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Opinion Formation in the World Trade Network

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  • Célestin Coquidé

    (UTINAM - Univers, Transport, Interfaces, Nanostructures, Atmosphère et environnement, Molécules (UMR 6213) - INSU - CNRS - Institut national des sciences de l'Univers - CNRS - Centre National de la Recherche Scientifique - UFC - Université de Franche-Comté - UBFC - Université Bourgogne Franche-Comté [COMUE], DM2L - Data Mining and Machine Learning - LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information - UL2 - Université Lumière - Lyon 2 - ECL - École Centrale de Lyon - Université de Lyon - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - INSA Lyon - Institut National des Sciences Appliquées de Lyon - Université de Lyon - INSA - Institut National des Sciences Appliquées - CNRS - Centre National de la Recherche Scientifique, LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information - UL2 - Université Lumière - Lyon 2 - ECL - École Centrale de Lyon - Université de Lyon - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - INSA Lyon - Institut National des Sciences Appliquées de Lyon - Université de Lyon - INSA - Institut National des Sciences Appliquées - CNRS - Centre National de la Recherche Scientifique)

  • José Lages

    (UTINAM - Univers, Transport, Interfaces, Nanostructures, Atmosphère et environnement, Molécules (UMR 6213) - INSU - CNRS - Institut national des sciences de l'Univers - CNRS - Centre National de la Recherche Scientifique - UFC - Université de Franche-Comté - UBFC - Université Bourgogne Franche-Comté [COMUE])

  • Dima Shepelyansky

    (LPT - Laboratoire de Physique Théorique - UT3 - Université Toulouse III - Paul Sabatier - UT - Université de Toulouse - CNRS - Centre National de la Recherche Scientifique - FeRMI - Fédération de recherche « Matière et interactions » - INSA Toulouse - Institut National des Sciences Appliquées - Toulouse - INSA - Institut National des Sciences Appliquées - UT - Université de Toulouse - UT3 - Université Toulouse III - Paul Sabatier - UT - Université de Toulouse - CNRS - Centre National de la Recherche Scientifique, ICQ - Cohérence Quantique (LPT) - LPT - Laboratoire de Physique Théorique - UT3 - Université Toulouse III - Paul Sabatier - UT - Université de Toulouse - CNRS - Centre National de la Recherche Scientifique - FeRMI - Fédération de recherche « Matière et interactions » - INSA Toulouse - Institut National des Sciences Appliquées - Toulouse - INSA - Institut National des Sciences Appliquées - UT - Université de Toulouse - UT3 - Université Toulouse III - Paul Sabatier - UT - Université de Toulouse - CNRS - Centre National de la Recherche Scientifique)

Abstract

We extend the opinion formation approach to probe the world influence of economical organizations. Our opinion formation model mimics a battle between currencies within the international trade network. Based on the United Nations Comtrade database, we construct the world trade network for the years of the last decade from 2010 to 2020. We consider different core groups constituted by countries preferring to trade in a specific currency. We will consider principally two core groups, namely, five Anglo-Saxon countries that prefer to trade in US dollar and the 11 BRICS+ that prefer to trade in a hypothetical currency, hereafter called BRI, pegged to their economies. We determine the trade currency preference of the other countries via a Monte Carlo process depending on the direct transactions between the countries. The results obtained in the frame of this mathematical model show that starting from the year 2014, the majority of the world countries would have preferred to trade in BRI than USD. The Monte Carlo process reaches a steady state with three distinct groups: two groups of countries preferring to trade in whatever is the initial distribution of the trade currency preferences, one in BRI and the other in USD, and a third group of countries swinging as a whole between USD and BRI depending on the initial distribution of the trade currency preferences. We also analyze the battle between three currencies: on one hand, we consider USD, BRI and EUR, the latter currency being pegged by the core group of nine EU countries. We show that the countries preferring EUR are mainly the swing countries obtained in the frame of the two currencies model. On the other hand, we consider USD, CNY (Chinese yuan), OPE, the latter currency being pegged to the major OPEC+ economies for which we try to probe the effective economical influence within international trade. Finally, we present the reduced Google matrix description of the trade relations between the Anglo-Saxon countries and the BRICS+.

Suggested Citation

  • Célestin Coquidé & José Lages & Dima Shepelyansky, 2024. "Opinion Formation in the World Trade Network," Post-Print hal-04461784, HAL.
  • Handle: RePEc:hal:journl:hal-04461784
    DOI: 10.3390/e26020141
    Note: View the original document on HAL open archive server: https://hal.science/hal-04461784
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    References listed on IDEAS

    as
    1. Leonardo Ermann & Dima L. Shepelyansky, 2011. "Google matrix of the world trade network," Papers 1103.5027, arXiv.org.
    2. Leonardo Ermann & Dima L. Shepelyansky, 2015. "Google matrix analysis of the multiproduct world trade network," Papers 1501.03371, arXiv.org.
    3. Biswas, Soumyajyoti & Chatterjee, Arnab & Sen, Parongama, 2012. "Disorder induced phase transition in kinetic models of opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3257-3265.
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    5. Eom, Young-Ho & Shepelyansky, Dima L., 2015. "Opinion formation driven by PageRank node influence on directed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 707-715.
    6. C'elestin Coquid'e & Jos'e Lages & Dima L. Shepelyansky, 2022. "Dollar-Yuan Battle in the World Trade Network," Papers 2211.07180, arXiv.org, revised Feb 2023.
    7. Célestin Coquidé & Leonardo Ermann & José Lages & Dima L. Shepelyansky, 2019. "Influence of petroleum and gas trade on EU economies from the reduced Google matrix analysis of UN COMTRADE data," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 92(8), pages 1-14, August.
    8. A. O. Zhirov & O. V. Zhirov & D. L. Shepelyansky, 2010. "Two-dimensional ranking of Wikipedia articles," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 77(4), pages 523-531, October.
    9. Frahm, Klaus M. & Shepelyansky, Dima L., 2019. "Ising-PageRank model of opinion formation on social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    10. Katarzyna Sznajd-Weron & Józef Sznajd, 2000. "Opinion Evolution In Closed Community," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(06), pages 1157-1165.
    11. Luca De Benedictis & Lucia Tajoli, 2011. "The World Trade Network," The World Economy, Wiley Blackwell, vol. 34(8), pages 1417-1454, August.
    12. C'elestin Coquid'e & Leonardo Ermann & Jos'e Lages & D. L. Shepelyansky, 2019. "Influence of petroleum and gas trade on EU economies from the reduced Google matrix analysis of UN COMTRADE data," Papers 1903.01820, arXiv.org.
    13. Klaus M. Frahm & Katia Jaffrès-Runser & Dima L. Shepelyansky, 2016. "Wikipedia mining of hidden links between political leaders," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(12), pages 1-21, December.
    14. Leonardo Ermann & Dima Shepelyansky, 2015. "Google matrix analysis of the multiproduct world trade network," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(4), pages 1-19, April.
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