IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_6749.html
   My bibliography  Save this paper

Modeling Fluctuations in the Global Demand for Commodities

Author

Listed:
  • Lutz Kilian
  • Xiaoqing Zhou

Abstract

It is widely understood that the real price of globally traded commodities is determined by the forces of demand and supply. One of the main determinants of the real price of commodities is shifts in the demand for commodities associated with unexpected fluctuations in global real economic activity. There have been numerous proposals for quantifying global real economic activity. We discuss which criteria a measure of global real activity must satisfy to be useful for modeling industrial commodity prices, we examine which of the many alternative measures in the literature are most suitable for applied work, and we explain why some popular measures are inappropriate for modeling commodity prices. Given these insights, we reexamine in detail the question of whether global real economic activity has declined since 2011 and by how much. Drawing on a range of new evidence, we show that the global commodity price boom of the 2000s appears to have been largely transitory. Our analysis has important implications for the design of structural models of commodity markets, for the analysis of the transmission of commodity price shocks to commodity-importing and exporting economies, and for commodity price forecasting.

Suggested Citation

  • Lutz Kilian & Xiaoqing Zhou, 2017. "Modeling Fluctuations in the Global Demand for Commodities," CESifo Working Paper Series 6749, CESifo.
  • Handle: RePEc:ces:ceswps:_6749
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp6749.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kilian, Lutz & Lee, Thomas K., 2014. "Quantifying the speculative component in the real price of oil: The role of global oil inventories," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 71-87.
    2. Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2022. "Common factors of commodity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 461-476, April.
    3. Ron Alquist & Lutz Kilian, 2010. "What do we learn from the price of crude oil futures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 539-573.
    4. Büyükşahin, Bahattin & Robe, Michel A., 2014. "Speculators, commodities and cross-market linkages," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 38-70.
    5. Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2013. "Forecasting the Price of Oil," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 427-507, Elsevier.
    6. Christiane Baumeister & Gert Peersman, 2013. "The Role Of Time‐Varying Price Elasticities In Accounting For Volatility Changes In The Crude Oil Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1087-1109, November.
    7. Cabrillac, Bruno & Al-Haschimi, Alexander & Babecká Kucharčuková, Oxana & Borin, Alessandro & Bussière, Matthieu & Cezar, Raphael & Derviz, Alexis & Dimitropoulou, Dimitra & Ferrara, Laurent & Gächter, 2016. "Understanding the weakness in global trade - What is the new normal?," Occasional Paper Series 178, European Central Bank.
    8. Robin Greenwood & Samuel G. Hanson, 2015. "Waves in Ship Prices and Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(1), pages 55-109.
    9. Canova, Fabio, 2014. "Bridging DSGE models and the raw data," Journal of Monetary Economics, Elsevier, vol. 67(C), pages 1-15.
    10. Christiane Baumeister & Lutz Kilian, 2016. "Lower Oil Prices and the U.S. Economy: Is This Time Different?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(2 (Fall)), pages 287-357.
    11. Lutz Kilian, 2008. "The Economic Effects of Energy Price Shocks," Journal of Economic Literature, American Economic Association, vol. 46(4), pages 871-909, December.
    12. Francesco Ravazzolo & Joaquin L. Vespignani, 2015. "A new monthly indicator of global real economic activity," Globalization Institute Working Papers 244, Federal Reserve Bank of Dallas.
    13. Francis X. Diebold & Lutz Kilian, 2001. "Measuring predictability: theory and macroeconomic applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(6), pages 657-669.
    14. Ready, Robert & Roussanov, Nikolai & Ward, Colin, 2017. "After the tide: Commodity currencies and global trade," Journal of Monetary Economics, Elsevier, vol. 85(C), pages 69-86.
    15. Francesco Lippi & Andrea Nobili, 2012. "Oil And The Macroeconomy: A Quantitative Structural Analysis," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 1059-1083, October.
    16. Lutz Kilian, 2017. "The Impact of the Fracking Boom on Arab Oil Producers," The Energy Journal, , vol. 38(6), pages 137-160, November.
    17. Christopher R. Knittel & Robert S. Pindyck, 2016. "The Simple Economics of Commodity Price Speculation," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(2), pages 85-110, April.
    18. Van Robays, Ine & Belu Mănescu, Cristiana, 2014. "Forecasting the Brent oil price: addressing time-variation in forecast performance," Working Paper Series 1735, European Central Bank.
    19. 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.
    20. Alquist, Ron & Bhattarai, Saroj & Coibion, Olivier, 2020. "Commodity-price comovement and global economic activity," Journal of Monetary Economics, Elsevier, vol. 112(C), pages 41-56.
    21. Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K., 2014. "Are there gains from pooling real-time oil price forecasts?," Energy Economics, Elsevier, vol. 46(S1), pages 33-43.
    22. James D. Hamilton, 2018. "Why You Should Never Use the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 831-843, December.
    23. Stratford, Kate, 2013. "Nowcasting world GDP and trade using global indicators," Bank of England Quarterly Bulletin, Bank of England, vol. 53(3), pages 233-242.
    24. Robert B. Barsky & Lutz Kilian, 2002. "Do We Really Know That Oil Caused the Great Stagflation? A Monetary Alternative," NBER Chapters, in: NBER Macroeconomics Annual 2001, Volume 16, pages 137-198, National Bureau of Economic Research, Inc.
    25. Richard G. Newell & Brian C. Prest & Ashley Vissing, 2016. "Trophy Hunting vs. Manufacturing Energy: The Price-Responsiveness of Shale Gas," NBER Working Papers 22532, National Bureau of Economic Research, Inc.
    26. Lutz Kilian & Bruce Hicks, 2013. "Did Unexpectedly Strong Economic Growth Cause the Oil Price Shock of 2003–2008?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 385-394, August.
    27. Lutz Kilian & Daniel P. Murphy, 2014. "The Role Of Inventories And Speculative Trading In The Global Market For Crude Oil," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 454-478, April.
    28. Christiane Baumeister & Lutz Kilian, 2014. "Do oil price increases cause higher food prices? [Biofuels, binding constraints, and agricultural commodity price volatility]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 29(80), pages 691-747.
    29. Christiane Baumeister & Lutz Kilian, 2014. "What Central Bankers Need To Know About Forecasting Oil Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55, pages 869-889, August.
    30. Valentina G. Bruno & Bahattin Büyükşahin & Michel A. Robe, 2017. "The Financialization of Food?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(1), pages 243-264.
    31. Frederick R. Macaulay, 1938. "Some Theoretical Problems Suggested by the Movements of Interest Rates, Bond Yields and Stock Prices in the United States since 1856," NBER Books, National Bureau of Economic Research, Inc, number maca38-1.
    32. James D. Hamilton, 2017. "Why You Should Never Use the Hodrick-Prescott Filter," NBER Working Papers 23429, National Bureau of Economic Research, Inc.
    33. Payton Odom, 2010. "Shipping Indexes Signal Global Economic Trends," Annual Report, Globalization and Monetary Policy Institute, Federal Reserve Bank of Dallas, pages 28-35.
    34. Gerlach, H M Stefan, 1988. "World Business Cycles under Fixed and Flexible Exchange Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 20(4), pages 621-632, November.
    35. Holz, Carsten A., 2014. "The quality of China's GDP statistics," China Economic Review, Elsevier, vol. 30(C), pages 309-338.
    36. Kilian,Lutz & Lütkepohl,Helmut, 2018. "Structural Vector Autoregressive Analysis," Cambridge Books, Cambridge University Press, number 9781107196575, September.
    37. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    38. Michael Francis & Louis Morel, 2015. "The Slowdown in Global Trade," Bank of Canada Review, Bank of Canada, vol. 2015(Spring), pages 13-25.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lutz Kilian & Xiaoqing Zhou, 2023. "The Econometrics of Oil Market VAR Models," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 65-95, Emerald Group Publishing Limited.
    2. Christiane Baumeister & Lutz Kilian, 2016. "Forty Years of Oil Price Fluctuations: Why the Price of Oil May Still Surprise Us," Journal of Economic Perspectives, American Economic Association, vol. 30(1), pages 139-160, Winter.
    3. Joëts, Marc & Mignon, Valérie & Razafindrabe, Tovonony, 2017. "Does the volatility of commodity prices reflect macroeconomic uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 313-326.
    4. Simona Delle Chiaie & Laurent Ferrara & Domenico Giannone, 2022. "Common factors of commodity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 461-476, April.
    5. Degiannakis, Stavros & Filis, George, 2018. "Forecasting oil prices: High-frequency financial data are indeed useful," Energy Economics, Elsevier, vol. 76(C), pages 388-402.
    6. 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).
    7. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil prices," MPRA Paper 77531, University Library of Munich, Germany.
    8. Stavros Degiannakis & George Filis & Vipin Arora, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," The Energy Journal, , vol. 39(5), pages 85-130, September.
    9. Baumeister, Christiane & Guérin, Pierre & Kilian, Lutz, 2015. "Do high-frequency financial data help forecast oil prices? The MIDAS touch at work," International Journal of Forecasting, Elsevier, vol. 31(2), pages 238-252.
    10. Francesco Ravazzolo & Joaquin Vespignani, 2020. "World steel production: A new monthly indicator of global real economic activity," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 743-766, May.
    11. Kilian, Lutz & Zhou, Xiaoqing, 2018. "Structural Interpretation of Vector Autoregressions with Incomplete Information: Revisiting the Role of Oil Supply and Demand S," CEPR Discussion Papers 13068, C.E.P.R. Discussion Papers.
    12. Kilian, Lutz, 2022. "Facts and fiction in oil market modeling," Energy Economics, Elsevier, vol. 110(C).
    13. Kilian, Lutz & Zhou, Xiaoqing, 2022. "Oil prices, exchange rates and interest rates," Journal of International Money and Finance, Elsevier, vol. 126(C).
    14. Lutz Kilian & Xiaoqing Zhou, 2018. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks: Comment," CESifo Working Paper Series 7166, CESifo.
    15. Figuerola-Ferretti, Isabel & McCrorie, J. Roderick & Paraskevopoulos, Ioannis, 2020. "Mild explosivity in recent crude oil prices," Energy Economics, Elsevier, vol. 87(C).
    16. Nathan Sussman & Osnat Zohar, 2016. "Has Inflation Targeting Become Less Credible? Oil Prices, Global Aggregate Demand and Inflation Expectations during the Global Financial Crisis," Bank of Israel Working Papers 2016.13, Bank of Israel.
    17. Efthymios G. Pavlidis & Ivan Paya & David A. Peel, 2018. "Using Market Expectations to Test for Speculative Bubbles in the Crude Oil Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(5), pages 833-856, August.
    18. Miao, Hong & Ramchander, Sanjay & Wang, Tianyang & Yang, Dongxiao, 2017. "Influential factors in crude oil price forecasting," Energy Economics, Elsevier, vol. 68(C), pages 77-88.
    19. Lutz Kilian, 2017. "The Impact of the Fracking Boom on Arab Oil Producers," The Energy Journal, , vol. 38(6), pages 137-160, November.
    20. Francesco Ravazzolo & Joaquin L. Vespignani, 2015. "A new monthly indicator of global real economic activity," Globalization Institute Working Papers 244, Federal Reserve Bank of Dallas.

    More about this item

    Keywords

    commodity market; demand; real economic activity; global economy; oil price; international business; cycle; leading indicators;
    All these keywords.

    JEL classification:

    • F44 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Business Cycles
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply; Prices
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_6749. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.