 Forecasting and Analyzing World Commodity PricesRené Lalonde, Zhenhua Zhu and Frederick Demers Staff Working Papers from 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. Keywords: Econometric; and; statistical; methods (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bca:bocawp:03-24 Access Statistics for this paper More papers in Staff Working Papers from Bank of Canada 234 Wellington Street, Ottawa, Ontario, K1A 0G9, Canada. Contact information at EDIRC. |
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