IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v482y2017icp345-356.html
   My bibliography  Save this article

The stability of the international oil trade network from short-term and long-term perspectives

Author

Listed:
  • Sun, Qingru
  • Gao, Xiangyun
  • Zhong, Weiqiong
  • Liu, Nairong

Abstract

To examine the stability of the international oil trade network and explore the influence of countries and trade relationships on the trade stability, we construct weighted and unweighted international oil trade networks based on complex network theory using oil trading data between countries from 1996 to 2014. We analyze the stability of international oil trade network (IOTN) from short-term and long-term aspects. From the short-term perspective, we find that the trade volumes play an important role on the stability. Moreover, the weighted IOTN is stable; however, the unweighted networks can better reflect the actual evolution of IOTN. From the long-term perspective, we identify trade relationships that are maintained during the whole sample period to reveal the situation of the whole international oil trade. We provide a way to quantitatively measure the stability of complex network from short-term and long-term perspectives, which can be applied to measure and analyze trade stability of other goods or services.

Suggested Citation

  • Sun, Qingru & Gao, Xiangyun & Zhong, Weiqiong & Liu, Nairong, 2017. "The stability of the international oil trade network from short-term and long-term perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 345-356.
  • Handle: RePEc:eee:phsmap:v:482:y:2017:i:c:p:345-356
    DOI: 10.1016/j.physa.2017.04.047
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117303485
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2017.04.047?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Giorgio Fagiolo & Javier Reyes & Stefano Schiavo, 2010. "The evolution of the world trade web: a weighted-network analysis," Journal of Evolutionary Economics, Springer, vol. 20(4), pages 479-514, August.
    2. Marco Dueñas & Giorgio Fagiolo, 2014. "Global Trade Imbalances: A Network Approach," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 17(03n04), pages 1-29.
    3. Li, Huajiao & An, Haizhong & Gao, Xiangyun & Huang, Jiachen & Xu, Qun, 2014. "On the topological properties of the cross-shareholding networks of listed companies in China: Taking shareholders’ cross-shareholding relationships into account," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 80-88.
    4. Hao, Xiaoqing & An, Haizhong & Qi, Hai & Gao, Xiangyun, 2016. "Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network," Applied Energy, Elsevier, vol. 162(C), pages 1515-1522.
    5. Franco Ruzzenenti & Diego Garlaschelli & Riccardo Basosi, 2010. "Complex Networks and Symmetry II: Reciprocity and Evolution of World Trade," Papers 1009.4489, arXiv.org.
    6. Rossana Mastrandrea & Squartini Tiziano & Giorgio Fagiolo & Diego Garlaschelli, 2014. "Reconstructing the world trade multiplex: the role of intensive and extensive biases," Post-Print hal-01113938, HAL.
    7. Barigozzi, Matteo & Fagiolo, Giorgio & Mangioni, Giuseppe, 2011. "Identifying the community structure of the international-trade multi-network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2051-2066.
    8. Zhang, Hai-Ying & Ji, Qiang & Fan, Ying, 2014. "Competition, transmission and pattern evolution: A network analysis of global oil trade," Energy Policy, Elsevier, vol. 73(C), pages 312-322.
    9. Gao, Cuixia & Sun, Mei & Shen, Bo, 2015. "Features and evolution of international fossil energy trade relationships: A weighted multilayer network analysis," Applied Energy, Elsevier, vol. 156(C), pages 542-554.
    10. Yang, Yu & Poon, Jessie P.H. & Liu, Yi & Bagchi-Sen, Sharmistha, 2015. "Small and flat worlds: A complex network analysis of international trade in crude oil," Energy, Elsevier, vol. 93(P1), pages 534-543.
    11. Zhong, Weiqiong & An, Haizhong & Gao, Xiangyun & Sun, Xiaoqi, 2014. "The evolution of communities in the international oil trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 42-52.
    12. Gergely Palla & Albert-László Barabási & Tamás Vicsek, 2007. "Quantifying social group evolution," Nature, Nature, vol. 446(7136), pages 664-667, April.
    13. Li, Huajiao & Fang, Wei & An, Haizhong & Yan, LiLi, 2014. "The shareholding similarity of the shareholders of the worldwide listed energy companies based on a two-mode primitive network and a one-mode derivative holding-based network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 525-532.
    14. An, Haizhong & Zhong, Weiqiong & Chen, Yurong & Li, Huajiao & Gao, Xiangyun, 2014. "Features and evolution of international crude oil trade relationships: A trading-based network analysis," Energy, Elsevier, vol. 74(C), pages 254-259.
    15. Pawe{l} Fiedor, 2014. "Mutual Information Rate-Based Networks in Financial Markets," Papers 1401.2548, arXiv.org.
    16. Jianxi Gao & Xueming Liu & Daqing Li & Shlomo Havlin, 2015. "Recent Progress on the Resilience of Complex Networks," Energies, MDPI, vol. 8(10), pages 1-24, October.
    17. Dassisti, M. & Carnimeo, L., 2013. "A small-world methodology of analysis of interchange energy-networks: The European behaviour in the economical crisis," Energy Policy, Elsevier, vol. 63(C), pages 887-899.
    18. Mingqi Zhang & Meirong Su & Weiwei Lu & Chunhua Su, 2015. "An Assessment of the Security of China’s Natural Gas Supply System Using Two Network Models," Energies, MDPI, vol. 8(12), pages 1-16, December.
    19. An, Feng & Gao, Xiangyun & Guan, Jianhe & Li, Huajiao & Liu, Qian, 2016. "An evolution analysis of executive-based listed company relationships using complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 276-285.
    20. Ali Mirchi & Saeed Hadian & Kaveh Madani & Omid M. Rouhani & Azadeh M. Rouhani, 2012. "World Energy Balance Outlook and OPEC Production Capacity: Implications for Global Oil Security," Energies, MDPI, vol. 5(8), pages 1-26, July.
    21. Gao, Xiangyun & An, Haizhong & Fang, Wei & Li, Huajiao & Sun, Xiaoqi, 2014. "The transmission of fluctuant patterns of the forex burden based on international crude oil prices," Energy, Elsevier, vol. 73(C), pages 380-386.
    22. Sun, Xiaoqi & An, Haizhong & Gao, Xiangyun & Jia, Xiaoliang & Liu, Xiaojia, 2016. "Indirect energy flow between industrial sectors in China: A complex network approach," Energy, Elsevier, vol. 94(C), pages 195-205.
    23. Liu, Jiming & Shi, Benyun, 2012. "Towards understanding the robustness of energy distribution networks based on macroscopic and microscopic evaluations," Energy Policy, Elsevier, vol. 49(C), pages 318-327.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zheng, Shuxian & Zhou, Xuanru & Zhao, Pei & Xing, Wanli & Han, Yawen & Hao, Hongchang & Luo, Wenbo, 2022. "Impact of countries’ role on trade prices from a nickel chain perspective: Based on complex network and panel regression analysis," Resources Policy, Elsevier, vol. 78(C).
    2. Wei, Na & Xie, Wen-Jie & Zhou, Wei-Xing, 2022. "Robustness of the international oil trade network under targeted attacks to economies," Energy, Elsevier, vol. 251(C).
    3. Guo, Yaoqi & Zheng, Ru & Zhang, Hongwei, 2023. "Tantalum trade structural dependencies are what we need: A perspective on the industrial chain," Resources Policy, Elsevier, vol. 82(C).
    4. Qiaowen Zhang & Benjamin Batinge, 2021. "A social network analysis of the structure and evolution of intra‐African trade," African Development Review, African Development Bank, vol. 33(1), pages 204-217, March.
    5. Guo, Yue & Yang, Yu & Wang, Chang, 2021. "Global energy networks: Geographies of mergers and acquisitions of worldwide oil companies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    6. Ma, Yu & Wang, Minxi & Li, Xin, 2022. "Analysis of the characteristics and stability of the global complex nickel ore trade network," Resources Policy, Elsevier, vol. 79(C).
    7. Yinpeng Liu & Xiangyun Gao & Jianfeng Guo, 2018. "Network Features of the EU Carbon Trade System: An Evolutionary Perspective," Energies, MDPI, vol. 11(6), pages 1-16, June.
    8. Liu, Haiping & Li, Huajiao & Qi, Yajie & An, Pengli & Shi, Jianglan & Liu, Yanxin, 2021. "Identification of high-risk agents and relationships in nickel, cobalt, and lithium trade based on resource-dependent networks," Resources Policy, Elsevier, vol. 74(C).
    9. Yujing Wang & Fu Ren & Ruoxin Zhu & Qingyun Du, 2020. "An Exploratory Analysis of Networked and Spatial Characteristics of International Natural Resource Trades (2000–2016)," Sustainability, MDPI, vol. 12(18), pages 1-34, September.
    10. Huang, Yubo & Dong, Hongli & Zhang, Weidong & Lu, Junguo, 2019. "Stability analysis of nonlinear oscillator networks based on the mechanism of cascading failures," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 5-15.
    11. Qingru Sun & Meiyi Hou & Shuaiwei Shi & Liwei Cui & Zenglei Xi, 2022. "The Influence of Country Risks on the International Agricultural Trade Patterns Based on Network Analysis and Panel Data Method," Agriculture, MDPI, vol. 12(3), pages 1-18, March.
    12. Wu, Congcong & Gao, Xiangyun & Xi, Xian & Zhao, Yiran & Li, Yu, 2021. "The stability optimization of the international lithium trade," Resources Policy, Elsevier, vol. 74(C).
    13. Chen, Sai & Ding, Yueting & Zhang, Yanfang & Zhang, Ming & Nie, Rui, 2022. "Study on the robustness of China's oil import network," Energy, Elsevier, vol. 239(PB).
    14. Yu, Yu & Ma, Daipeng & Zhu, Weiwei, 2023. "Resilience assessment of international cobalt trade network," Resources Policy, Elsevier, vol. 83(C).
    15. Jiang, Xuemei & Zhang, Shaoxue, 2021. "Visualizing the services embodied in global manufacturing exports," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    16. Chen, Guang & Kong, Rui & Wang, Yixin, 2020. "Research on the evolution of lithium trade communities based on the complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    17. Zhao, Yiran & Gao, Xiangyun & An, Haizhong & Xi, Xian & Sun, Qingru & Jiang, Meihui, 2020. "The effect of the mined cobalt trade dependence Network's structure on trade price," Resources Policy, Elsevier, vol. 65(C).
    18. 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.
    19. Xi, Xian & Zhou, Jinsheng & Gao, Xiangyun & Liu, Donghui & Zheng, Huiling & Sun, Qingru, 2019. "Impact of changes in crude oil trade network patterns on national economy," Energy Economics, Elsevier, vol. 84(C).
    20. Wen-Jie Xie & Na Wei & Wei-Xing Zhou, 2020. "Evolving efficiency and robustness of global oil trade networks," Papers 2004.05325, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qing Guan & Haizhong An & Xiaoqing Hao & Xiaoliang Jia, 2016. "The Impact of Countries’ Roles on the International Photovoltaic Trade Pattern: The Complex Networks Analysis," Sustainability, MDPI, vol. 8(4), pages 1-16, March.
    2. Xi, Xian & Zhou, Jinsheng & Gao, Xiangyun & Liu, Donghui & Zheng, Huiling & Sun, Qingru, 2019. "Impact of changes in crude oil trade network patterns on national economy," Energy Economics, Elsevier, vol. 84(C).
    3. Guan, Qing & An, Haizhong, 2017. "The exploration on the trade preferences of cooperation partners in four energy commodities’ international trade: Crude oil, coal, natural gas and photovoltaic," Applied Energy, Elsevier, vol. 203(C), pages 154-163.
    4. Shi, Jianglan & Li, Huajiao & Guan, Jianhe & Sun, Xiaoqi & Guan, Qing & Liu, Xiaojia, 2017. "Evolutionary features of global embodied energy flow between sectors: A complex network approach," Energy, Elsevier, vol. 140(P1), pages 395-405.
    5. Hao, Xiaoqing & An, Haizhong & Qi, Hai & Gao, Xiangyun, 2016. "Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network," Applied Energy, Elsevier, vol. 162(C), pages 1515-1522.
    6. Huan Chen & Lixin Tian & Minggang Wang & Zaili Zhen, 2017. "Analysis of the Dynamic Evolutionary Behavior of American Heating Oil Spot and Futures Price Fluctuation Networks," Sustainability, MDPI, vol. 9(4), pages 1-29, April.
    7. Zhong, Weiqiong & An, Haizhong & Shen, Lei & Fang, Wei & Gao, Xiangyun & Dong, Di, 2017. "The roles of countries in the international fossil fuel trade: An emergy and network analysis," Energy Policy, Elsevier, vol. 100(C), pages 365-376.
    8. Wang, Minggang & Chen, Ying & Tian, Lixin & Jiang, Shumin & Tian, Zihao & Du, Ruijin, 2016. "Fluctuation behavior analysis of international crude oil and gasoline price based on complex network perspective," Applied Energy, Elsevier, vol. 175(C), pages 109-127.
    9. Chen, B. & Li, J.S. & Wu, X.F. & Han, M.Y. & Zeng, L. & Li, Z. & Chen, G.Q., 2018. "Global energy flows embodied in international trade: A combination of environmentally extended input–output analysis and complex network analysis," Applied Energy, Elsevier, vol. 210(C), pages 98-107.
    10. Sun, Xiaoqi & An, Haizhong & Gao, Xiangyun & Jia, Xiaoliang & Liu, Xiaojia, 2016. "Indirect energy flow between industrial sectors in China: A complex network approach," Energy, Elsevier, vol. 94(C), pages 195-205.
    11. Wang, Wenya & Fan, L.W. & Zhou, P., 2022. "Evolution of global fossil fuel trade dependencies," Energy, Elsevier, vol. 238(PC).
    12. Zhong, Weiqiong & An, Haizhong & Shen, Lei & Dai, Tao & Fang, Wei & Gao, Xiangyun & Dong, Di, 2017. "Global pattern of the international fossil fuel trade: The evolution of communities," Energy, Elsevier, vol. 123(C), pages 260-270.
    13. Yang, Yu & Poon, Jessie P.H. & Liu, Yi & Bagchi-Sen, Sharmistha, 2015. "Small and flat worlds: A complex network analysis of international trade in crude oil," Energy, Elsevier, vol. 93(P1), pages 534-543.
    14. Peng, Peng & Yang, Yu & Cheng, Shifen & Lu, Feng & Yuan, Zimu, 2019. "Hub-and-spoke structure: Characterizing the global crude oil transport network with mass vessel trajectories," Energy, Elsevier, vol. 168(C), pages 966-974.
    15. Li, Huajiao & An, Haizhong & Huang, Jiachen & Huang, Xuan & Mou, Songtao & Shi, Yanli, 2016. "The evolutionary stability of shareholders’ co-holding behavior for China’s listed energy companies based on associated maximal connected sub-graphs of derivative holding-based networks," Applied Energy, Elsevier, vol. 162(C), pages 1601-1607.
    16. Li, Huajiao & An, Haizhong & Fang, Wei & Wang, Yue & Zhong, Weiqiong & Yan, Lili, 2017. "Global energy investment structure from the energy stock market perspective based on a Heterogeneous Complex Network Model," Applied Energy, Elsevier, vol. 194(C), pages 648-657.
    17. Li, Huajiao & An, Haizhong & Liu, Xueyong & Gao, Xiangyun & Fang, Wei & An, Feng, 2016. "Price fluctuation in the energy stock market based on fluctuation and co-fluctuation matrix transmission networks," Energy, Elsevier, vol. 117(P1), pages 73-83.
    18. An, Qier & An, Haizhong & Wang, Lang & Gao, Xiangyun & Lv, Na, 2015. "Analysis of embodied exergy flow between Chinese industries based on network theory," Ecological Modelling, Elsevier, vol. 318(C), pages 26-35.
    19. An, Pengli & Li, Huajiao & Zhou, Jinsheng & Chen, Fan, 2017. "The evolution analysis of listed companies co-holding non-listed financial companies based on two-mode heterogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 558-568.
    20. Yujing Wang & Fu Ren & Ruoxin Zhu & Qingyun Du, 2020. "An Exploratory Analysis of Networked and Spatial Characteristics of International Natural Resource Trades (2000–2016)," Sustainability, MDPI, vol. 12(18), pages 1-34, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:482:y:2017:i:c:p:345-356. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.