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A dynamic network analysis of the world oil market: Analysis of OPEC and non-OPEC members

Author

Listed:
  • Sahel Al Rousan
  • Rashid Sbia

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Bedri Kamil Onur Tas

Abstract

We characterize the dynamic network structure of major oil producing countries. We examine the oil production coordination of 13 Organization of the Petroleum Exporting Countries (OPEC) and 17 non-OPEC members. We construct the dynamic network structure using the network connectedness measure of Diebold and Yilmaz (2009). We investigate the structural changes in connectedness of OPEC and non-OPEC members. Additionally, we study how the influence of OPEC members, non-OPEC countries and major oil producers evolve. We find that the network structure of major oil-producing countries changes significantly over time. Specifically, the impact of changes in oil-production of all OPEC members on global oil production declines, whereas the impact of non-OPEC on global oil production increases. OPEC's “increase” decisions have a significant and positive impact on OPEC and non-OPEC coordination. However, “cut” decisions do not affect coordination. We find that OPEC countries and developing countries have significantly higher levels of connectedness. Additionally, countries with high oil production levels have significantly more influence. The empirical results provide intuition about the recent developments in global oil production.
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Suggested Citation

  • Sahel Al Rousan & Rashid Sbia & Bedri Kamil Onur Tas, 2018. "A dynamic network analysis of the world oil market: Analysis of OPEC and non-OPEC members," Post-Print hal-01908019, HAL.
    • Handle: RePEc:hal:journl:hal-01908019
    DOI: 10.1016/j.eneco.2018.07.032
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    7. Gil-Alana, Luis A. & Dadgar, Yadollah & Nazari, Rouhollah, 2020. "An analysis of the OPEC and non-OPEC position in the World Oil Market: A fractionally integrated approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    8. C.R. BISHNOI & Apeksha SHARMA, 2022. "An econometric approach to analyse the perceived cartel behaviour of OPEC," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(632), A), pages 27-42, Autumn.
    9. Xiaoyu Niu & Wei Chen & Nyuying Wang, 2023. "Spatiotemporal Dynamics and Topological Evolution of the Global Crude Oil Trade Network," Energies, MDPI, vol. 16(4), pages 1-18, February.
    10. Peng, Peng & Poon, Jessie P.H. & Yang, Yu & Lu, Feng & Cheng, Shifen, 2019. "Global oil traffic network and diffusion of influence among ports using real time data," Energy, Elsevier, vol. 172(C), pages 333-342.
    11. N. Wei & W. -J. Xie & W. -X. Zhou, 2021. "Robustness of the international oil trade network under targeted attacks to economies," Papers 2101.10679, arXiv.org, revised Jan 2021.
    12. Wu, Ling & Hock Ow, Siew, 2021. "The Impact of News Sentiment on the Stock Market Fluctuation: The Case of Selected Energy Sector," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 55(3), pages 1-21.
    13. Su, Chi-Wei & Huang, Shi-Wen & Qin, Meng & Umar, Muhammad, 2021. "Does crude oil price stimulate economic policy uncertainty in BRICS?," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
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    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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