经济学院知识库

农业是经济社会发展的支撑，建设农业强国，健全现代农业产业体系至关重要。数字经济作为经济高质量发展的新引擎，对建设现代农业作用重大。加快数字经济在农业领域的应用，加速推进农业现代化进程，推动农业向智能化、精准化、绿色化方向发展。在深入实施乡村振兴战略的进程中，产业兴旺被确立为核心发展目标，通过产业间的深度融合，着力构建现代农业产业体系，为乡村经济注入持续发展动力。当前，推动新质生产力赋能农业高质量发展，增加农业的附加值，依靠技术进步提升全要素生产率，是推进农业农村现代化的目标。随着长期以来化肥、薄膜等农业生产的投入，也给绿色生态发展带来了一系列思考。中国面临巨大绿色低碳转型压力，促进农业绿色高质量发展，提升农业产出效率，对生态环境保护、促进农民增收、保证粮食安全意义重大。

本研究构建产业集聚影响农业绿色全要素生产率的理论分析框架，基于2011-2022年中国省级面板数据，从地理集聚和虚拟集聚两个维度，实证检验其分别对农业绿色全要素生产率的影响作用。研究首先基于可持续发展理论、产业集聚理论和熊彼特创新理论构建理论框架。其次，研究采用熵权法分别测算地理集聚和虚拟集聚指数，应用SBM-GML模型测算农业绿色全要素生产率，对地理集聚、虚拟集聚和农业绿色全要素生产率的时空演变格局进行分析。再次，利用 研究期内的省级面板数据，探究产业集聚对农业绿色全要素生产率的直接影响效应，以及城乡收入差距对产业集聚和农业绿色全要素生产率的间接影响效应。最后，根据本文实证结果，提出具体的政策建议，以期为农业绿色可持续发展提供方向指引。

运用面板模型和门槛效应模型，对地理集聚、虚拟集聚分别对农业GTFP的直接影响效应和间接影响效应进行实证检验。研究发现：（1）核心解释变量为地理集聚的估计系数为0.374，核心解释变量为虚拟集聚的估计系数为0.121。（2）地理集聚和虚拟集聚对我国农业GTFP产生区域异质性作用。（3）当解释变量为地理集聚时，城乡收入差距在地理集聚对农业GTFP的影响中具有正向作用，城乡收入差距小于门槛值的系数为0.357，大于门槛值的系数为0.423。城乡收入差距大于门槛值的时候，正向作用更显著。当解释变量为虚拟集聚时，城乡收入差距在其中产生的间接影响为正向作用，城乡收入差距小于门槛值的系数为0.065，大于门槛值的系数为0.117。城乡收入差距大于门槛值的时候，正向作用更显著。据此，提出加快数字基础设施建设，形成特色产业集聚优势；优化产业集聚方式，促进农业绿色现代化发展；推动产业转型升级，助推农业新质生产力；提升农村居民收入，推进城乡共同富裕等政策建议。以期为促进我国农业绿色可持续发展提供一定的参考。

Agriculture is the foundation of economic and social development. Building a strong agricultural nation and improving the modern agricultural industrial system are of vital importance. The digital economy, as a new engine for high-quality economic development, plays a significant role in modernizing agriculture. Accelerating the application of digital economy in the agricultural sector and promoting the modernization process of agriculture will drive it towards intelligence, precision, and green development. In the process of deeply implementing the rural revitalization strategy, industrial prosperity has been established as the core development goal. Through the deep integration of industries, efforts are made to build a modern agricultural industrial system, injecting continuous development momentum into the rural economy. Currently, promoting new productivity to empower high-quality agricultural development, increasing the added value of agriculture, and enhancing total factor productivity through technological progress are the goals of advancing the modernization of agriculture and rural areas. However, the long-term input of fertilizers, films, and other agricultural production materials has also brought a series of considerations for green and ecological development. China is under great pressure for green and low-carbon transformation. Promoting green and high-quality agricultural development and improving agricultural output efficiency are of great significance for ecological and environmental protection, increasing farmers' income, and ensuring food security.

This study constructs a theoretical analysis framework of the impact of industrial agglomeration on agricultural green total factor productivity. Based on the provincial panel data of China from 2011 to 2022, it empirically examines the impact of geographical agglomeration and virtual agglomeration on agricultural green total factor productivity from two dimensions. The study first builds a theoretical framework based on sustainable development theory, industrial agglomeration theory, and Schumpeter's innovation theory. Secondly, it uses the entropy weight method to calculate the geographical agglomeration and virtual agglomeration indices, and applies the SBM-GML model to calculate agricultural green total factor productivity. It analyzes the spatio-temporal evolution patterns of geographical agglomeration, virtual agglomeration, and agricultural green total factor productivity. Thirdly, it uses the provincial panel data during the research period to explore the direct impact of industrial agglomeration on agricultural green total factor productivity and the indirect impact of the urban-rural income gap on industrial agglomeration and agricultural green total factor productivity. Finally, based on the empirical results of this study, specific policy recommendations are proposed to provide direction for the green and sustainable development of agriculture.

Using panel models and threshold effect models, the direct and indirect impact effects of geographical agglomeration and virtual agglomeration on agricultural GTFP are empirically tested. The study finds that: (1) The estimated coefficient of the core explanatory variable of geographical agglomeration is 0.374, and the estimated coefficient of the core explanatory variable of virtual agglomeration is 0.121. (2) Geographical agglomeration and virtual agglomeration have regional heterogeneous effects on China's agricultural GTFP. (3) When the explanatory variable is geographical agglomeration, the urban-rural income gap has a positive effect on the impact of geographical agglomeration on agricultural GTFP. The coefficient is 0.357 when the urban-rural income gap is less than the threshold value, and 0.423 when it is greater than the threshold value. When the urban-rural income gap is greater than the threshold value, the positive effect is more significant. When the explanatory variable is virtual agglomeration, the indirect impact of the urban-rural income gap is positive. The coefficient is 0.065 when the urban-rural income gap is less than the threshold value, and 0.117 when it is greater than the threshold value. When the urban-rural income gap is greater than the threshold value, the positive effect is more significant. Based on this, the following policy recommendations are proposed: accelerating the construction of digital infrastructure to form a competitive advantage of characteristic industrial agglomeration; optimizing the mode of industrial agglomeration to promote the green and modern development of agriculture; promoting industrial transformation and upgrading to boost new productivity in agriculture; and increasing rural residents' income to promote common prosperity in urban and rural areas. These recommendations aim to provide certain references for promoting the green and sustainable development of agriculture in China.