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Forecasting and Analyzing World Commodity Prices

Author

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  • René Lalonde

    (Bank of Canada)

  • Zhenhua Zhu

    (Bank of Canada)

  • Frédérick Demers

    (Bank of Canada)

Abstract

The authors develop simple econometric models to analyze and forecast two components of the Bank of Canada commodity price index: the Bank of Canada non-energy (BCNE) commodity prices and the West Texas Intermediate crude oil price. They present different methodologies to identify transitory and permanent components of movements in these prices. A structural vector autoregressive model is used for real BCNE prices and a multiple structural-break technique is employed for real crude oil prices. The authors use these transitory and permanent components to develop forecasting models. They assess various aspects of the models' performance. Their main results indicate that: (i) the world economic activity and real U.S.-dollar effective exchange rate explain much of the cyclical variation of real BCNE prices, (ii) real crude oil prices have two structural breaks over the sample period, and recently their link with the world economic activity has been quite strong, and (iii) the models outperform benchmark models, namely a vector autoregressive model, an autoregressive model, and a random-walk model, in terms of out-of-sample forecasting.
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Suggested Citation

  • René Lalonde & Zhenhua Zhu & Frédérick Demers, 2003. "Forecasting and Analyzing World Commodity Prices," Money Affairs, CEMLA, vol. 0(1), pages 1-30, January-J.
  • Handle: RePEc:cml:moneya:v:xvi:y:2003:i:1:p:1-30
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    4. Walter Labys, 2005. "Commodity Price Fluctuations: A Century of Analysis," Working Papers Working Paper 2005-01, Regional Research Institute, West Virginia University.
    5. Drachal, Krzysztof, 2016. "Forecasting spot oil price in a dynamic model averaging framework — Have the determinants changed over time?," Energy Economics, Elsevier, vol. 60(C), pages 35-46.
    6. René Lalonde & Dirk Muir, 2007. "The Bank of Canada's Version of the Global Economy Model (BoC-GEM)," Technical Reports 98, Bank of Canada.
    7. 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.
    8. Olivier Gervais & Ilan Kolet & René Lalonde, 2010. "A Larger Slice of a Growing Pie: the Role of Emerging Asia in Forecasting Commodity Prices," Money Affairs, CEMLA, vol. 0(1), pages 75-95, January-J.
    9. Pablo Pincheira, 2010. "A Real Time Evaluation of the Central Bank of Chile GDP Growth Forecasts," Money Affairs, CEMLA, vol. 0(1), pages 37-73, January-J.
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    12. Jean-Philippe Cayen & Marc-André Gosselin & Sharon Kozicki, 2009. "Estimating DSGE-Model-Consistent Trends for Use in Forecasting," Staff Working Papers 09-35, Bank of Canada.
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    14. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    15. 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(01), pages 29-44, April.
    16. Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.

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