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Bank-Firm Credit Network in Japan: An Analysis of a Bipartite Network

Author

Listed:
  • Luca Marotta
  • Salvatore Miccichè
  • Yoshi Fujiwara
  • Hiroshi Iyetomi
  • Hideaki Aoyama
  • Mauro Gallegati
  • Rosario N Mantegna

Abstract

We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32-year-long analysis we detect a persistence of the over-expression of attributes of communities of banks and firms together with a slow dynamic of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms.

Suggested Citation

  • Luca Marotta & Salvatore Miccichè & Yoshi Fujiwara & Hiroshi Iyetomi & Hideaki Aoyama & Mauro Gallegati & Rosario N Mantegna, 2015. "Bank-Firm Credit Network in Japan: An Analysis of a Bipartite Network," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-18, May.
  • Handle: RePEc:plo:pone00:0123079
    DOI: 10.1371/journal.pone.0123079
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    1. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    2. Yoshi Fujiwara & Hideaki Aoyama & Yuichi Ikeda & Hiroshi Iyetomi & Wataru Souma, 2009. "Structure and temporal change of the credit network between banks and large firms in Japan," Papers 0901.2377, arXiv.org, revised May 2009.
    3. Bargigli, Leonardo & Gallegati, Mauro, 2013. "Finding communities in credit networks," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 7, pages 1-39.
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    5. Fujiwara, Yoshi & Aoyama, Hideaki & Ikeda, Yuichi & Iyetomi, Hiroshi & Souma, Wataru, 2009. "Structure and Temporal Change of Credit Network between Banks and Large Firms in Japan," Economics Discussion Papers 2009-1, Kiel Institute for the World Economy (IfW Kiel).
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    8. Iyetomi, Hiroshi & Ikeda, Yuichi & Aoyama, Hideaki & Fujiwara, Yoshi & Souma, Wataru, 2009. "Structure and Temporal Change of the Credit Network between Banks and Large Firms in Japan," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-18.
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    Cited by:

    1. Landaberry, Victoria & Caccioli, Fabio & Rodriguez-Martinez, Anahi & Baron, Andrea & Martinez-Jaramillo, Serafin & Lluberas, Rodrigo, 2021. "The contribution of the intra-firm exposures network to systemic risk," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 2(2).
    2. Ramirez-Marquez, J.E. & Rocco, C.M. & Moronta, J. & Gama Dessavre, D., 2016. "Robustness in network community detection under links weights uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 88-95.
    3. Barón, Andrea & Landaberry, María Victoria & Lluberas, Rodrigo & Ponce, Jorge, 2021. "Commercial and banking credit network in Uruguay," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 2(3).
    4. Chakraborty, Abhijit & Krichene, Hazem & Inoue, Hiroyasu & Fujiwara, Yoshi, 2019. "Characterization of the community structure in a large-scale production network in Japan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 210-221.
    5. Yanquen, Eduardo & Livan, Giacomo & Montañez-Enriquez, Ricardo & Martinez-Jaramillo, Serafin, 2022. "Measuring systemic risk for bank credit networks: A multilayer approach," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 3(2).
    6. Luca Marotta & Salvatore Miccich`e & Yoshi Fujiwara & Hiroshi Iyetomi & Hideaki Aoyama & Mauro Gallegati & Rosario N. Mantegna, 2015. "Backbone of credit relationships in the Japanese credit market," Papers 1511.06870, arXiv.org.
    7. Diaz de la Fuente Manuel, 2023. "Análisis de la Topología de las relaciones entre Bancos y Firmas mediante Redes Complejas: comparación del caso de Argentina e Italia," Asociación Argentina de Economía Política: Working Papers 4647, Asociación Argentina de Economía Política.
    8. Opeoluwa Banwo & Fabio Caccioli & Paul Harrald & Francesca Medda, 2016. "The Effect Of Heterogeneity On Financial Contagion Due To Overlapping Portfolios," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 19(08), pages 1-20, December.
    9. Ermanno Catullo & Antonio Palestrini & Ruggero Grilli & Mauro Gallegati, 2018. "Early warning indicators and macro-prudential policies: a credit network agent based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 81-115, April.
    10. Bikramjit Das & Vicky Fasen-Hartmann, 2023. "Measuring risk contagion in financial networks with CoVaR," Papers 2309.15511, arXiv.org, revised Jun 2024.
    11. Sebastian Poledna & Abraham Hinteregger & Stefan Thurner, 2018. "Identifying systemically important companies in the entire liability network of a small open economy," Papers 1801.10487, arXiv.org.
    12. Duc Thi Luu, 2022. "Portfolio Correlations in the Bank-Firm Credit Market of Japan," Computational Economics, Springer;Society for Computational Economics, vol. 60(2), pages 529-569, August.
    13. Rocco, Claudio M. & Moronta, José & Ramirez-Marquez, José E. & Barker, Kash, 2017. "Effects of multi-state links in network community detection," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 46-56.
    14. Wu, Yujia & Lan, Wei & Fan, Xinyan & Fang, Kuangnan, 2024. "Bipartite network influence analysis of a two-mode network," Journal of Econometrics, Elsevier, vol. 239(2).
    15. Margarita Baltakienė & Kęstutis Baltakys & Juho Kanniainen & Dino Pedreschi & Fabrizio Lillo, 2019. "Clusters of investors around initial public offering," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-14, December.
    16. Bryan S. Graham, 2020. "Sparse network asymptotics for logistic regression," Papers 2010.04703, arXiv.org.

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