Yun Tian

This paper summarizes the spatial–temporal characteristics of China’s rural energy carbon emission efficiency and then uses the Tobit model to explore its influencing factors. The results show that the rural energy carbon emission efficiency had experienced a growing trend in China during 2005 and 2020, with an annual growth rate of 4.82%. The growth is more affected by technological changes than by improvements in technical efficiency. Although all 30 provinces were in a state of improvement in rural energy carbon productivity during the period under review, there were significant differences between them. Technological change played a significant important role in promoting rural energy carbon productivity in the majority of Chinese provinces, while technical efficiency not only played a slightly less important role but also deteriorated in many provinces. Rural energy carbon emission efficiency is positively influenced by the level of agricultural development, the structure of rural labor force, and the urbanization level. However, it is negatively affected by the structure of cultivated land use, the rural human capital and rural residents’ consumption level. As such, policy formulation should support and promote the overall improvement of rural energy carbon emission efficiency.

By introducing network game theory, this paper analyzes the internal relationship and interaction mechanism among environmental governance, local government competition, and agricultural carbon peak level. On the basis of theoretical analysis, a spatial panel model is constructed using panel data from 30 provincial-level regions in China for empirical analysis. The research finds that local governments have positive competition with respect to the agricultural carbon peak, they adopt complementary carbon peak competition strategies, and they are more inclined to take geographical distance to adjacent regions as the yardstick in the competition with respect to the agricultural carbon peak strategy. That is, when the carbon peak level of surrounding provinces increases, the carbon peak level of the region will also increase. Thus, there is a phenomenon of mutual imitation and convergence between neighboring provinces. Environmental governance has a significant positive direct effect and a positive spatial spillover effect. From the perspective of coefficient, its direct effect is significantly greater than the spatial spillover effect. Therefore, more attention should be paid to local environmental governance to promote the improvement of the agricultural carbon peak level. Furthermore, the agricultural industrial structure, fiscal decentralization, agricultural public investment, regional industrial structure, and the proportion of the rural population have significant spatial spillover effects. The agricultural industrial structure and fiscal decentralization are significantly positively correlated with the peak level of agricultural carbon while the proportion of the rural population is significantly negatively correlated with the peak level of agricultural carbon. The research results have important theoretical value for expanding the research in the field of agricultural carbon emissions and provide important practical reference for China to successfully achieve the goal of agricultural carbon peak and promote the high-quality development of agriculture