Research on the structural evolution and influence mechanism of the global green trade network based on exponential random graph model

Abstract With the global spread of environmental protection, green trade has become a new trend in trade development. Based on the total import and export value of green products from 227 countries (regions) from 2012 to 2020, this study uses a complex network analysis method to construct a global green trade network, study the structural characteristics and evolution of the network from three dimensions–whole, community, and node–and analyze the influence mechanism of the global green trade network using an exponential random graph model. The estimation results of the exponential random graph model show that the economic size gap, population size gap, development level, trade liberalization and language differences between countries will affect the formation of the global green trade network. The global green trade network has strong mutuality, and it is easier for countries with large differences in economic scale, countries with the same WTO member and developed countries to establish green trade relations. The common language network has a positive impact on the global green trade network. Countries should be clear about their own characteristics and position in the global green trade network, and actively develop green trade.