaussian models. …

sufficient prior information dominates competing approaches. In this paper we evaluate the forecast performance of large BVAR in …Forecast models with large cross-sections are often subject to overparameterization leading to unstable parameter … estimates and hence inaccurate forecasts. Recent articles suggest that a large Bayesian vector autoregression (BVAR) with …

We consider forecast combination and, indirectly, model selection for VAR models when there is uncertainty about which … variables to include in the model in addition to the forecast variables. The key difference from traditional Bayesian variable … models include the forecast variables, but may otherwise have differing sets of endogenous variables. This is a difficult …