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Hierarchical and Circular Flow Structure of the Interfirm Transaction Network in Japan

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  • KICHIKAWA Yuichi
  • IINO Takashi
  • IYETOMI Hiroshi
  • INOUE Hiroyasu

Abstract

The objective of this study is to shed new light on the industrial flow structure embedded in microscopic supplier-buyer relations. We first construct directed networks from actual data from interfirm transaction relations in Japan; as one example, the dataset compiled by the Tokyo Shoko Research, Ltd. in 2016 contains five million links between one million firms. Then, we analyze the industrial flow structure of such a large-scale network with a special emphasis on its hierarchy and circularity. The Helmholtz-Hodge decomposition enables us to break down the flow on a directed network into two flow components: gradient flow and circular flow. The gradient flow between a pair of nodes is given by the difference of their potentials obtained by the Helmholtz-Hodge decomposition. The gradient flow runs from a node with higher potential to a node with lower potential; hence, the potential of a node shows its hierarchical position in a network. On the other hand, the circular flow component illuminates feedback loops built in a network. The potential values averaged over firms classified by the major industrial category describe hierarchical characteristics of sectors. The ordering of sectors according to the potential agrees well with the general idea of the supply chain. We also identify industrially integrated clusters of firms by applying a flow-based community detection method to the extracted circular flow network. We then find that each of the major communities is characterized by its main industry, forming a hierarchical supply chain with feedback loops by complementary industries such as transport and services.

Suggested Citation

  • KICHIKAWA Yuichi & IINO Takashi & IYETOMI Hiroshi & INOUE Hiroyasu, 2019. "Hierarchical and Circular Flow Structure of the Interfirm Transaction Network in Japan," Discussion papers 19063, Research Institute of Economy, Trade and Industry (RIETI).
  • Handle: RePEc:eti:dpaper:19063
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    References listed on IDEAS

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    1. Vasco Carvalho, 2007. "Aggregate fluctuations and the network structure of intersectoral trade," Economics Working Papers 1206, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2010.
    2. Slater, P B, 1978. "The Network Structure of the United States Input-Output Table," Empirical Economics, Springer, vol. 3(1), pages 49-70.
    3. Hayato Goto & Hideki Takayasu & Misako Takayasu, 2017. "Estimating risk propagation between interacting firms on inter-firm complex network," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-12, October.
    4. 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.
    5. Jianxi Luo & Carliss Y. Baldwin & Daniel E. Whitney & Christopher L. Magee, 2012. "The architecture of transaction networks: a comparative analysis of hierarchy in two sectors," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 21(6), pages 1307-1335, December.
    6. Martha G. Alatriste Contreras & Giorgio Fagiolo, 2014. "Propagation of economic shocks in input-output networks: A cross-country analysis," Post-Print hal-01474258, HAL.
    7. Tsutomu Watanabe & Iichiro Uesugi & Arito Ono (ed.), 2015. "The Economics of Interfirm Networks," Advances in Japanese Business and Economics, Springer, edition 127, number 978-4-431-55390-8.
    8. Slater, Paul B, 1977. "The Determination of Groups of Functionally Integrated Industries in the United States Using a 1967 Interindustry Flow Table," Empirical Economics, Springer, vol. 2(1), pages 1-9.
    9. Elisa Letizia & Paolo Barucca & Fabrizio Lillo, 2018. "Resolution of ranking hierarchies in directed networks," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-25, February.
    10. Giulio Cainelli & Sandro Montresor & Giuseppe Vittucci Marzetti, 2013. "Production and financial linkages in inter-firm networks: structural variety, risk-sharing and resilience," Economic Complexity and Evolution, in: Andreas Pyka & Esben Sloth Andersen (ed.), Long Term Economic Development, edition 127, pages 113-136, Springer.
    11. McNerney, James & Fath, Brian D. & Silverberg, Gerald, 2013. "Network structure of inter-industry flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6427-6441.
    12. Abhijit Chakraborty & Yuichi Kichikawa & Takashi Iino & Hiroshi Iyetomi & Hiroyasu Inoue & Yoshi Fujiwara & Hideaki Aoyama, 2018. "Hierarchical communities in the walnut structure of the Japanese production network," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-25, August.
    13. Elisa Letizia & Fabrizio Lillo, 2017. "Corporate payments networks and credit risk rating," Papers 1711.07677, arXiv.org, revised Sep 2018.
    14. Vestal, James E., 1995. "Planning for Change: Industrial Policy and Japanese Economic Development 1945-1990," OUP Catalogue, Oxford University Press, number 9780198290278.
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    Cited by:

    1. Yoshi Fujiwara & Hiroyasu Inoue & Takayuki Yamaguchi & Hideaki Aoyama & Takuma Tanaka, 2020. "Money flow network among firms' accounts in a regional bank of Japan," Papers 2007.14630, arXiv.org, revised Jul 2020.

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