经济学院知识库

作为一个农业大国，现代农业建设的持续推进使我国农业经济得到了迅猛发展，但也产生了大量的碳排放，目前我国农业发展与保护环境之间的矛盾仍然存在。此外我国各区域的农业资源禀赋、生产特点等方面存在着很大的差距，区域经济发展不平衡问题明显，不利于我国农业经济的协调发展。所以从依赖要素投入的粗放型农业经济增长模式向以绿色全要素生产率为驱动的增长模式转换是我国实现农业绿色协调发展、建设农业强国的重要关键点。

基于此，本文以狭义农业为研究对象，利用SBM—GML模型对我国的农业绿色全要素生产率进行测算，其次运用Dagum基尼系数法测度我国的区域差异，并进一步探索差异的来源，利用s收敛和空间β收敛模型从时间和空间两个视角下研究农业绿色全要素生产率的收敛性特征，最后建立空间杜宾模型探究影响我国农业绿色全要素生产率的主要因素及其效应。

研究发现：（1）在研究期内我国农业绿色全要素生产率的平均值为1.046，可以分为“波动上升—轻微下降—稳步上升”三个阶段，除了西藏小于1之外其他省份都大于1，但高于全国整体水平的省份只有9个。东部地区的年均农业绿色全要素生产率为1.037，技术进步是决定其发展的关键因素。中部地区的年均农业绿色全要素生产率为1.048，前期主要由农业技术进步驱动，后面由农业技术效率驱动。西部地区的年均农业绿色全要素生产率为1.044，主要依靠农业技术进步驱动，农业技术效率只在研究早期起正向驱动作用。东北地区的年均农业绿色全要素生产率为1.04，整体呈现着“平稳-下降-上升”的变化趋势。（2）我国农业绿色全要素生产率的总体基尼系数呈现波动的先下降后上升变化趋势，中部地区的区内差异最大，东部和东北地区次之，西部地区最小。东北和东部地区之间的平均差异程度最大，中部和西部地区的差异程度最小。区间差异是造成我国农业绿色发展不平衡的主要原因，区内差异是造成总体差异的第二来源，超变密度的贡献率最小。我国不存在s收敛，各地区存在着明显的区域差异并且差异呈现扩大趋势。全国和各区域都存在β收敛特征，不同区域的收敛速度不同。（3）经济发展水平、城镇化水平、农业财政支出和农业技术水平对我国的农业绿色全要素生产率有正向推动作用，而对外依存度起抑制作用。经济发展水平、农业财政支出对农业绿色全要素生产率增长具有显著的直接效应，城镇化水平有显著的间接效应，对外依存度和农业技术水平的直接、间接效应都显著。在对不同区域的分析时发现各影响因素对农业绿色全要素生产率增长有着明显的空间异质性。

本文根据研究结论得出以下对策建议：（1）积极鼓励农业技术创新，提升技术效率水平。（2）破解要素流动障碍，加强区域间的交流合作。（3）建立绿色导向财政支出体系，引导农民绿色生产。（4）因地制宜，统筹规划区域农业发展。

As a major agricultural country, China has made rapid progress in modern agricultural construction. However, this progress has also resulted in a large amount of carbon emissions. Currently, the contradiction between China's agricultural development and environmental protection still exists. Therefore, it is crucial for China to shift from a growth model that relies on factor inputs to one driven by GTFP in order to achieve sustainable development of its agriculture and build itself into a strong agricultural nation. In addition, China has a vast territory with significant differences in agricultural production resources and characteristics among different regions. This regional imbalance in agricultural economic development is not conducive to coordinated development of China's agriculture.

Based on above, this paper takes narrow agriculture as the research object, uses SBM-GML model to measure China's agricultural GTFP, and then uses Dagum Gini coefficient to measure China's regional differences, and further discusses the sources of regional differences. The σ convergence and spatial β convergence models were used to study the convergence characteristics of agricultural GTFP from the perspectives of time and space. Finally, the spatial Durbin model was established to explore the main factors affecting agricultural GTFP in China and their effects.

The findings are as follows: (1) During the study period, the average value of agricultural GTFP in China was 1.046, which could be divided into three stages of "fluctuating rise - slight decline - steady rise". Except Tibet, the average value of agricultural GTFP was less than 1 in all other provinces, but only 9 provinces were higher than the overall level of the country. The average annual agricultural GTFP in eastern China is 1.037, and technological progress is the key factor to determine agricultural GTFP. The average annual agricultural GTFP in the central region is 1.048, which is mainly driven by the progress of agricultural technology in the early stage and the efficiency of agricultural technology in the later stage. The average annual agricultural GTFP in western China was 1.044, which was mainly driven by agricultural technology progress, while agricultural technology efficiency only played a positive driving role in the early stage of the study. The average annual agricultural GTFP in Northeast China is 1.04, showing a trend of "stable - declining - rising". (2) The overall Gini coefficient of agricultural GTFP in China showed a fluctuating trend of first decreasing and then increasing, and the regional difference was the largest in the central region, followed by the eastern region and the northeast region, and the western region was the least. The average difference degree between eastern region and Northeast region is the largest, and the interval difference level between central region and western region is the smallest. The regional difference is the main cause of the imbalance of agricultural green development in China, the regional difference is the second source of the overall difference, and the contribution rate of supervariable density is the least. There is no σ convergence in our country. There are obvious regional differences in various regions and the differences present a larger trend. There are obvious β convergence characteristics in the whole country and the four regions, and the convergence speed is different in different regions. (3) By analyzing the results of the spatial Durbin model, it is found that economic development level, urbanization level, agricultural financial expenditure and agricultural technology level have a positive promoting effect on China's agricultural GTFP, while the external dependence degree has an inhibitory effect. The level of economic development and agricultural fiscal expenditure have significant direct effects on the growth of agricultural GTFP, the level of urbanization has significant indirect effects, and the degree of external dependence and the level of agricultural technology have significant direct and indirect effects. In the analysis of different regions, it is found that the influencing factors have obvious spatial heterogeneity on the growth of agricultural GTFP.

Based on the research conclusions, this paper proposes the following countermeasures and suggestions: (1) Actively encourage technological innovation in agriculture and improve technical efficiency levels. (2) Break down barriers to factor flow and strengthen exchanges and cooperation among regions. (3) Establish a green-oriented fiscal expenditure system to guide farmers in producing in an environmentally friendly manner. (4) Plan regional agricultural development according to local conditions and make overall plans accordingly.