evidence of nonlinearity and/or higher moment influences which seriously questions the habit of forecast and model evaluation … significance of the differences with our more general measures of forecast performance …

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 …

forecast models. This process is intended to serve as a general guideline for energy economists and practitioners who need to … apply sophisticated forecast models. …

-switching models, and forecast combination to predict the dynamics in the S&P 500. First, we aggregate the weekly information of 115 …

forecasts and probabilistic prediction intervals for demographic parameters in addition. Age-sex specific population forecast …-specific population forecast using the cohort-component method. The consequence for the German pension system is discussed. To maintain …

hierarchically by export destination and product category. We apply existing state of the art methods in forecast reconciliation and … forecasts, reconciliation also leads to improvements in forecast accuracy. …

interpreting economic forecasts. This framework's value is illustrated by re-examining mean square forecast errors from dynamic … as nonlinearity bias and the possible nonmonotonicity and nonexistence of mean square forecast errors in isolation from …

interpreting economic forecasts. This framework's value is illustrated by re-examining mean square forecast errors from dynamic … such as nonlinearity bias and the possible nonmonotonicity and nonexistence of mean square forecast errors in isolation …

accuracy is assessed through in-sample forecast evaluation across various data sub-samples. This paper also discusses how these …