I use Bayesian VARs to forecast global temperatures anomalies until the end of the XXI century by exploiting their … cointegration with the Joint Radiative Forcing (JRF) of the drivers of climate change. Under a ‘no change’ scenario, the most … favorable median forecast predicts the land temperature anomaly to reach 5.6 Celsius degrees in 2100. Forecasts conditional on …

-GVAR models for the one- and four-quarter ahead forecast horizon for standard macroeconomic variables (real GDP, inflation, the … practically all variables and at both forecast horizons. The comparison of prior elicitation strategies indicates that the use of … finding is confirmed by density forecast measures, for which the predictive ability of the SSVS prior is the best among all …

frequency information into one model. We consider subsample averaging, bootstrap averaging, forecast averaging methods for the … forecasting the daily S&P 500 index return quantile (Value-at-Risk or VaR is simply the negative of it), using high …-frequency information is beneficial, often substantially and particularly so, in forecasting downside risk. Our empirical results show that …