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Understanding the Decline in the Price of Oil since June 2014

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Listed:
  • Christiane Baumeister
  • Lutz Kilian

Abstract

There has been much interest in the causes of the steep decline in the Brent price of oil between June and December 2014. Our analysis shows that more than half of this decline was predictable in real time as of June 2014. We attribute $11 of this predictable decline to the cumulative effects of negative demand shocks prior to July 2014 which can be traced to a slowing global economy. The remaining $16 of the predictable decline is due to positive shocks to current and expected oil production prior to July 2014. The rest of the $49 cumulative decline was unpredictable and reflected a shock to oil price expectations in July 2014 which lowered the demand for oil inventories and a negative demand shock caused by an unexpected weakening of the global economy in December 2014. These two shocks lowered the price by an additional $9 and $13, respectively.

Suggested Citation

  • Christiane Baumeister & Lutz Kilian, 2016. "Understanding the Decline in the Price of Oil since June 2014," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 3(1), pages 131-158.
  • Handle: RePEc:ucp:jaerec:doi:10.1086/684160
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    References listed on IDEAS

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    1. Ravazzolo, Francesco & Vespignani, Joaquin L., 2015. "A new monthly indicator of global real economic activity," Globalization Institute Working Papers 244, Federal Reserve Bank of Dallas.
    2. Christiane Baumeister & Lutz Kilian, 2014. "Do oil price increases cause higher food prices?," Economic Policy, CEPR;CES;MSH, vol. 29(80), pages 691-747, October.
    3. repec:ucp:jpolec:doi:10.1086/697203 is not listed on IDEAS
    4. Green, Edward J & Porter, Robert H, 1984. "Noncooperative Collusion under Imperfect Price Information," Econometrica, Econometric Society, vol. 52(1), pages 87-100, January.
    5. Baumeister, Christiane & Kilian, Lutz, 2014. "A General Approach to Recovering Market Expectations from Futures Prices With an Application to Crude Oil," CEPR Discussion Papers 10162, C.E.P.R. Discussion Papers.
    6. Hamilton, James D., 2003. "What is an oil shock?," Journal of Econometrics, Elsevier, vol. 113(2), pages 363-398, April.
    7. Soren T. Anderson & Ryan Kellogg & Stephen W. Salant, 2018. "Hotelling under Pressure," Journal of Political Economy, University of Chicago Press, vol. 126(3), pages 984-1026.
    8. Christiane Baumeister & Lutz Kilian, 2014. "Real-Time Analysis of Oil Price Risks Using Forecast Scenarios," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 62(1), pages 119-145, April.
    9. 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.
    10. James L. Smith, 2009. "World Oil: Market or Mayhem?," Journal of Economic Perspectives, American Economic Association, vol. 23(3), pages 145-164, Summer.
    11. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    12. 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.
    13. 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.
    14. Hamilton, James D. & Wu, Jing Cynthia, 2014. "Risk premia in crude oil futures prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 9-37.
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    More about this item

    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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