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Influence of petroleum and gas trade on EU economies from the reduced Google matrix analysis of UN COMTRADE data

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Abstract

Using the United Nations COMTRADE database (United Nations Commodity Trade Statistics Database,http://comtrade.un.org/db/ (accessed January 2019)) we apply the reduced Google matrix (REGOMAX) algorithm to analyze the multiproduct world trade in years 2004–2016. Our approach allows determining the trade balance sensitivity of a group of countries to a specific product price increase from a specific exporting country taking into account all direct and indirect trade pathways via all world countries exchanging 61 UN COMTRADE identified trade products. On the basis of this approach we present the influence of trade in petroleum and gas products from Russia, USA, Saudi Arabia and Norway determining the sensitivity of each EU country. We show that the REGOMAX approach provides a new and more detailed analysis of trade influence propagation comparing to the usual approach based on export and import flows.

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References

  1. United Nations Commodity Trade Statistics Database,http://comtrade.un.org/db/ (accessed January 2019)

  2. World Trade Organization,World Trade Statistical Review 2018 (2018),https://www.wto.org/english/res_e/statis_e/wts2018_e/wts18_toc_e.htm (accessed January 2019)

  3. P.R. Krugman,M. Obstfeld,M. Melitz,International Economics: Theory & Policy(Prentic Hall,New Jersey,2011)

  4. S. Dorogovtsev,Lectures on Complex Networks(Oxford University Press,Oxford,2010)

  5. L. Ermann,D.L. Shepelyansky,Acta Phys. Pol. A120, A158(2011)

    Article  Google Scholar 

  6. L. Ermann,D.L. Shepelyansky,Eur. Phys. J. B88, 84(2015)

    Article ADS  Google Scholar 

  7. S. Brin,L. Page,Comput. Netw. ISDN Syst.30, 107(1998)

    Article  Google Scholar 

  8. A.M. Langville,C.D. Meyer,Google’s PageRank and Beyond: The Science of Search Engine Rankings(Princeton University Press,Princeton,2006)

  9. L. Ermann,K.M. Frahm,D.L. Shepelyansky,Rev. Mod. Phys.87, 1261(2015)

    Article ADS  Google Scholar 

  10. A.D. Chepelianskii,Towards physical laws for software architecture,https://arXiv:1003.5455(2010)

  11. A.O. Zhirov,O.V. Zhirov,D.L. Shepelyansky,Eur. Phys. J. B77, 523(2010)

    Article ADS  Google Scholar 

  12. K.M. Frahm,D.L. Shepelyansky,Reduced Google matrix,https://arXiv:1602.02394(2016)

  13. K.M. Frahm,K. Jaffrès-Runser,D.L. Shepelyansky,Eur. Phys. J. B89, 269(2016)

    Article ADS  Google Scholar 

  14. C. Coquide,J. Lages,D.L. Shepelyansky,Eur. Phys. J. B92, 3(2019)

    Article ADS  Google Scholar 

  15. J. Lages,D.L. Shepelyansky,A. Zinovyev,PLoS ONE13, e0190812(2018)

    Article  Google Scholar 

  16. M.A. Serrano,M. Boguna,A. Vespignani,J. Econ.Interac. Coord.2, 111(2007)

    Article  Google Scholar 

  17. G. Fagiolo,J. Reyes,S. Schiavo,Phys. Rev. E79, 036115(2009)

    Article ADS MathSciNet  Google Scholar 

  18. J. He,M.W. Deem,Phys. Rev. Lett.105, 198701(2010)

    Article ADS  Google Scholar 

  19. G. Fagiolo,J. Reyes,S. Schiavo,J. Evol. Econ.20, 479(2010)

    Article  Google Scholar 

  20. M. Barigozzi,G. Fagiolo,D. Garlaschelli,Phys. Rev. E81, 046104(2010)

    Article ADS  Google Scholar 

  21. A. Chakraborty,Y. Kichikawa,T. Iino,H. Iyetomi,H. Inoue,Y. Fujiwara,H. Aoyama,PLoS ONE13, e0202739(2018)

    Article  Google Scholar 

  22. L. De Benedictis,L. Tajoli,World Econ.34, 1417(2011)

    Article  Google Scholar 

  23. T. Deguchi,K. Takahashi,H. Takayasu,M. Takayasu,PLoS ONE9, e1001338(2014)

    Article  Google Scholar 

  24. L. Ermann,K.M. Frahm,D.L. Shepelyansky,Eur. Phys. J. B91, 127(2018)

    Article ADS  Google Scholar 

  25. J.-P. Bouchaud,M. Potters,Theory of Financial Risk and Derivative Pricing(Cambridge University Press,Cambridge,2003)

  26. M.C. Munnix,R. Schaefer,T. Guhr,PLoS ONE9, e98030(2014)

    Article ADS  Google Scholar 

  27. M. Bardoscia,G. Livan,M. Marsili,J. Stat. Mech.: Theory Exp.2017, 043402(2017)

    Article  Google Scholar 

  28. ISO 3166-1 alpha-2, Wikipedia,https://en.wikipedia.org/w/index.php?title=ISO_3166-1_alpha-2&oldid=881234177 (accessed January 2019)

  29. List of sovereign states in Europe by GDP (nominal), Wikipedia,https://en.wikipedia.org/w/index.php?title=List_of_sovereign_states_in_Europe_by_GDP_(nominal)&oldid=864980281 (accessed January 2019)

  30. Jenks natural breaks optimization, Wikipedia,https://en.wikipedia.org/wiki/Jenks_natural_breaks_optimization (accessed January 2019)

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Authors and Affiliations

  1. Institut UTINAM, OSU THETA, Université de Bourgogne Franche-Comté, CNRS, Besançon, France

    Célestin Coquidé & José Lages

  2. Departamento de Física Teórica, GIyA, CNEA, Av. Libertador 8250, (C1429BNP), Buenos Aires, Argentina

    Leonardo Ermann

  3. Laboratoire de Physique Théorique, IRSAMC, Université de Toulouse, CNRS, UPS, 31062, Toulouse, France

    Dima L. Shepelyansky

Authors
  1. Célestin Coquidé

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  2. Leonardo Ermann

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  3. José Lages

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  4. Dima L. Shepelyansky

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Corresponding author

Correspondence toDima L. Shepelyansky.

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Coquidé, C., Ermann, L., Lages, J.et al. Influence of petroleum and gas trade on EU economies from the reduced Google matrix analysis of UN COMTRADE data.Eur. Phys. J. B92, 171 (2019). https://doi.org/10.1140/epjb/e2019-100132-6

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