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The Long-Run Forecasting of Energy Prices Using the Model of Shifting Trend

Author

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  • Stanislav Radchenko

    (UNC at Charlotte)

Abstract

This paper constructs long-term forecasts of energy prices using a reduced form model of shifting trend developed by Pindyck (1999). A Gibbs sampling algorithm is developed to estimate models with a shifting trend line which are used to construct 10-period-ahead and 15-period ahead forecasts. An advantage of forecasts from this model is that they are not very influenced by the presence of large, long-lived increases and decreases in energy prices. The forecasts form shifting trends model are combined with forecasts from the random walk model and the autoregressive model to substantially decrease the mean forecast squared error compared to each individual model.

Suggested Citation

  • Stanislav Radchenko, 2005. "The Long-Run Forecasting of Energy Prices Using the Model of Shifting Trend," Econometrics 0502002, EconWPA.
    • Handle: RePEc:wpa:wuwpem:0502002
    Note: Type of Document - pdf; pages: 29
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    File URL: http://econwpa.repec.org/eps/em/papers/0502/0502002.pdf
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    References listed on IDEAS

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    1. Paul Cashin & C. John McCDermott, 2002. "The Long-Run Behavior of Commodity Prices: Small Trends and Big Variability," IMF Staff Papers, Palgrave Macmillan, vol. 49(2), pages 1-2.
    2. 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.
    3. Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian, 2004. "Structural Change and Forecasting Long-Run Energy Prices," Staff Working Papers 04-5, Bank of Canada.
    4. Marwan Chacra, 2002. "Oil-Price Shocks and Retail Energy Prices in Canada," Staff Working Papers 02-38, Bank of Canada.
    5. Lin Chan, Hing & Kam Lee, Shu, 1997. "Modelling and forecasting the demand for coal in China," Energy Economics, Elsevier, vol. 19(3), pages 271-287, July.
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    Citations

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    Cited by:

    1. Maslyuk, Svetlana & Smyth, Russell, 2008. "Unit root properties of crude oil spot and futures prices," Energy Policy, Elsevier, vol. 36(7), pages 2591-2600, July.
    2. Matteo Manera & Chiara Longo & Anil Markandya & Elisa Scarpa, 2007. "Evaluating the Empirical Performance of Alternative Econometric Models for Oil Price Forecasting," Working Papers 2007.4, Fondazione Eni Enrico Mattei.
    3. Giliola Frey & Matteo Manera & Anil Markandya & Elisa Scarpa, 2009. "Econometric Models for Oil Price Forecasting: A Critical Survey," CESifo Forum, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 10(1), pages 29-44, April.
    4. Baomin Dong & Xuefeng Li & Boqiang Lin, 2010. "Forecasting Long-Run Coal Price in China: A Shifting Trend Time-Series Approach," Review of Development Economics, Wiley Blackwell, vol. 14(s1), pages 499-519, August.
    5. Zhongbao Zhou & Ke Duan & Ling Lin & Qianying Jin, 2015. "Forecasting long-term and short-term crude oil price: a comparison of the predictive abilities of competing models," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 38(4/5/6), pages 286-297.
    6. Ozdemir, Zeynel Abidin & Gokmenoglu, Korhan & Ekinci, Cagdas, 2013. "Persistence in crude oil spot and futures prices," Energy, Elsevier, vol. 59(C), pages 29-37.

    More about this item

    Keywords

    energy forecasting; oil price; coal price; natural gas price; shifting trends model; long term forecasting;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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