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Commodity prices, commodity currencies, and global economic developments


  • Jan J. J. Groen
  • Paolo A. Pesenti


In this paper we seek to produce forecasts of commodity price movements that can systematically improve on naive statistical benchmarks, and revisit the forecasting performance of changes in commodity currencies as efficient predictors of commodity prices, a view emphasized in the recent literature. In addition, we consider different types of factor-augmented models that use information from a large data set containing a variety of indicators of supply and demand conditions across major developed and developing countries. These factor-augmented models use either standard principal components or partial least squares (PLS) regression to extract dynamic factors from the data set. Our forecasting analysis considers ten alternative indices and sub-indices of spot prices for three different commodity classes across different periods. We find that the exchange rate-based model and especially the PLS factor-augmented model are more prone to outperform the naive statistical benchmarks. However, across our range of commodity price indices we are not able to generate out-of-sample forecasts that, on average, are systematically more accurate than predictions based on a random walk or autoregressive specifications.

Suggested Citation

  • Jan J. J. Groen & Paolo A. Pesenti, 2010. "Commodity prices, commodity currencies, and global economic developments," NBER Working Papers 15743, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:15743
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    References listed on IDEAS

    1. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
    2. Yu-Chin Chen & Kenneth S. Rogoff & Barbara Rossi, 2010. "Can Exchange Rates Forecast Commodity Prices?," The Quarterly Journal of Economics, Oxford University Press, vol. 125(3), pages 1145-1194.
    3. Jan J. J. Groen & George Kapetanios, 2009. "Model selection criteria for factor-augmented regressions," Staff Reports 363, Federal Reserve Bank of New York.
    4. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    5. Margaret E. Slade & Henry Thille, 2006. "Commodity Spot Prices: An Exploratory Assessment of Market Structure and Forward-Trading Effects," Economica, London School of Economics and Political Science, vol. 73(290), pages 229-256, May.
    6. Groen, Jan J.J. & Kapetanios, George, 2016. "Revisiting useful approaches to data-rich macroeconomic forecasting," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 221-239.
    7. Selim Elekdag & René Lalonde & Douglas Laxton & Dirk Muir & Paolo Pesenti, 2008. "Oil Price Movements and the Global Economy: A Model-Based Assessment," IMF Staff Papers, Palgrave Macmillan, vol. 55(2), pages 297-311, June.
    8. Akram, Q. Farooq, 2009. "Commodity prices, interest rates and the dollar," Energy Economics, Elsevier, vol. 31(6), pages 838-851, November.
    9. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    10. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    11. Reinhart, Carmen, 1988. "Real Exchange Rate and Commodity Prices in a Neoclassical Model," MPRA Paper 13188, University Library of Munich, Germany.
    12. Eduardo Borensztein & Carmen M. Reinhart, 1994. "The Macroeconomic Determinants of Commodity Prices," IMF Staff Papers, Palgrave Macmillan, vol. 41(2), pages 236-261, June.
    13. Aasim M. Husain & Chakriya Bowman, 2004. "Forecasting Commodity Prices; Futures Versus Judgment," IMF Working Papers 04/41, International Monetary Fund.
    14. Reinhart, Carmen & Borensztein, Eduardo, 1994. "The Macroeconomic Determinants of Commodity Prices," MPRA Paper 6979, University Library of Munich, Germany.
    15. Stephen G Cecchetti & Richhild Moessner, 2008. "Commodity prices and inflation dynamics," BIS Quarterly Review, Bank for International Settlements, December.
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    Cited by:

    1. Arezki, Rabah & Dumitrescu, Elena & Freytag, Andreas & Quintyn, Marc, 2014. "Commodity prices and exchange rate volatility: Lessons from South Africa's capital account liberalization," Emerging Markets Review, Elsevier, vol. 19(C), pages 96-105.
    2. West, Kenneth D. & Wong, Ka-Fu, 2014. "A factor model for co-movements of commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 289-309.
    3. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
    4. Yu-Chin Chen & Kenneth S. Rogoff & Barbara Rossi, 2010. "Can Exchange Rates Forecast Commodity Prices?," The Quarterly Journal of Economics, Oxford University Press, vol. 125(3), pages 1145-1194.
    5. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2011. "Can oil prices forecast exchange rates?," Working Papers 11-34, Federal Reserve Bank of Philadelphia.
    6. Ravazzolo, Francesco & Vespignani, Joaquin, 2017. "World steel production: A new monthly indicator of global real economic activity," Working Papers 2017-08, University of Tasmania, Tasmanian School of Business and Economics.
    7. Delle Chiaie, Simona & Ferrara, Laurent & Giannone, Domenico, 2017. "Common factors of commodity prices," Working Paper Series 2112, European Central Bank.
    8. Ding, Liang & Vo, Minh, 2012. "Exchange rates and oil prices: A multivariate stochastic volatility analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 15-37.
    9. Antonakakis, Nikolaos & Kizys, Renatas, 2015. "Dynamic spillovers between commodity and currency markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 303-319.
    10. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    11. Gazi Salah Uddin & Aviral Kumar Tiwari, 2013. "Measuring co-movement of oil price and exchange rate differential in Bangladesh," Economics Bulletin, AccessEcon, vol. 33(3), pages 1922-1930.
    12. Tokuo Iwaisako, 2011. "Comment on "The Relationship between Commodity Prices and Currency Exchange Rates: Evidence from the Futures Markets"," NBER Chapters,in: Commodity Prices and Markets, East Asia Seminar on Economics, Volume 20, pages 71-72 National Bureau of Economic Research, Inc.
    13. repec:eee:eneeco:v:66:y:2017:i:c:p:399-410 is not listed on IDEAS
    14. Pincheira, Pablo & Hardy, Nicolas, 2018. "Forecasting Base Metal Prices with Commodity Currencies," MPRA Paper 83564, University Library of Munich, Germany.
    15. repec:eee:jrpoli:v:52:y:2017:i:c:p:427-434 is not listed on IDEAS
    16. Uddin, Gazi Salah & Tiwari, Aviral Kumar & Arouri, Mohamed & Teulon, Frédéric, 2013. "On the relationship between oil price and exchange rates: A wavelet analysis," Economic Modelling, Elsevier, vol. 35(C), pages 502-507.
    17. S. Delle Chiaie & L. Ferrara & D. Giannone, 2017. "Common Factors of Commodity Prices," Working papers 645, Banque de France.
    18. repec:ipg:wpaper:2014-456 is not listed on IDEAS
    19. Wolfgang Pollan, 2013. "US Inflation and Crude Oil Prices. An International Perspective," WIFO Working Papers 451, WIFO.
    20. Gargano, Antonio & Timmermann, Allan, 2014. "Forecasting commodity price indexes using macroeconomic and financial predictors," International Journal of Forecasting, Elsevier, vol. 30(3), pages 825-843.
    21. Gao, Lin & Süss, Stephan, 2015. "Market sentiment in commodity futures returns," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 84-103.

    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

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