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城镇化模式与农业绿色全要素生产率：基于空间门限面板模型
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Abstract:
“双碳”目标背景下，厘清不同城镇化模式与农业绿色全要素生产率之间的协同关系，对实现农业降污增效具有重要意义。本文基于卫星监测夜间灯光数据构建的复合灯光指数衡量城镇化水平，采用Super-SBM方向函数测算的GML指数评估2000~2022年间中国31个省份的农业绿色全要素生产率，并利用空间门限面板模型实证检验了城镇化水平对农业绿色全要素生产率的非线性门限关系、不同城镇化模式的差异性影响以及农业绿色全要素生产率的路径依赖性。研究结果表明，随着农业产业集聚水平的提高：(1) 城镇化水平与农业绿色全要素生产率之间呈现“先降–后升–再降”的非线性关系。(2) 城镇化深度模式对农业绿色全要素生产率的影响具有三区制门限特征，表现为“先降–后升–再降”的波动趋势，城镇化广度模式则呈现“先降–后升”的双区制门限效应。(3) 在城镇化综合水平、城镇化深度模式与农业绿色技术进步之间，均存在“先降–后升–再降”的非线性关系；在产业较高集聚水平下，二者对农业技术效率的影响由负向正转变；相比之下，城镇化广度模式对两条技术路径的依赖性较低。本文基于上述研究结果所提出的政策建议，对推动农业绿色循环发展和实现“双碳”目标具有重要的参考价值。
In the context of the “dual carbon” goals, clarifying the synergistic relationship between different urbanization models and agricultural green total factor productivity (GTFP) is crucial for achieving agricultural pollution reduction and efficiency improvement. This study constructs an urbanization index based on satellite-monitored nighttime light data and evaluates the GTFP of 31 provinces in China from 2000 to 2022 using the Super-SBM directional function. A spatial threshold panel model is employed to empirically test the nonlinear threshold relationship between urbanization levels and GTFP, the differential effects of different urbanization models, and the path dependence of GTFP. The results show that as the level of agricultural industrial agglomeration increases: (1) There is a nonlinear relationship between urbanization levels and GTFP that follows a pattern of “decline-rise-decline”. (2) The deep urbanization model has a three-threshold characteristic on GTFP, showing a fluctuating trend of “decline-rise-decline”, while the extensive urbanization model exhibits a two-threshold effect with “decline-rise”. (3) A nonlinear relationship of “decline-rise-decline” exists between the comprehensive urbanization level, the deep urbanization model, and agricultural green technological progress; under high industrial agglomeration levels, the effect of both shifts from negative to positive on agricultural technical efficiency. In contrast, the extensive urbanization model shows lower dependency on both technical paths. The policy recommendations derived from these findings have significant reference value for promoting agricultural green circular development and achieving the “dual carbon” goals.
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