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The role of precautionary and speculative demand in the global market for crude oil

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Abstract

Contemporary structural models of the global market for crude oil treat storage demand as a composite of precautionary responses to uncertainty and speculative behavior, due to difficulties in jointly identifying these distinct demand components. This difficulty arises because the underlying expectation shifts are latent and operate through similar transmission mechanisms. In this paper, we extend the workhorse oil market model by jointly identifying these distinct demand components. Our main insight is that precautionary demand is the primary driver of the real price of crude oil, previously associate with storage demand shocks. Historically, precautionary demand shifts associated with adverse sociopolitical conditions in the Middle-East, can explain the oil price spikes during the 1979 oil crisis and the Wars of 1980 and 1990, while speculative demand was a more important driver during the disbandment of OPEC. Finally, we find that these newly identified shocks have distinct consequences for the U.S. economy: precautionary demand shocks reduce real GDP, while speculative demand shocks cause inflation.

Suggested Citation

  • Cross, James L. & Nguyen, Bao H. & Tran, Trung Duc, 2020. "The role of precautionary and speculative demand in the global market for crude oil," Working Papers 2020-02, University of Tasmania, Tasmanian School of Business and Economics.
    • Handle: RePEc:tas:wpaper:32764
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    File URL: https://eprints.utas.edu.au/32764/1/2020-02_Cross_Nguyen_Tran.pdf
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    Cited by:

    1. Atsushi Inoue & Lutz Kilian, 2020. "The Role of the Prior in Estimating VAR Models with Sign Restrictions," Working Papers 2030, Federal Reserve Bank of Dallas.
    2. Inoue, Atsushi & Kilian, Lutz, 2022. "Joint Bayesian inference about impulse responses in VAR models," Journal of Econometrics, Elsevier, vol. 231(2), pages 457-476.
    3. Lutz Kilian & Xiaoqing Zhou, 2020. "Does drawing down the US Strategic Petroleum Reserve help stabilize oil prices?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 673-691, September.
    4. Kilian, Lutz, 2022. "Understanding the estimation of oil demand and oil supply elasticities," Energy Economics, Elsevier, vol. 107(C).
    5. De, Kuhelika & Compton, Ryan A. & Giedeman, Daniel C., 2022. "Oil shocks and the U.S. economy in a data-rich model," Economic Modelling, Elsevier, vol. 108(C).
    6. Robin Braun & Ralf Brüggemann, 2017. "Identification of SVAR Models by Combining Sign Restrictions With External Instruments," Working Paper Series of the Department of Economics, University of Konstanz 2017-07, Department of Economics, University of Konstanz.
    7. Braun, Robin, 2021. "The importance of supply and demand for oil prices: evidence from non-Gaussianity," Bank of England working papers 957, Bank of England.

    More about this item

    Keywords

    oil price uncertainty; oil market; SVAR; narrative sign restrictions;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • 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

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