【摘要】 基于非期望产出的超效率SBM模型与GML指数，测度了2011—2023年中国省域农业碳排放效率的时空格局与驱动机制。结果表明，超效率SBM静态效率呈现显著区域分异，西藏、新疆等生态优势地区效率最优，甘肃、安徽等地因资源约束或农资过度投入导致效率偏低；GML指数动态效率反映出技术活跃地区以技术进步为主要驱动，部分禀赋优势地区出现技术效率回落，暴露技术落地在部分地区受到多方面制约；2012年、2016年、2020年、2023年全国全要素生产率空间分布结果显示，部分地区受自然环境与产业结构调整未能适应农业技术更新迭代影响，导致农业碳排放效率变动幅度显著；分位数回归结果表明，劳动力结构滞后制约高碳排放效率地区发展，农业机械化在中高农业碳排放效率地区面临高耗能瓶颈，土地流转率对碳排放效率影响呈多维度抑制，而复种指数在高分位点处具有显著促进作用。更多还原

【Abstract】 Based on the undesirable-output super-efficiency SBM model and the GML index,the spatiotemporal patterns and driving mechanisms of agricultural carbon emission efficiency across Chinese provinces from 2011 to 2023 were measured. The results showed that the static efficiency measured by the super-efficiency SBM model exhibited significant regional differentiation:Regions with ecological advantages,such as Tibet and Xinjiang,achieved the highest efficiency,while Gansu and Anhui showed relatively low efficiency due to resource constraints or excessive agricultural input;the dynamic efficiency reflected by the GML index indicated that technologically active regions were primarily driven by technological progress,whereas some resource-rich regions experienced a decline in technical efficiency,revealing multifaceted constraints on technology implementation;spatial distributions of total factor productivity in 2012,2016,2020,and 2023 further demonstrated significant fluctuations in agricultural carbon emission efficiency in certain regions,resulting from their failure to adapt to technological upgrades under natural environment and industrial restructuring;quantile regression results indicated that the lagging labor structure hindered the development of high-efficiency regions,agricultural mechanization faced high-energy-consumption bottlenecks in medium-efficiency and high-efficiency regions,land transfer rate exerted multidimensional inhibitory effects on carbon emission efficiency,whereas the multiple cropping index played a significantly positive role at high quantiles.更多还原