The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast …, including the question of whether financial market information helps forecast the real price of oil in physical markets. An … and statistically significant real-time improvements in forecast accuracy. The preferred MIDAS model reduces the MSPE by …

model forecast should become the benchmark for forecasting horse races. We compare the real-time forecasting accuracy of the … forecast benchmark when evaluating DSGE models. Indeed,low-dimensional unrestricted AR and VAR forecasts may forecast more …

forecasts, however, are obtained when allowing the forecast combinations to vary across forecast horizons. While the latter … no-change forecast and its directional accuracy as high as 73%. Our results are robust to alternative oil price measures … and apply to monthly as well as quarterly forecasts. We illustrate how forecast pooling may be used to produce real …

specifications involving product spreads and compare these models to the no-change forecast of the real price of oil. We show that …

combination weights, we compute optimal weights which minimize the mean square forecast error (MSFE) in the case of point …

benefits of allowing for time variation in VAR model parameters and of constructing forecast combinations. We conclude that …

than analysts' consensus forecasts, reducing their forecast errors by 15% to 30% on average, depending on forecast horizon. …