数字经济对粮食生态效率的影响研究基于13个粮食主产区面板数据的实证检验

Study on the impact of digital economy on grain eco-efficiency: Empirical test based on panel data of 13 major grain-producing areas

  • 摘要: 有效缓解资源环境约束对粮食生产的威胁, 全面提升粮食生态效率水平, 是新形势下不断筑牢我国粮食安全“堡垒”的必然选择。本文基于2013—2021年中国13个粮食主产区的面板数据, 运用基准回归、中介效应和门槛效应等模型, 从多维度分析了数字经济对粮食生态效率的影响机制。研究结果表明: 数字经济对粮食生态效率具有显著的正向影响, 在一系列稳健性检验后结论仍然成立; 异质性分析表明, 数字产业化对粮食生态效率的促进作用更为显著, 且在北方地区和低粮食生态效率地区数字经济对粮食生态效率的促进作用更加明显; 中介效应表明, 数字经济通过提高农地经营规模和农业社会化服务, 间接推动粮食生态效率提升; 门槛检验结果表明, 数字经济对粮食生态效率的促进作用受到财政支农力度的影响, 且呈现边际效应递增的非线性特征。因此, 未来应完善农村新型数字基础设施建设, 提高农地经营规模和农业社会化服务水平, 优化财政支农结构, 突出绿色政策的发展导向, 因地制宜制定数字经济与粮食生态效率的协同推进策略, 以促进粮食生态效率的持续提升。

     

    Abstract: Effectively alleviating the threat of resource and environmental constraints on grain production and improving grain eco-efficiency are inevitable choices to continuously build the “fortress” of China’s grain security. As a new economic form accompanying the changes in information technology, the digital economy can promote high-quality development of the grain industry both directly and indirectly. Based on the panel data of 13 major grain-producing areas from 2013 to 2021, this study constructed digital economy indicators from the two dimensions: digital industrialization and industrial digitalization. The development level of the digital economy and grain eco-efficiency was measured using the entropy weight method. The impact mechanism of the digital economy on grain eco-efficiency was analyzed in multiple dimensions using baseline regression, intermediary effect, and threshold effect models, which were of great significance for clarifying the correlation between them. The results indicated that the overall grain eco-efficiency of the 13 major grain-producing areas showed an increasing trend from 2013 to 2021, divided into three stages: rapid decline, rapid increase, and slow increase. Moreover, there were clear spatial differences in grain eco-efficiency, indicating that the growth rate of grain eco-efficiency in the northern region was higher than that in the southern region. The digital economy had a significant positive impact on grain eco-efficiency, and this conclusion remained valid after a series of robustness tests, such as adjusting sample intervals, eliminating outlier estimates, and lagging explanatory variables. Heterogeneity analysis revealed that digital industrialization had a more significant promoting effect on grain eco-efficiency than industrial digitalization, and that the digital economy had a more significant promoting effect on grain eco-efficiency in the northern regions and regions with low grain eco-efficiency. The intermediary effect analysis showed that the scale of agricultural land management and agricultural socialization services significantly promoted grain eco-efficiency. This indicates that the digital economy can indirectly improve grain eco-efficiency by expanding the scale of agricultural land management and improving agricultural socialization services. The threshold test results suggested that the promoting effect of digital economy on grain eco-efficiency was influenced by the intensity of fiscal support for agriculture and presented a nonlinear feature of increasing marginal effects; that is, the higher the intensity of fiscal support for agriculture, the more the digital economy could improve grain eco-efficiency. To continuously improve grain eco-efficiency, it is necessary to enhance the construction of a new rural digital infrastructure, increase the scale of agricultrual land management and agricultural socialization, optimize the structure of fiscal support for agriculture, highlight the development orientation of green policies, and adopt a differentiated collaborative promotion strategy for the digital economy and grain eco-efficiency.

     

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