(UVAR) andBayesian (BVAR) perspective. The package includes functionalities forthe speci cation, estimation and diagnosis of …

parameter risk using Bayesian techniques. This paper uses a Bayesian Vector Autoregressive (BVAR) model for the parameters of … parameters. Forecasts can readily incorporate parameter uncertainty using the models. Bayesian Vector Autoregressive (BVAR …) models are shown to significantly improve the forecast accuracy of VAR models for mortality rates based on Australian data …

predictions of euro exchange rates leads to improvements in predictive accuracy as measured by the mean square forecast error …. While the forecasting error of the combined forecast tends to be systematically smaller than that of the individual model … significantly in terms of squared forecast errors. Direction of change statistics, on the other hand, are significantly improved by …

We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil …, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter …-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach …

the predictors. We compare the performance of the priors in density forecast of inflation allowing for constant and … forecast …

entropy to tilt one-step ahead and long-horizon VAR forecasts to match the nowcast and long-horizon forecast from the Survey … of Professional Forecasters. The results indicate meaningful gains in multi-horizon forecast accuracy relative to model …, including those that are not directly tilted but are affected through spillover effects from tilted variables. The forecast …

directional forecasts can provide a useful framework to assess the economic forecast value when loss functions (or success … directional forecast value is a readily available alternative to the commonly used squared error loss criterion. -- Directional … forecasts ; directional forecast value ; forecast evaluation ; economic forecast value ; mean squared forecast error ; mean …

This paper constructs a monthly real-time oil price dataset using backcasting and compares the forecast performance of … used to forecast the real price of oil. The results show that time-varying volatility models dominate their counterparts …