Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/87691 
Year of Publication: 
2013
Series/Report no.: 
CFS Working Paper No. 2013/11
Publisher: 
Goethe University Frankfurt, Center for Financial Studies (CFS), Frankfurt a. M.
Abstract: 
The U.S. Energy Information Administration (EIA) regularly publishes monthly and quarterly forecasts of the price of crude oil for horizons up to two years, which are widely used by practitioners. Traditionally, such out-of-sample forecasts have been largely judgmental, making them difficult to replicate and justify. An alternative is the use of real-time econometric oil price forecasting models. We investigate the merits of constructing combinations of six such models. Forecast combinations have received little attention in the oil price forecasting literature to date. We demonstrate that over the last 20 years suitably constructed real-time forecast combinations would have been systematically more accurate than the no-change forecast at horizons up to 6 quarters or 18 months. MSPE reduction may be as high as 12% and directional accuracy as high as 72%. The gains in accuracy are robust over time. In contrast, the EIA oil price forecasts not only tend to be less accurate than no-change forecasts, but are much less accurate than our preferred forecast combination. Moreover, including EIA forecasts in the forecast combination systematically lowers the accuracy of the combination forecast. We conclude that suitably constructed forecast combinations should replace traditional judgmental forecasts of the price of oil.
Subjects: 
forecast combination
real-time data
model misspecification
structural change
oil price
JEL: 
Q43
C53
E32
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
374.31 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.