Evolution of structural properties of the global strategic emerging industries' trade network and its determinants: An TERGM analysis

Abstract

This article examines the evolution of the global strategic emerging industries trade networks (GSEITNs) and employs the temporal exponential random graph model (TERGM) to investigate the principal determinants of the critical trade cooperation in the global strategic emerging industries (SEIs) from 2007 to 2020. The findings indicate that GSEITNs exhibit a sparse, hierarchical, and monopolistic structure. Despite the continual integration of emerging nations into GSEITNs, countries have grown progressively wary of the network. Moreover, the structure properties of the endogenous network proves that SEIs trade links have a substantial signaling effect. More importantly, SEIs trade is more reliant on the economic size and innovation capacity, and countries are more cautious about protecting their intellectual property, especially when trading with countries possessing similar R&D levels. Furthermore, robust bilateral political ties can augment the probability of SEIs trade between two countries, particularly in sectors such as new energy vehicles and new-generation information technology industries. In summary, this article takes into account the influence of network structure, national attributes and external networks, and provides new insights into studying trade network evolution in SEIs.