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What is behind the increase in oil prices? Analyzing oil consumption and supply relationship with oil price

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  • Gallo, Andres
  • Mason, Paul
  • Shapiro, Steve
  • Fabritius, Michael

Abstract

The continuing increases in oil prices have renewed the argument over the real culprits behind these movements. The growth in demand for oil in international markets, especially from the United States and China, is often identified as the main source of consumption pressure on prices, and thus the upward trend in oil prices. This paper uses unit root tests with two endogenous breaks to analyze the characteristics of oil prices, production, and consumption for several countries. By taking into account structural breaks, we find that many countries’ oil consumption and oil prices are stationary, while other countries are not. We also perform causality tests to determine the direction of any possible relationship between oil price and oil consumption and production. Our statistical analysis reveals that production variables cause oil prices, while oil prices tend to cause consumption. As a result, we claim that the blame for the recent fluctuations in oil prices is more appropriately associated with supply factors, not consumption influences.

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  • Gallo, Andres & Mason, Paul & Shapiro, Steve & Fabritius, Michael, 2010. "What is behind the increase in oil prices? Analyzing oil consumption and supply relationship with oil price," Energy, Elsevier, vol. 35(10), pages 4126-4141.
  • Handle: RePEc:eee:energy:v:35:y:2010:i:10:p:4126-4141
    DOI: 10.1016/j.energy.2010.06.033
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    Cited by:

    1. Bataa, Erdenebat & Izzeldin, Marwan & Osborn, Denise R., 2016. "Changes in the global oil market," Energy Economics, Elsevier, vol. 56(C), pages 161-176.
    2. Jammazi, Rania, 2012. "Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach," Energy, Elsevier, vol. 37(1), pages 430-454.
    3. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    4. repec:spr:empeco:v:53:y:2017:i:3:d:10.1007_s00181-016-1162-9 is not listed on IDEAS
    5. Ahmadi, Maryam & Manera, Matteo & Sadeghzadeh, Mehdi, 2016. "Global oil market and the U.S. stock returns," Energy, Elsevier, vol. 114(C), pages 1277-1287.
    6. Zhang, Yue-Jun, 2013. "Speculative trading and WTI crude oil futures price movement: An empirical analysis," Applied Energy, Elsevier, vol. 107(C), pages 394-402.
    7. Xie, Nan & Yan, Zhijun & Zhou, Yi & Huang, Wenjun, 2017. "China's optimal stockpiling policies in the context of new oil price trend," Energy Policy, Elsevier, vol. 105(C), pages 332-340.
    8. repec:eee:rensus:v:88:y:2018:i:c:p:297-325 is not listed on IDEAS
    9. Chul-Yong Lee & Sung-Yoon Huh, 2017. "Forecasting Long-Term Crude Oil Prices Using a Bayesian Model with Informative Priors," Sustainability, MDPI, Open Access Journal, vol. 9(2), pages 1-15, January.
    10. Mercure, Jean-François & Salas, Pablo, 2013. "On the global economic potentials and marginal costs of non-renewable resources and the price of energy commodities," Energy Policy, Elsevier, vol. 63(C), pages 469-483.
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    12. Wu, Man-Hwa & Ni, Yen-Sen, 2011. "The effects of oil prices on inflation, interest rates and money," Energy, Elsevier, vol. 36(7), pages 4158-4164.
    13. Lin, Boqiang & Wesseh, Presley K., 2013. "What causes price volatility and regime shifts in the natural gas market," Energy, Elsevier, vol. 55(C), pages 553-563.
    14. Gori, Fabio, 2016. "Mass and energy-capital conservation equations to forecast the oil price evolution with accumulation or depletion of the resources," Energy, Elsevier, vol. 116(P1), pages 746-760.
    15. Zhang, Yue-Jun & Zhang, Lu, 2015. "Interpreting the crude oil price movements: Evidence from the Markov regime switching model," Applied Energy, Elsevier, vol. 143(C), pages 96-109.
    16. Movagharnejad, Kamyar & Mehdizadeh, Bahman & Banihashemi, Morteza & Kordkheili, Masoud Sheikhi, 2011. "Forecasting the differences between various commercial oil prices in the Persian Gulf region by neural network," Energy, Elsevier, vol. 36(7), pages 3979-3984.

    More about this item

    Keywords

    Q40 Energy general; Q41 Energy-supply and demand; L71: Industry studies – mining; extraction; and refining: hydrocarbon fuels; C22: Time series models;

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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