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Forecasting crude oil spot price using OECD petroleum inventory levels

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  • Michael Ye
  • John Zyren
  • Joanne Shore

Abstract

This paper presents a short-term monthly forecasting model of West Texas Intermediate crude oil spot price using OECD petroleum inventory levels. Theoretically, petroleum inventory levels are a measure of the balance, or imbalance, between petroleum production and demand, and thus provide a good market barometer of crude oil price change. Based on an understanding of petroleum market fundamentals and observed market behavior during the post-Gulf War period, the model was developed with the objectives of being both simple and practical, with required data readily available. As a result, the model is useful to industry and government decision-makers in forecasting price and investigating the impacts of changes on price, should inventories, production, imports, or demand change. Copyright International Atlantic Economic Society 2002

Suggested Citation

  • Michael Ye & John Zyren & Joanne Shore, 2002. "Forecasting crude oil spot price using OECD petroleum inventory levels," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 8(4), pages 324-333, November.
  • Handle: RePEc:kap:iaecre:v:8:y:2002:i:4:p:324-333:10.1007/bf02295507
    DOI: 10.1007/BF02295507
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    References listed on IDEAS

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    1. Robert S. Pindyck, 1994. "Inventories and the Short-Run Dynamics of Commodity Prices," RAND Journal of Economics, The RAND Corporation, vol. 25(1), pages 141-159, Spring.
    2. Maccini, Louis J & Rossana, Robert J, 1984. "Joint Production, Quasi-Fixed Factors of Production, and Investement in Finished Goods Inventories," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 16(2), pages 218-236, May.
    3. Nicholas Kaldor, 1939. "Speculation and Economic Stability," Review of Economic Studies, Oxford University Press, vol. 7(1), pages 1-27.
    4. Gustafson, Robert L., 1958. "Carryover levels for grains: A method for determining amounts that are optimal under specified conditions," Technical Bulletins 157231, United States Department of Agriculture, Economic Research Service.
    5. Eichenbaum, Martin, 1989. "Some Empirical Evidence on the Production Level and Production Cost Smoothing Models of Inventory Investment," American Economic Review, American Economic Association, vol. 79(4), pages 853-864, September.
    6. Timothy J. Considine & Donald F. Larson, 2001. "Risk premiums on inventory assets: the case of crude oil and natural gas," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(2), pages 109-126, February.
    7. Lester G. Telser, 1958. "Futures Trading and the Storage of Cotton and Wheat," Journal of Political Economy, University of Chicago Press, vol. 66, pages 233-233.
    8. Ramey, Valerie A, 1989. "Inventories as Factors of Production and Economic Fluctuations," American Economic Review, American Economic Association, vol. 79(3), pages 338-354, June.
    9. Robert Mabro, 1992. "OPEC and the Price of Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    10. Walter N. Thurman, 1988. "Speculative Carryover: An Empirical Examination of the U.S. Refined Copper Market," RAND Journal of Economics, The RAND Corporation, vol. 19(3), pages 420-437, Autumn.
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    Cited by:

    1. repec:eee:glofin:v:35:y:2018:i:c:p:177-201 is not listed on IDEAS
    2. Karali, Berna & Ramirez, Octavio A., 2014. "Macro determinants of volatility and volatility spillover in energy markets," Energy Economics, Elsevier, vol. 46(C), pages 413-421.
    3. Sung Je Byun, 2017. "Speculation in Commodity Futures Markets, Inventories and the Price of Crude Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    4. Owen Q. Wu & Hong Chen, 2010. "Optimal Control and Equilibrium Behavior of Production-Inventory Systems," Management Science, INFORMS, vol. 56(8), pages 1362-1379, August.
    5. Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.
    6. Mehdi Asali, 2008. "Dynamics of petroleum markets in OECD countries in a monthly VAR-VEC model (1995-2007)," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 32(1), pages 54-87, March.
    7. Frankel, Jeffrey A., 2014. "Effects of speculation and interest rates in a “carry trade” model of commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 88-112.

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