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Structure and Temporal Change of the Credit Network between Banks and Large Firms in Japan

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  • Iyetomi, Hiroshi
  • Ikeda, Yuichi
  • Aoyama, Hideaki
  • Fujiwara, Yoshi
  • Souma, Wataru

Abstract

We present a new approach to understanding credit relationships between commercial banks and quoted firms, and with this approach, examine the temporal change in the structure of the Japanese credit network from 1980 to 2005. At each year, the credit network is regarded as a weighted bipartite graph where edges correspond to the relationships and weights refer to the amounts of loans. Reduction in the supply of credit affects firms as debtor, and failure of a firm influences banks as creditor. To quantify the dependency and influence between banks and firms, we propose a set of scores of banks and firms, which can be calculated by solving an eigenvalue problem determined by the weight of the credit network. We found that a few largest eigenvalues and corresponding eigenvectors are significant by using a null hypothesis of random bipartite graphs, and that the scores can quantitatively describe the stability or fragility of the credit network during the 25 years.

Suggested Citation

  • 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.
  • Handle: RePEc:zbw:ifweej:7551
    DOI: 10.5018/economics-ejournal.ja.2009-7
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    2. G. De Masi & Y. Fujiwara & M. Gallegati & B. Greenwald & J. E. Stiglitz, 2009. "An Analysis of the Japanese Credit Network," Papers 0901.2384, arXiv.org, revised Nov 2010.
    3. Kano, Masaji & Uchida, Hirofumi & Udell, Gregory F. & Watanabe, Wako, 2011. "Information verifiability, bank organization, bank competition and bank-borrower relationships," Journal of Banking & Finance, Elsevier, vol. 35(4), pages 935-954, April.
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    Citations

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    Cited by:

    1. 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.
    2. Bargigli, Leonardo & Gallegati, Mauro, 2011. "Random digraphs with given expected degree sequences: A model for economic networks," Journal of Economic Behavior & Organization, Elsevier, vol. 78(3), pages 396-411, May.
    3. Araújo, Tanya & Spelta, Alessandro, 2014. "Structural changes in cross-border liabilities: A multidimensional approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 277-287.
    4. León, C. & Berndsen, R.J. & Renneboog, L.D.R., 2014. "Financial Stability and Interacting Networks of Financial Institutions and Market Infrastructures," Other publications TiSEM 0de9add3-0338-4575-9c00-b, Tilburg University, School of Economics and Management.
    5. Abhijit Chakraborty & Hiroyasu Inoue & Yoshi Fujiwara, 2020. "Economic complexity of prefectures in Japan," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-13, August.
    6. Berndsen, Ron J. & León, Carlos & Renneboog, Luc, 2018. "Financial stability in networks of financial institutions and market infrastructures," Journal of Financial Stability, Elsevier, vol. 35(C), pages 120-135.
    7. Alessandro Spelta & Tanya Araujo, 2012. "Interlinkages and structural changes in cross-border liabilities: a network approach," Working Papers Department of Economics 2012/19, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    8. Bargigli, Leonardo & Gallegati, Mauro & Riccetti, Luca & Russo, Alberto, 2014. "Network analysis and calibration of the “leveraged network-based financial accelerator”," Journal of Economic Behavior & Organization, Elsevier, vol. 99(C), pages 109-125.
    9. León, C., 2015. "Financial stability from a network perspective," Other publications TiSEM bb2e4e44-e842-45c6-a946-4, Tilburg University, School of Economics and Management.
    10. He, Fang & Chen, Xi, 2016. "Credit networks and systemic risk of Chinese local financing platforms: Too central or too big to fail?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 158-170.
    11. 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).
    12. 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.
    13. Spelta, Alessandro & Araújo, Tanya, 2012. "The topology of cross-border exposures: Beyond the minimal spanning tree approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5572-5583.
    14. Ms. Sheri M. Markose, 2012. "Systemic Risk from Global Financial Derivatives: A Network Analysis of Contagion and Its Mitigation with Super-Spreader Tax," IMF Working Papers 2012/282, International Monetary Fund.
    15. Li, Shouwei & Liu, Yifu & Wu, Chaoqun, 2020. "Systemic risk in bank-firm multiplex networks," Finance Research Letters, Elsevier, vol. 33(C).
    16. Thiago Christiano Silva & Marcos Soares da Silva & Benjamin Miranda Tabak, 2015. "Liquidity Performance Evaluation of the Brazilian Interbank Market using a Network-Based Approach," Working Papers Series 401, Central Bank of Brazil, Research Department.
    17. Delli Gatti, Domenico & Gallegati, Mauro & Greenwald, Bruce & Russo, Alberto & Stiglitz, Joseph E., 2010. "The financial accelerator in an evolving credit network," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1627-1650, September.
    18. Di Guilmi, C. & Gallegati, M. & Landini, S. & Stiglitz, J.E., 2020. "An analytical solution for network models with heterogeneous and interacting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 189-220.

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    More about this item

    Keywords

    Banking; credit topology; bipartite network; systemic risk;
    All these keywords.

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers

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