Characteristics and Influencing Factors of Provincial Industrial Convergence Networks in China

Abstract

Abstract The 20th National Congress of the Communist Party of China proposed accelerating the promotion of Chinese-style modernization, placing higher requirements on regional economic development. In this context, interregional industrial convergence has become a new driving force for achieving high-quality economic development and regional industrial transformation and upgrading. Using the 2017 interregional input-output table provided by Carbon Emission Accounts and Datasets (CEADs), this study constructs a directed weighted network from both the supply side and the demand side, with “province-industry” as the node and the real flow between industries as the edge weight. Network analysis is used to investigate the overall status of industrial convergence in China, as well as differences according to industry and region. Finally, an exponential random graph model (ERGM) is used to examine the influencing factors and effects of network formation. The results show the following: (1) the industrial convergence relationship between regions in China is transitive and reciprocal, and the overall tendency of the network is one in which output capacity is greater than absorption capacity. (2) The marginal flow of manufacturing and services occupies an absolute advantage in China’s industrial convergence network, in which mid-end manufacturing and producer services are the most prominent. (3) Industrial convergence between provinces has formed a hierarchical spatial layout of “output-conduction-absorption”. In the absorption layer, the breadth and depth of Beijing’s industrial integration are characterized by absorption-dominant development. In the output layer, Shanghai’s capital-intensive industries have a strong external radiation capacity and generally show open-led development. (4) Interregional industrial convergence tends to occur in areas with similar economic levels and output value levels, showing a coordinated development trend of high-level output and low-level absorption, which is also affected by location proximity relationships, regional technology gaps, and employment population gaps. This research shows that China’s inter-provincial industrial convergence network generally shows the characteristics of spatial hierarchy, significant industry differences and multi-factor drivers.