Advanced Search
MyIDEAS: Login

Evaluating the Empirical Performance of Alternative Econometric Models for Oil Price Forecasting

Contents:

Author Info

  • Matteo Manera

    (University of Milan Bicocca)

  • Chiara Longo

    (Fondazione Eni Enrico Mattei)

  • Anil Markandya

    (University of Bath and Fondazione Eni Enrico Mattei)

  • Elisa Scarpa

    (Risk Management Department, Intesa-San Paolo)

Abstract

The relevance of oil in the world economy explains why considerable effort has been devoted to the development of different types of econometric models for oil price forecasting. Several specifications have been proposed in the economic literature. Some are based on financial theory and concentrate on the relationship between spot and futures prices (“financial” models). Others assign a key role to variables explaining the characteristics of the physical oil market (“structural” models). The empirical literature is very far from any consensus about the appropriate model for oil price forecasting that should be implemented. Relative to the previous literature, this paper is novel in several respects. First of all, we test and systematically evaluate the ability of several alternative econometric specifications proposed in the literature to capture the dynamics of oil prices. Second, we analyse the effects of different data frequencies on the coefficient estimates and forecasts obtained using each selected econometric specification. Third, we compare different models at different data frequencies on a common sample and common data. Fourth, we evaluate the forecasting performance of each selected model using static and dynamic forecasts, as well as different measures of forecast errors. Finally, we propose a new class of models which combine the relevant aspects of the financial and structural specifications proposed in the literature (“mixed” models). Our empirical findings can be summarized as follows. Financial models in levels do not produce satisfactory forecasts for the WTI spot price. The financial error correction model yields accurate in-sample forecasts. Real and strategic variables alone are insufficient to capture the oil spot price dynamics in the forecasting sample. Our proposed mixed models are statistically adequate and exhibit accurate forecasts. Different data frequencies seem to affect the forecasting ability of the models under analysis.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.feem.it/userfiles/attach/Publication/NDL2007/NDL2007-004.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number 2007.4.

as in new window
Length:
Date of creation: Jan 2007
Date of revision:
Handle: RePEc:fem:femwpa:2007.4

Contact details of provider:
Postal: Corso Magenta, 63 - 20123 Milan
Phone: 0039-2-52036934
Fax: 0039-2-52036946
Email:
Web page: http://www.feem.it/
More information through EDIRC

Related research

Keywords: Oil Price; WTI Spot And Futures Prices; Forecasting; Econometric Models;

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Antonio Merino & Alvaro Ortiz, 2005. "Explaining the so-called "price premium" in oil markets," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 29(2), pages 133-152, 06.
  2. Zeng, T. & Swanson, N.R., 1997. "Predictive Evaluation of Econometric Forecasting Models in Commodity Futures Markets," Papers 9-97-4, Pennsylvania State - Department of Economics.
  3. Dees, Stephane & Karadeloglou, Pavlos & Kaufmann, Robert K. & Sanchez, Marcelo, 2007. "Modelling the world oil market: Assessment of a quarterly econometric model," Energy Policy, Elsevier, vol. 35(1), pages 178-191, January.
  4. MacKinnon, James G, 1996. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 601-18, Nov.-Dec..
  5. Serletis, Apostolos, 1991. "Rational expectations, risk and efficiency in energy futures markets," Energy Economics, Elsevier, vol. 13(2), pages 111-115, April.
  6. Robert K. Kaufmann, Stephane Dees, Pavlos Karadeloglou and Marcelo Sanchez, 2004. "Does OPEC Matter? An Econometric Analysis of Oil Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 67-90.
  7. John R. Moroney & M. Douglas Berg, 1999. "An Integrated Model of Oil Production," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 105-124.
  8. Bopp, Anthony E. & Lady, George M., 1991. "A comparison of petroleum futures versus spot prices as predictors of prices in the future," Energy Economics, Elsevier, vol. 13(4), pages 274-282, October.
  9. Moosa, Imad A. & Al-Loughani, Nabeel E., 1994. "Unbiasedness and time varying risk premia in the crude oil futures market," Energy Economics, Elsevier, vol. 16(2), pages 99-105, April.
  10. Kaufmann, Robert K., 1995. "A model of the world oil market for project LINK Integrating economics, geology and politics," Economic Modelling, Elsevier, vol. 12(2), pages 165-178, April.
  11. Gulen, S. Gurcan, 1998. "Efficiency in the crude oil futures market," Journal of Energy Finance & Development, Elsevier, vol. 3(1), pages 13-21.
  12. Salah Abosedra, 2005. "Futures versus univariate forecast of crude oil prices," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 29(4), pages 231-241, December.
  13. Morana, Claudio, 2001. "A semiparametric approach to short-term oil price forecasting," Energy Economics, Elsevier, vol. 23(3), pages 325-338, May.
  14. Robert S. Pindyck, 1999. "The Long-Run Evolutions of Energy Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-27.
  15. Ye, Michael & Zyren, John & Shore, Joanne, 2005. "A monthly crude oil spot price forecasting model using relative inventories," International Journal of Forecasting, Elsevier, vol. 21(3), pages 491-501.
  16. Saeed Moshiri & Faezeh Foroutan, 2006. "Forecasting Nonlinear Crude Oil Futures Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 81-96.
  17. Stanislav Radchenko, 2005. "The Long-Run Forecasting of Energy Prices Using the Model of Shifting Trend," Econometrics 0502002, EconWPA.
  18. Menzie D. Chinn & Michael LeBlanc & Olivier Coibion, 2005. "The Predictive Content of Energy Futures: An Update on Petroleum, Natural Gas, Heating Oil and Gasoline," NBER Working Papers 11033, National Bureau of Economic Research, Inc.
  19. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Claudio Dicembrino & Pasquale Lucio Scandizzo, 2012. "The Fundamental and Speculative Components of the Oil Spot Price: A Real Option Value Approach," CEIS Research Paper 229, Tor Vergata University, CEIS, revised 18 Apr 2012.
  2. Zhang, Xun & Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method," Energy Economics, Elsevier, vol. 31(5), pages 768-778, September.
  3. Ekins, Paul & Pollitt, Hector & Barton, Jennifer & Blobel, Daniel, 2011. "The implications for households of environmental tax reform (ETR) in Europe," Ecological Economics, Elsevier, vol. 70(12), pages 2472-2485.
  4. Sanders, Dwight R. & Manfredo, Mark R. & Boris, Keith, 2009. "Evaluating information in multiple horizon forecasts: The DOE's energy price forecasts," Energy Economics, Elsevier, vol. 31(2), pages 189-196.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:fem:femwpa:2007.4. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (barbara racah).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.