Research on the Statistical Properties and Stability of Complex Interindustrial Networks

Abstract

This study consolidates input-output data from 42 sectors across 31 provinces and regions in China into a unified dataset for 42 industrial sectors within eight major economic zones. Leveraging the maximum entropy method, we identify significant interindustrial relationships, subsequently forming a directed, weighted, complex network of these ties. Building upon this intricate network, we analyze its foundational statistical attributes. The stability of the network’s structure is further assessed through simulations of varied network attacks. Our findings demonstrate that the maximum entropy method is adept at extracting notable relationships between industrial sectors, facilitating the creation of a cogent complex interindustrial network. Although this established network exhibits high stability, it calls for targeted policy interventions and risk management, especially for industries with pronounced degree centrality and betweenness centrality. These pivotal industry nodes play a decisive role in the overall stability of the network. The insights derived from our examination of complex interindustrial networks illuminate the structure and function of industrial networks, bearing profound implications for policymaking and propelling sustainable, balanced economic progress.