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Business cycles’ correlation and systemic risk of the Japanese supplier-customer network
by
Inoue, Hiroyasu
, Chakraborty, Abhijit
, Fujiwara, Yoshi
, Krichene, Hazem
in
Algorithms
/ Biology and Life Sciences
/ Business
/ Business cycles
/ Commerce
/ Communities
/ Community structure
/ Computer and Information Sciences
/ Correlation
/ Correlation analysis
/ Earth Sciences
/ Ecology and Environmental Sciences
/ Econometrics
/ Engineering and Technology
/ Japan
/ Physical Sciences
/ Risk
/ Simulation
/ Social Sciences
/ Topology
/ Vendor relations
2017
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Business cycles’ correlation and systemic risk of the Japanese supplier-customer network
by
Inoue, Hiroyasu
, Chakraborty, Abhijit
, Fujiwara, Yoshi
, Krichene, Hazem
in
Algorithms
/ Biology and Life Sciences
/ Business
/ Business cycles
/ Commerce
/ Communities
/ Community structure
/ Computer and Information Sciences
/ Correlation
/ Correlation analysis
/ Earth Sciences
/ Ecology and Environmental Sciences
/ Econometrics
/ Engineering and Technology
/ Japan
/ Physical Sciences
/ Risk
/ Simulation
/ Social Sciences
/ Topology
/ Vendor relations
2017
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Do you wish to request the book?
Business cycles’ correlation and systemic risk of the Japanese supplier-customer network
by
Inoue, Hiroyasu
, Chakraborty, Abhijit
, Fujiwara, Yoshi
, Krichene, Hazem
in
Algorithms
/ Biology and Life Sciences
/ Business
/ Business cycles
/ Commerce
/ Communities
/ Community structure
/ Computer and Information Sciences
/ Correlation
/ Correlation analysis
/ Earth Sciences
/ Ecology and Environmental Sciences
/ Econometrics
/ Engineering and Technology
/ Japan
/ Physical Sciences
/ Risk
/ Simulation
/ Social Sciences
/ Topology
/ Vendor relations
2017
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Business cycles’ correlation and systemic risk of the Japanese supplier-customer network
Journal Article
Business cycles’ correlation and systemic risk of the Japanese supplier-customer network
2017
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Overview
This work aims to study and explain the business cycle correlations of the Japanese production network. We consider the supplier-customer network, which is a directed network representing the trading links between Japanese firms (links from suppliers to customers). The community structure of this network is determined by applying the Infomap algorithm. Each community is defined by its GDP and its associated business cycle. Business cycle correlations between communities are estimated based on copula theory. Then, based on firms' attributes and network topology, these correlations are explained through linear econometric models. The results show strong evidence of business cycle correlations in the Japanese production network. A significant systemic risk is found for high negative or positive shocks. These correlations are explained mainly by the sector and by geographic similarities. Moreover, our results highlight the higher vulnerability of small communities and small firms, which is explained by the disassortative mixing of the production network.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
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