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dc.contributor.authorMarotta, Lucaen
dc.contributor.authorMiccichè, Salvatoreen
dc.contributor.authorFujiwara, Yoshien
dc.contributor.authorIyetomi, Hiroshien
dc.contributor.authorAoyama, Hideakien
dc.contributor.authorGallegati, Mauroen
dc.contributor.authorMantegna, Rosario N.en
dc.contributor.alternative青山, 秀明ja
dc.date.accessioned2017-02-17T07:45:43Z-
dc.date.available2017-02-17T07:45:43Z-
dc.date.issued2016-03-22-
dc.identifier.issn2193-1127-
dc.identifier.urihttp://hdl.handle.net/2433/218239-
dc.description.abstractWe detect the backbone of the weighted bipartite network of the Japanese credit market relationships. The backbone is detected by adapting a general method used in the investigation of weighted networks. With this approach we detect a backbone that is statistically validated against a null hypothesis of uniform diversification of loans for banks and firms. Our investigation is done year by year and it covers more than thirty years during the period from 1980 to 2011. We relate some of our findings with economic events that have characterized the Japanese credit market during the last years. The study of the time evolution of the backbone allows us to detect changes occurred in network size, fraction of credit explained, and attributes characterizing the banks and the firms present in the backbone.en
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherSpringer Natureen
dc.rights© 2016 Marotta et al. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in anymedium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.en
dc.subjectcomplex networksen
dc.subjectcredit marketen
dc.subjectinformation filteringen
dc.subjectstatistically validated networksen
dc.titleBackbone of credit relationships in the Japanese credit marketen
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.jtitleEPJ Data Scienceen
dc.identifier.volume5-
dc.relation.doi10.1140/epjds/s13688-016-0071-7-
dc.textversionpublisher-
dc.identifier.artnum10-
dcterms.accessRightsopen access-
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