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Structure and temporal change of the credit network between banks and large firms in Japan

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

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    Bibliographic Info

    Paper provided by arXiv.org in its series Papers with number 0901.2377.

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    Date of creation: Jan 2009
    Date of revision: May 2009
    Publication status: Published in Economics E-Journal 3 (2009) 2009-7
    Handle: RePEc:arx:papers:0901.2377

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    Web page: http://arxiv.org/

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    1. Iori, G. & Masi, G. D. & Precup, O. V. & Gabbi, G. & Caldarelli, G., 2005. "A network analysis of the Italian oversight money market," Working Papers 05/05, Department of Economics, City University London.
    2. Hirofumi Uchida & Gregory F. Udell & Wako Watanabe, 2006. "Bank Size and Lending Relationships in Japan," Discussion papers 06029, Research Institute of Economy, Trade and Industry (RIETI).
    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.
    4. Ogawa, Kazuo & Sterken, Elmer & Tokutsu, Ichiro, 2007. "Why do Japanese firms prefer multiple bank relationship? Some evidence from firm-level data," Economic Systems, Elsevier, vol. 31(1), pages 49-70, March.
    5. 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.
    6. Masanao Aoki, . "Reconstructing Macroeconomics: A Perspective from Statistical Physics and Combinatorial Stochastic Processes," UCLA Economics Online Papers 390, UCLA Department of Economics.
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    Cited by:
    1. 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.
    2. Alessandro Spelta & Tanya Araujo, 2012. "Interlinkages and structural changes in cross-border liabilities: a network approach," Working Papers Department of Economics 2012/19, ISEG - School of Economics and Management, Department of Economics, University of Lisbon.
    3. 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.
    4. 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.
    5. 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.

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