Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach

Posted: 24 Jul 2013

See all articles by Christiane Baumeister

Christiane Baumeister

University of Notre Dame; National Bureau of Economic Research (NBER); Centre for Economic Policy Research (CEPR)

Lutz Kilian

University of Michigan at Ann Arbor - Department of Economics; Centre for Economic Policy Research (CEPR)

Date Written: July 2013

Abstract

The U.S. Energy Information Administration regularly publishes short-term forecasts of the price of crude oil. Traditionally, such out-of-sample forecasts have been largely judgmental, making them difficult to replicate and justify, and not particularly successful when compared with naïve no-change forecasts, as documented in Alquist et al. (2013). Recently, a number of alternative econometric oil price forecasting models has been introduced in the literature and shown to be more accurate than the no-change forecast of the real price of oil. We investigate the merits of constructing real-time forecast combinations of six such models with weights that reflect the recent forecasting success of each model. Forecast combinations are promising for four reasons. First, even the most accurate forecasting models do not work equally well at all times. Second, some forecasting models work better at short horizons and others at longer horizons. Third, even the forecasting model with the lowest MSPE may potentially be improved by incorporating information from other models with higher MSPE. Fourth, one can think of forecast combinations as providing insurance against possible model misspecification and smooth structural change. We demonstrate that over the last 20 years suitably constructed real-time forecast combinations would have been more accurate than the no-change forecast at every horizon up to two years. Relative to the no-change forecast, forecast combinations reduce the mean-squared prediction error by up to 18%. They also have statistically significant directional accuracy as high as 77%. We conclude that suitably constructed forecast combinations should replace traditional judgmental forecasts of the price of oil.

Keywords: Forecast combination, Model misspecification, Oil price, Real-time data, Structural change

JEL Classification: C53, E32, Q43

Suggested Citation

Baumeister, Christiane and Kilian, Lutz, Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach (July 2013). CEPR Discussion Paper No. DP9569. Available at SSRN: https://ssrn.com/abstract=2297208

Christiane Baumeister (Contact Author)

University of Notre Dame ( email )

722 Flanner Hall
Notre Dame, IN 46556
United States
+1 574 631 8450 (Phone)

HOME PAGE: http://https://sites.google.com/site/cjsbaumeister/

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

Lutz Kilian

University of Michigan at Ann Arbor - Department of Economics ( email )

611 Tappan Street
Ann Arbor, MI 48109-1220
United States
734-764-2320 (Phone)
734-764-2769 (Fax)

Centre for Economic Policy Research (CEPR)

London
United Kingdom

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