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Finding communities in credit networks

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  • Bargigli, Leonardo
  • Gallegati, Mauro

Abstract

In this paper the authors focus on credit connections as a potential source of systemic risk. In particular, they seek to answer the following question: how do we find densely connected subsets of nodes within a credit network? The question is relevant for policy, since these subsets are likely to channel any shock affecting the network. As it turns out, a reliable answer can be obtained with the aid of complex network theory. In particular, the authors show how it is possible to take advantage of the community detection network literature. The proposed answer entails two subsequent steps. Firstly, the authors need to verify the hypothesis that the network under study truly has communities. Secondly, they need to devise a reliable algorithm to find those communities. In order to be sure that a given algorithm works, they need to test it over a sample of random benchmark networks with known communities. To overcome the limitation of existing benchmarks, the authors introduce a new model and test alternative algorithms, obtaining very good results with an adapted spectral decomposition method. To illustrate this method they provide a community description of the Japanese bank-firm credit network, getting evidence of a strengthening of communities over time and finding support for the well-known Japanese main bank system. Thus, the authors find comfort both from simulations and from real data on the possibility to apply community detection methods to credit markets. They believe that this method can fruitfully complement the study of contagious defaults, since the likelihood of intracommunity default contagion is expected to be high. --

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Bibliographic Info

Paper provided by Kiel Institute for the World Economy in its series Economics Discussion Papers with number 2012-41.

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Date of creation: 2012
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Handle: RePEc:zbw:ifwedp:201241

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Keywords: Credit networks; communities; contagion; systemic risk;

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References

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  1. E. N. Sawardecker & C. A. Amundsen & M. Sales-Pardo & L. A.N. Amaral, 2009. "Comparison of methods for the detection of node group membership in bipartite networks," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, Springer, vol. 72(4), pages 671-677, December.
  2. Helmut Elsinger & Alfred Lehar & Martin Summer, 2006. "Systemically important banks: an analysis for the European banking system," International Economics and Economic Policy, Springer, Springer, vol. 3(1), pages 73-89, April.
  3. Kavonius, Ilja Kristian & Castrén, Olli, 2009. "Balance Sheet Interlinkages and Macro-Financial Risk Analysis in the Euro Area," Working Paper Series, European Central Bank 1124, European Central Bank.
  4. Aoki,Masanao & Yoshikawa,Hiroshi, 2007. "Reconstructing Macroeconomics," Cambridge Books, Cambridge University Press, Cambridge University Press, number 9780521831062.
  5. Paolo Emilio Mistrulli, 2007. "Assessing financial contagion in the interbank market: Maximum entropy versus observed interbank lending patterns," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area 641, Bank of Italy, Economic Research and International Relations Area.
  6. Nier, Erlend & Yang, Jing & Yorulmazer, Tanju & Alentorn, Amadeo, 2008. "Network models and financial stability," Bank of England working papers, Bank of England 346, Bank of England.
  7. Upper, Christian & Worms, Andreas, 2004. "Estimating bilateral exposures in the German interbank market: Is there a danger of contagion?," European Economic Review, Elsevier, Elsevier, vol. 48(4), pages 827-849, August.
  8. Iman van Lelyveld & Franka Liedorp, 2006. "Interbank Contagion in the Dutch Banking Sector: A Sensitivity Analysis," International Journal of Central Banking, International Journal of Central Banking, International Journal of Central Banking, vol. 2(2), May.
  9. Battiston, Stefano & Delli Gatti, Domenico & Gallegati, Mauro & Greenwald, Bruce & Stiglitz, Joseph E., 2012. "Liaisons dangereuses: Increasing connectivity, risk sharing, and systemic risk," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 36(8), pages 1121-1141.
  10. Bargigli, Leonardo & Gallegati, Mauro, 2011. "Random digraphs with given expected degree sequences: A model for economic networks," Journal of Economic Behavior & Organization, Elsevier, Elsevier, vol. 78(3), pages 396-411, May.
  11. 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.
  12. Upper, Christian, 2011. "Simulation methods to assess the danger of contagion in interbank markets," Journal of Financial Stability, Elsevier, Elsevier, vol. 7(3), pages 111-125, August.
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Cited by:
  1. Wäckerle, Manuel, 2013. "On the bottom-up foundations of the banking-macro nexus," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 7(40), pages 1-45.

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