Dynamic relationships among the energy structure, industrial structure, economic efficiency, and carbon emission efficiency in China: A panel vector autoregressive (PVAR) analysis

As the world’s largest emitter of greenhouse gases, China announced its “dual carbon goals” in September 2020. Achieving these goals and advancing high-quality economic development require the coordinated advancement of energy structure optimization, industrial structure upgrading, economic efficiency improvement, and carbon emission efficiency enhancement. On the basis of panel data from 30 Chinese provinces (including municipalities and autonomous regions) from 2010 to 2023, this study first evaluates economic efficiency and carbon emission efficiency via a nonparametric production frontier approach. It then employs a panel vector autoregression (PVAR) model to examine the dynamic relationships among these four indicators—industrial structure upgrading, energy structure optimization, economic efficiency, and carbon emission efficiency—at both the national and regional levels. The findings reveal that: (Ⅰ) At the national level, the four indicators have not yet established a long-term dynamic coupling relationship, indicating that synergies among these development factors in China’s green transition remain insufficient; (Ⅱ) significant regional heterogeneity exists. The central region shows preliminary mutual influences among the variables, although the strength and stability of these interactions require further enhancement. In contrast, the eastern region demonstrates short-term economic inertia, where economic efficiency and industrial structure upgrading have not formed a virtuous cycle. The western region lacks an endogenous driving mechanism for effective coordination between industrial and economic efficiency.