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The similarity of global value chains: A network-based measure

Author

Listed:
  • ZHU, ZHEN
  • MORRISON, GREG
  • PULIGA, MICHELANGELO
  • CHESSA, ALESSANDRO
  • RICCABONI, MASSIMO

Abstract

International trade has been increasingly organized in the form of global value chains (GVCs). In this paper, we provide a new method for comparing GVCs across countries and over time. First, we use the World Input–Output Database (WIOD) to construct both the upstream and the downstream global value networks. Second, we introduce a network-based measure of node similarity to compare the GVCs between any pair of countries for each sector and each year available in the WIOD. Our network-based similarity is a better measure for node comparison than the existing ones because it takes into account all the direct and indirect relationships between the country–sector pairs, is applicable to both directed and weighted networks with self-loops, and takes into account externally defined node attributes. As a result, our measure of similarity reveals the most intensive interactions among the GVCs across countries and over time. From 1995 to 2011, the average similarity between sectors and countries have clear increasing trends, which are temporarily interrupted by the recent economic crisis. This measure of the similarity of GVCs provides quantitative answers to important questions about dependency, sustainability, risk, and competition in the global production system.

Suggested Citation

  • Zhu, Zhen & Morrison, Greg & Puliga, Michelangelo & Chessa, Alessandro & Riccaboni, Massimo, 2018. "The similarity of global value chains: A network-based measure," Network Science, Cambridge University Press, vol. 6(4), pages 607-632, December.
  • Handle: RePEc:cup:netsci:v:6:y:2018:i:04:p:607-632_00
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    Cited by:

    1. Russo, Margherita & Alboni, Fabrizio & Sanginés, Jorge Carreto & De Domenico, Manlio & Mangioni, Giuseppe & Righi, Simone & Simonazzi, Annamaria, 2023. "Regionalisation and cross-region integration. Twin dynamics in the automotive international trade networks," Structural Change and Economic Dynamics, Elsevier, vol. 67(C), pages 98-114.
    2. Xing, Lizhi & Guan, Jun & Dong, Xianlei & Wu, Shan, 2018. "Understanding the competitive advantage of TPP-related nations from an econophysics perspective: Influence caused by China and the United States," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 164-184.
    3. Rodolfo Metulini & Giorgio Gnecco & Francesco Biancalani & Massimo Riccaboni, 2023. "Hierarchical clustering and matrix completion for the reconstruction of world input–output tables," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(3), pages 575-620, September.
    4. Xing, Lizhi & Wang, Dawei & Li, Yan & Guan, Jun & Dong, Xianlei, 2020. "Simulation analysis of the competitive status between China and Portuguese-speaking countries under the background of one belt and one road initiative," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    5. Stefano Costa & Federico Sallusti, 2016. "Message from an Italian bottleneck: inter-industry relationships and efficiency spillover," Working Papers LuissLab 16128, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    6. Giorgio Gnecco & Federico Nutarelli & Massimo Riccaboni, 2023. "Matrix completion of world trade: An analysis of interpretability through Shapley values," The World Economy, Wiley Blackwell, vol. 46(9), pages 2707-2731, September.
    7. Yu, Chunjiao & Zhao, Jiaqi & Cheng, Shixiong, 2023. "GVC trade and business cycle synchronization between China and belt-road countries," Economic Modelling, Elsevier, vol. 126(C).
    8. Xiaolong Gao & Changfei Li & Ehsan Elahi & Mohammad Ilyas Abro & Zhaocai Cui, 2023. "Technological Innovation, Product Quality and Upgrading of Manufacturing Value Chain: Empirical Evidence from China," Sustainability, MDPI, vol. 15(9), pages 1-19, April.
    9. Amat Adarov, 2021. "Interactions Between Global Value Chains and Foreign Direct Investment: A Network Approach," wiiw Working Papers 204, The Vienna Institute for International Economic Studies, wiiw.
    10. Xing, Lizhi & Guan, Jun & Wu, Shan, 2018. "Measuring the impact of final demand on global production system based on Markov process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 148-163.

    More about this item

    JEL classification:

    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • F10 - International Economics - - Trade - - - General
    • F15 - International Economics - - Trade - - - Economic Integration

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