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Bank-firm credit network in Japan: an analysis of a bipartite network
We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtai...
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Published in: | PloS one 2015-05, Vol.10 (5), p.e0123079 |
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description | We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32-year-long analysis we detect a persistence of the over-expression of attributes of communities of banks and firms together with a slow dynamic of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms. |
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Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32-year-long analysis we detect a persistence of the over-expression of attributes of communities of banks and firms together with a slow dynamic of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0123079</identifier><identifier>PMID: 25933413</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Banks ; Commerce ; Communities ; Datasets ; Economic sectors ; Economics ; Empirical analysis ; Evolution ; Financial statements ; Geographical distribution ; International conferences ; Japan ; Markets ; Overexpression ; Probability ; Residence Characteristics ; Science ; Statistical methods ; Stock exchanges ; Studies ; Time Factors</subject><ispartof>PloS one, 2015-05, Vol.10 (5), p.e0123079</ispartof><rights>2015 Marotta et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2015 Marotta et al 2015 Marotta et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c537t-a7365ea7c0f1ffb10264b5b54d47ced6d365b737f9a2756e54a1c82c4d6f9a43</citedby><cites>FETCH-LOGICAL-c537t-a7365ea7c0f1ffb10264b5b54d47ced6d365b737f9a2756e54a1c82c4d6f9a43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1677644899/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1677644899?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25933413$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Huerta-Quintanilla, Rodrigo</contributor><creatorcontrib>Marotta, Luca</creatorcontrib><creatorcontrib>Miccichè, Salvatore</creatorcontrib><creatorcontrib>Fujiwara, Yoshi</creatorcontrib><creatorcontrib>Iyetomi, Hiroshi</creatorcontrib><creatorcontrib>Aoyama, Hideaki</creatorcontrib><creatorcontrib>Gallegati, Mauro</creatorcontrib><creatorcontrib>Mantegna, Rosario N</creatorcontrib><title>Bank-firm credit network in Japan: an analysis of a bipartite network</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. 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Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms.</description><subject>Algorithms</subject><subject>Banks</subject><subject>Commerce</subject><subject>Communities</subject><subject>Datasets</subject><subject>Economic sectors</subject><subject>Economics</subject><subject>Empirical analysis</subject><subject>Evolution</subject><subject>Financial statements</subject><subject>Geographical distribution</subject><subject>International conferences</subject><subject>Japan</subject><subject>Markets</subject><subject>Overexpression</subject><subject>Probability</subject><subject>Residence Characteristics</subject><subject>Science</subject><subject>Statistical methods</subject><subject>Stock exchanges</subject><subject>Studies</subject><subject>Time 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subjects | Algorithms Banks Commerce Communities Datasets Economic sectors Economics Empirical analysis Evolution Financial statements Geographical distribution International conferences Japan Markets Overexpression Probability Residence Characteristics Science Statistical methods Stock exchanges Studies Time Factors |
title | Bank-firm credit network in Japan: an analysis of a bipartite network |
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