Heterogeneous Economic Networks

Summary The Japanese shareholding network at the end of March 2002 is studied. To understand the characteristics of this network intuitively, we visualize it as a directed graph and an adjacency matrix. Especially detailed features of networks concerned with the automobile industry sector are discussed by using the visualized networks. The shareholding network is also considered as an undirected graph, because many quantities characterizing networks are defined for undirected cases. For this undirected shareholding network, we show that a degree distribution is well fitted by a power law function with an exponential tail. The exponent in the power law range is γ = 1.8. We also show that the spectrum of this network follows asymptotically the power law distribution with the exponent δ = 2.6. By comparison with γ and δ, we find a scaling relation δ = 2γ − 1. The reason why this relation holds is attributed to the local tree-like structure of networks. To clarify this structure, the correlation between degrees and clustering coefficients is considered. We show that this correlation is negative and fitted by the power law function with the exponent α = 1.1. This guarantees the local tree-like structure of the network and suggests the existence of a hierarchical structure. We also show that the degree correlation is negative and follows the power law function with the exponent ν = 0.8. This indicates a degree-nonassortative network, in which hubs are not directly connected with each other. To understand these features of the network from the viewpoint of a company’s growth, we consider the correlation between the degree and the company’s total assets and age. It is clarified that the degree and the company’s total assets correlate strongly, but the degree and the company’s age have no correlation.