|Author Name||FUJIWARA Yoshi (University of Hyogo) / INOUE Hiroyasu (University of Hyogo) / YAMAGUCHI Takayuki (Shiga University) / AOYAMA Hideaki (Faculty Fellow, RIETI) / TANAKA Takuma (Shiga University) / KIKUCHI Kentaro (Shiga University)|
|Creation Date/NO.||January 2021 21-E-005|
|Research Project||Macro-Economy under COVID-19 influence: Data-intensive analysis and the road to recovery|
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In this study, we investigate the flow of money among bank accounts possessed by firms in a single region by employing an exhaustive list of all the bank transfers in a regional bank in Japan, to clarify how the network of money flow is related to the economic activities of the firms. The network statistics and structures are examined and shown to be similar to those of a nationwide production network. Specifically, the bowtie analysis indicates what we refer to as a "walnut" structure with core and upstream/downstream components. To quantify the location of an individual account in the network, we used the Hodge decomposition method and found that the Hodge potential of the account has a significant correlation to its position in the bowtie structure as well as to its net flow of incoming and outgoing money and links, namely the net demand/supply of individual accounts. In addition, we used non-negative matrix factorization to identify important factors underlying the entire flow of money; it can be interpreted that these factors are associated with regional economic activities. One factor has a feature whereby the remittance source is localized to the largest city in the region, while the destination is scattered. The other factors correspond to the economic activities specific to different local places. This study serves as a basis for further investigation on the relationship between money flow and economic activities of firms.
Published: Fujiwara, Yoshi, Hiroyasu Inoue, Takayuki Yamaguchi, Hideaki Aoyama, Takuma Tanaka, and Kentaro Kikuchi, 2021. "Money flow network among firms' accounts in a regional bank of Japan," EPJ Data Science, 10, Article number: 19.