Money flow network among firms’ accounts in a regional bank of Japan

Abstract

In this study, we investigate the flow of money among bank accounts possessed by firms in a 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.

Disruption of international trade and its propagation through firm-level domestic supply chains: A case of Japan

“…Fig 5 in S1 Appendix shows the average potential of importers from various regions by industry, indicating that manufacturing industries (codes 9-32) are relatively upstream, while wholesale (50)(51)(52)(53)(54)(55), retail (56)(57)(58)(59)(60)(61), and finance (62-67) industries are more downstream, confirming the finding in the literature [43].…”

“…A potential flow from one node to another is determined by the degree of upstreamness/downstreamness of the nodes in a network [42], whereas loop flows are given by the constraint that the summation of the incoming and outgoing loop flows of any node equals zero. This method can be applied to any network to compute potential and loop flows, even if the network is complex [43,[56][57][58].…”

Identifying sinks and sources of human flows: A new approach to characterizing urban structures

“…This spatially embedded network has been intensively studied in network science (Barthelemy, 2011) and has also been utilized to detect the limits of cities (Amini et al, 2014; Fujishima et al, 2020; Huang et al, 2018; Zhong et al, 2014). Third, from the viewpoint of network analysis, the potential of combinatorial Hodge theory has been used for the analysis of gene regulatory networks (Maehara and Ohkawa, 2019; Qiu et al, 2022), neural networks (Haruna and Fujiki, 2016; Miura and Aoki, 2015), inter-firm transaction networks (Fujiwara et al, 2021; Kichikawa et al, 2019), and the correlation network of macroeconomic indicators (Iyetomi et al, 2020).…”