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How important are common factors in driving non-fuel commodity prices? A dynamic factor analysis


  • Vansteenkiste, Isabel


This paper analyses the importance of common factors in shaping non-fuel commodity price movements for the period 1957-2008. For this purpose, a dynamic factor model is estimated using Kalman Filtering techniques. Based on this set-up we are able to separate common and idiosyncratic developments of commodity prices. Our estimation results show that there exists one common significant factor for most non-fuel commodity prices and that this common factor has recently become increasingly important in driving non-fuel commodity prices. However during the seventies and early eighties, the co-movement was much higher. In a next step, we then rely on an instrumental variable approach to uncover which variables could be linked to the common factor. We find that the main statistically significant variables are the oil price, the US dollar effective exchange rate, the real interest rate but more recently also global demand (as measured by a proxy for global industrial production). JEL Classification: E30, F00

Suggested Citation

  • Vansteenkiste, Isabel, 2009. "How important are common factors in driving non-fuel commodity prices? A dynamic factor analysis," Working Paper Series 1072, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20091072

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    References listed on IDEAS

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    Cited by:

    1. Matteo Manera & Marcella Nicolini & Ilaria Vignati, 2012. "Returns in commodities futures markets and financial speculation: a multivariate GARCH approach," Quaderni di Dipartimento 170, University of Pavia, Department of Economics and Quantitative Methods.
    2. Adom, Philip Kofi, 2014. "Determinants of food availability and access in Ghana: what can we learn beyond the regression results?," Studies in Agricultural Economics, Research Institute for Agricultural Economics, vol. 116(3), December.
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    4. Phil Briggs & Carly Harker & Tim Ng & Aidan Yao, 2011. "Fluctuations in the international prices of oil, dairy products, beef and lamb between 2000 and 2008: A review of market-specific demand and supply factors," Reserve Bank of New Zealand Discussion Paper Series DP2011/02, Reserve Bank of New Zealand.
    5. Adam Jêdrzejczyk, 2012. "Inflation forecasting using dynamic factor analysis. SAS 4GL programming approach," Working Papers 63, Department of Applied Econometrics, Warsaw School of Economics.
    6. Joseph W. Gruber & Robert J. Vigfusson, 2012. "Interest rates and the volatility and correlation of commodity prices," International Finance Discussion Papers 1065, Board of Governors of the Federal Reserve System (U.S.).
    7. Rossen, Anja, 2015. "What are metal prices like? Co-movement, price cycles and long-run trends," Resources Policy, Elsevier, vol. 45(C), pages 255-276.
    8. David Matesanz & Benno Torgler & Germán Dabat & Guillermo J. Ortega, 2014. "Co-movements in commodity prices: a note based on network analysis," Agricultural Economics, International Association of Agricultural Economists, vol. 45(S1), pages 13-21, November.
    9. Krätschell, Karoline & Schmidt, Torsten, 2013. "Long-run trends or short-run fluctuations What establishes the correlation between oil and food prices?," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79798, Verein für Socialpolitik / German Economic Association.
    10. Gal Hochman & Deepak Rajagopal & David Zilberman, 2010. "Are Biofuels the Culprit? OPEC, Food, and Fuel," American Economic Review, American Economic Association, vol. 100(2), pages 183-187, May.
    11. Yannick Le Pen & Benoît Sévi, 2013. "Futures trading and the excess comovement of commodity prices," Post-Print hal-01613916, HAL.
    12. Christian Gross, 2017. "Examining the Common Dynamics of Commodity Futures Prices," CQE Working Papers 6317, Center for Quantitative Economics (CQE), University of Muenster.
    13. Byrne, Joseph P. & Fazio, Giorgio & Fiess, Norbert, 2013. "Primary commodity prices: Co-movements, common factors and fundamentals," Journal of Development Economics, Elsevier, vol. 101(C), pages 16-26.
    14. Marco Lombardi & Chiara Osbat & Bernd Schnatz, 2012. "Global commodity cycles and linkages: a FAVAR approach," Empirical Economics, Springer, vol. 43(2), pages 651-670, October.
    15. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    16. Krätschell, Karoline & Schmidt, Torsten, 2012. "Long-run Trends or Short-run Fluctuations – What Establishes the Correlation between Oil and Food Prices?The Interplay of Standardized Tests and Incentives – An Econometric Analysis with Data from PIS," Ruhr Economic Papers 357, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    17. Diego Bastourre & Jorge Carrera & Javier Ibarlucia & Mariano Sardi, 2012. "Common Drivers in Emerging Market Spreads and Commodity Prices," BCRA Working Paper Series 201257, Central Bank of Argentina, Economic Research Department.
    18. Byrne, Joseph P & Sakemoto, Ryuta & Xu, Bing, 2017. "Commodity Price Co-movement: Heterogeneity and the Time Varying Impact of Fundamentals," MPRA Paper 80791, University Library of Munich, Germany.
    19. Byrne, Joseph P & Fazio, Giorgio & Fiess, Norbert, 2010. "Optimism and commitment: An elementary theory of bargaining and war," SIRE Discussion Papers 2010-102, Scottish Institute for Research in Economics (SIRE).
    20. Golosnoy, Vasyl & Rossen, Anja, 2014. "Modeling dynamics of metal price series via state space approach with two common factors," HWWI Research Papers 156, Hamburg Institute of International Economics (HWWI).
    21. Lübbers, Johannes & Posch, Peter N., 2016. "Commodities' common factor: An empirical assessment of the markets' drivers," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 28-40.

    More about this item


    commodity prices; dynamic factor; Kalman filter;

    JEL classification:

    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • F00 - International Economics - - General - - - General

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