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dc.contributor.authorBargigli, Leonardoen_US
dc.contributor.authorGallegati, Mauroen_US
dc.date.accessioned2012-09-04en_US
dc.date.accessioned2012-09-04T15:18:42Z-
dc.date.available2012-09-04T15:18:42Z-
dc.date.issued2012en_US
dc.identifier.urihttp://hdl.handle.net/10419/62119-
dc.description.abstractIn 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.en_US
dc.language.isoengen_US
dc.publisherKiel Institute for the World Economy (IfW) Kielen_US
dc.relation.ispartofseriesEconomics Discussion Papers 2012-41en_US
dc.subject.jelC49en_US
dc.subject.jelC63en_US
dc.subject.jelD85en_US
dc.subject.jelE51en_US
dc.subject.jelG21en_US
dc.subject.ddc330en_US
dc.subject.keywordCredit networksen_US
dc.subject.keywordcommunitiesen_US
dc.subject.keywordcontagionen_US
dc.subject.keywordsystemic risken_US
dc.titleFinding communities in credit networksen_US
dc.typeWorking Paperen_US
dc.identifier.ppn723775443en_US
dc.rights.licensehttp://creativecommons.org/licenses/by-nc/2.0/de/deed.enen_US
dc.identifier.repecRePEc:zbw:ifwedp:201241-
Appears in Collections:Economics: The Open-Access, Open-Assessment E-Journal - Discussion Papers

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