Krichene Hazem, Chakraborty Abhijit, Inoue Hiroyasu, Fujiwara Yoshi
Graduate School of Simulation Studies, University of Hyogo, Japan.
PLoS One. 2017 Oct 23;12(10):e0186467. doi: 10.1371/journal.pone.0186467. eCollection 2017.
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.
这项工作旨在研究和解释日本生产网络的商业周期相关性。我们考虑供应商 - 客户网络，它是一个有向网络，代表日本公司之间的贸易联系（从供应商到客户的链接）。该网络的社区结构通过应用Infomap算法来确定。每个社区由其国内生产总值及其相关的商业周期定义。基于copula理论估计社区之间的商业周期相关性。然后，基于公司的属性和网络拓扑结构，通过线性计量经济模型来解释这些相关性。结果显示出日本生产网络中商业周期相关性的有力证据。发现高负向或正向冲击存在重大系统性风险。这些相关性主要由行业和地理相似性来解释。此外，我们的结果突出了小社区和小公司更高的脆弱性，这可以通过生产网络的异配混合来解释。
