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An Impact Path Analysis of Russo–Ukrainian Conflict on the World and Policy Response Based on the Input–Output Network

Author

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  • Weidong Li

    (Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China
    Research Center for Strategy of Global Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China)

  • Anjian Wang

    (Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China
    Research Center for Strategy of Global Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China)

  • Weiqiong Zhong

    (Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China
    Research Center for Strategy of Global Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China)

  • Chunhui Wang

    (Institute of Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China
    Research Center for Strategy of Global Mineral Resources, Chinese Academy of Geological Sciences, Beijing 100037, China
    School of Earth Sciences and Resources, China University of Geosciences, Beijing 100037, China)

Abstract

With the outbreak of the Russo–Ukrainian conflict, serious economic and financial sanctions have been initiated against Russia by many nations led by the United States and Europe. In the age of economic globalization, no countries can stand or fall alone. Which countries and industries will the economic shocks caused by the sanctions affect? How will the shocks propagate through the global economic system? In this paper, we adopt the input–output analysis and complex network methods to explore an impact path analysis of the Russo–Ukrainian conflict on the world from the regional, industrial, and critical path perspectives. The results show that (1) Russian economic development tends to depend more on the interaction among domestic industries, so it has a certain compressive capacity against sanctions. (2) There is a high economic interdependence between Russia and China, Germany, the United States, France, and South Korea. Sanctions against Russia will cause quite direct and serve economic shocks on these countries alongside Russia. (3) Industries such as Mining and quarrying, energy production, Coke and refined petroleum products, Chemical and chemical products, and Construction in Russia that are acting as either the center of transforming resources, as important suppliers or consumers for adjacent industries, or with weak symmetry and strong clustering, should be particularly analyzed. (4) Key industries in Russia play an important role as consumers of German machinery and equipment; the United States’ professional, scientific, and technical activities; and as suppliers for Chinese coke and refined petroleum products and the Japanese construction industry. Finally, corresponding policy suggestions are put forward.

Suggested Citation

  • Weidong Li & Anjian Wang & Weiqiong Zhong & Chunhui Wang, 2022. "An Impact Path Analysis of Russo–Ukrainian Conflict on the World and Policy Response Based on the Input–Output Network," Sustainability, MDPI, vol. 14(14), pages 1-17, July.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8672-:d:863580
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    References listed on IDEAS

    as
    1. Stolz, Simon & Schlereth, Christian, 2021. "Predicting Tie Strength with Ego Network Structures," Journal of Interactive Marketing, Elsevier, vol. 54(C), pages 40-52.
    2. Cuestas, Juan Carlos & Regis, Paulo José, 2013. "Purchasing power parity in OECD countries: Nonlinear unit root tests revisited," Economic Modelling, Elsevier, vol. 32(C), pages 343-346.
    3. H. Ben Hassine & F. Boudier & C. Mathieu, 2017. "The two ways of FDI R&D spillovers: evidence from the French manufacturing industry," Applied Economics, Taylor & Francis Journals, vol. 49(25), pages 2395-2408, May.
    4. Lenzen, Manfred, 2007. "Structural path analysis of ecosystem networks," Ecological Modelling, Elsevier, vol. 200(3), pages 334-342.
    5. Wei Li & Dror Y. Kenett & Kazuko Yamasaki & H. Eugene Stanley & Shlomo Havlin, 2014. "Ranking the Economic Importance of Countries and Industries," Papers 1408.0443, arXiv.org.
    6. Lizhi Xing & Qing Ye & Jun Guan, 2016. "Spreading Effect in Industrial Complex Network Based on Revised Structural Holes Theory," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-18, May.
    7. Wiedmann, Thomas, 2009. "A review of recent multi-region input-output models used for consumption-based emission and resource accounting," Ecological Economics, Elsevier, vol. 69(2), pages 211-222, December.
    8. Grazzini, Jakob & Spelta, Alessandro, 2022. "An empirical analysis of the global input–output network and its evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    9. Daron Acemoglu & Vasco M. Carvalho & Asuman Ozdaglar & Alireza Tahbaz‐Salehi, 2012. "The Network Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 80(5), pages 1977-2016, September.
    10. Defourny, Jacques & Thorbecke, Erik, 1984. "Structural Path Analysis and Multiplier Decomposition within a Social Accounting Matrix Framework," Economic Journal, Royal Economic Society, vol. 94(373), pages 111-136, March.
    11. Ando, Sakai, 2014. "Measuring US sectoral shocks in the world input–output network," Economics Letters, Elsevier, vol. 125(2), pages 204-207.
    12. Satoshi Inomata & Anne Owen, 2014. "Comparative Evaluation Of Mrio Databases," Economic Systems Research, Taylor & Francis Journals, vol. 26(3), pages 239-244, September.
    13. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    14. Anne Owen & Richard Wood & John Barrett & Andrew Evans, 2016. "Explaining value chain differences in MRIO databases through structural path decomposition," Economic Systems Research, Taylor & Francis Journals, vol. 28(2), pages 243-272, June.
    15. Chang K. Seung, 2015. "Untangling Economic Impacts for Alaska Fisheries: A Structural Path Analysis," Marine Resource Economics, University of Chicago Press, vol. 30(3), pages 331-347.
    16. Tsutomu Harada, 2015. "Changing Productive Relations, Linkage Effects, and Industrialization," Economic Systems Research, Taylor & Francis Journals, vol. 27(3), pages 374-390, September.
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    1. Trucmel Irina-Maria & Vintila Alexandra, 2023. "An Assessment of the Russo-Ukrainian Conflict on the European Cereal Exports Using Network Theory," Journal of Social and Economic Statistics, Sciendo, vol. 12(1), pages 46-62, July.

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