Research on the spatiotemporal differentiation, dynamic evolution, and impacts of agricultural energy efficiency in China under the constraint of the “dual carbon” target

Agricultural energy is the bedrock of agricultural production, and efficient energy utilization significantly bolsters the quality and productivity of agricultural outputs. However, agricultural energy consumption also plays a substantial role in carbon emissions. Hence, enhancing agricultural energy efficiency has emerged as a pivotal pathway toward achieving the "dual carbon" goals. This study utilises the super-efficiency SBM model and the Malmquist index model for non-expected output to assess and decompose agricultural energy efficiency in China from 2005 to 2021. The Theil index and spatial autocorrelation are employed to examine agricultural energy efficiency spatiotemporal differentiation. Concurrently, the Tobit model is utilized to analyze the principal determinants affecting agricultural energy efficiency. The research findings suggest that: (1) Agricultural energy efficiency in China exhibits an evolutionary pattern characterized by fluctuating declines, alongside the potential for enhancement. The disparity between the eastern and western regions is increasingly expanding, evolving from a state characterized by "high in the east and low in the west" to one defined as "high in the east and low in the middle". The intra-regional disparity is recognized as a significant factor that contributes to overall gaps, with the western region acting as a source of these intra-regional disparities. Agricultural energy efficiency demonstrates the presence of local "high-high" and "low-low" clusters; however, a spatial correlation is not evident. The degree of concentration in rural industry, per capita GDP, farmers' disposable income, the level of agricultural mechanization, and urbanization positively influence agricultural energy efficiency levels; conversely, financial support for agriculture has a notable inhibitory effect. In light of these findings, it is recommended that policies be developed to modify energy frameworks, improve technological competencies, increase agglomeration in the agricultural sector, and adopt regionalisation approaches.