统计与数据科学学院知识库

      2022年我国数字经济规模达50.2万亿元，占GDP的比重为41.5%，充分显示数字经济已成为我国经济增长的新引擎。其中，数字产业化规模与产业数字化规模分别为18.3%和81.7%，表明数字技术正深度融合到各行各业，推动传统产业数字化、智能化升级。然而，尽管我国数字经济发展势头强劲，但在农业领域，数字化水平仍然相对较低，是数字经济发展的短板。为此，党中央和国务院积极行动，通过实施大数据战略、数字乡村战略以及推进“互联网+”现代农业等举措，大力推动农业农村数字化转型。特别是2023年中央一号文件，明确提出要加快农业农村大数据应用，推进智慧农业发展，这进一步体现了国家对农业数字化转型的坚定决心。因此，抓住数字经济发展的有利时机，加快农业产业数字化转型，对于促进农业农村可持续发展至关重要。

        基于此，本文首先在整合国内外有关数字农业研究成果的基础上，梳理数字农业相关理论，归纳总结国内外发达地区数字农业发展经验；其次，从发展环境、基础设施等六个维度构建指标体系，利用熵值法测度2013-2021年甘肃省14个市州的数字农业发展水平，分析其时空分布特征；之后通过计算Dagum基尼系数量化数字农业发展水平的区域差异，理清区域分化根源；最后构建面板回归模型，识别制约甘肃省数字农业发展的关键因素，并提出针对性的政策建议。经过分析得出以下结论：

     （1）甘肃省各市州数字农业发展水平在不断提升，存在高-高集聚与低-低集聚现象，且河西地区数字农业发展水平处于全省领先位置；（2）数字农业发展水平区域总体差异呈波动中下降趋势；从区域内部差异来看，陇中地区区域内部差异略有扩大，其他三个地区区域内差异均减小；陇中—南部民族地区区域间差异有所增加且区域间差异是导致甘肃省数字农业发展不均衡的主要原因。（3）面板分位数回归的实证结果表明在数字农业发展的初期，农村集体经济发展水平与金融发展水平的提升会促进数字农业发展；中期，农村集体经济发展水平、乡村从业人员素质水平、金融发展水平等均起推动作用；后期，乡村从业人员素质水平、金融发展水平等是主要推动力。（4）从区域异质性来看，不同区域中各个影响因素对数字农业发展水平的影响各不相同。

       基于以上结论，从发展新型农村集体经济、发挥辐射带动、强化人才队伍建设、完善数字农业服务体系等方面提出了相应的政策建议。

  The scale of Chinese digital economy reached 50.2 trillion yuan in 2022,accounting for 41.5% of GDP,fully demonstrating that the digital economy has become a new engine of economic growth in China.Among them,the scale of digital industrialization and industrial digitization account for 18.3% and 81.7% respectively, indicating that digital technology is deeply integrating into various industries, promoting the digitalization and intelligent upgrading of traditional industries. However, despite the strong development momentum of Chinese digital economy, the level of digitalization in the agricultural sector is still relatively low, which is a shortcoming in the development of the digital economy. To this end, the CPC Central Committee and the State Council have taken active action to vigorously promote the digital transformation of agriculture and rural areas through the implementation of big data strategy, digital village strategy and the promotion of "Internet plus" modern agriculture and other measures. In particular, the No. 1 central document of the Central Committee in 2023 clearly proposed to accelerate the application of agricultural and rural big data and promote the development of smart agriculture, which further reflects the country's firm commitment to the digital transformation of agriculture. Therefore, seizing the favorable opportunity for the development of the digital economy and accelerating the digital transformation of the agricultural industry is crucial for promoting sustainable development of agriculture and rural areas.

   Based on this, this article first integrates the research results of digital agriculture at home and abroad, sorts out the relevant theories of digital agriculture, and summarizes the development experience of digital agriculture in developed regions at home and abroad; Secondly, an indicator system is constructed from six dimensions including development environment and infrastructure, and the entropy method is used to measure the development level of digital agriculture in 14 cities and prefectures in Gansu Province from 2013 to 2021, analyzing their spatiotemporal evolution patterns; Afterwards, by calculating the Dagum Gini coefficient, the regional differences in the development level of digital agriculture were clarified, and the root causes of regional differentiation were clarified; Finally, a panel regression model is constructed to identify the key factors that constrain the development of digital agriculture in Gansu Province, and targeted policy recommendations are proposed. The main conclusions are as follows:

   (1) The development level of digital agriculture in various cities and prefectures in Gansu Province is constantly improving, with high high and low agglomeration phenomena, and the development level of digital agriculture in Hexi region is at the forefront of the province; (2) The overall regional differences in digital agriculture show a fluctuating downward trend; From the perspective of regional differences, the differences within the Longzhong region have slightly expanded, while the differences within the other three regions have decreased; The regional differences between the ethnic regions in central and southern Gansu have increased, and these differences are the main reason for the uneven development of digital agriculture in Gansu Province. (3) The empirical results of panel quantile regression indicate that in the early stages of digital agriculture development, the development of rural collective economy and finance will significantly promote the development of digital agriculture; In the mid-term, rural collective economy, human capital, and financial development all play a driving role; In the later stage, human capital and financial development are the main driving forces. (4) From the perspective of regional heterogeneity, the impact of various influencing factors on digital agriculture varies in different regions.

  Based on the above conclusions, corresponding policy recommendations have been put forward from the aspects of developing newrural collective economy, leveraging radiation to drive, strengtheningtalent team construction, and improving the digital agriculture servi-ces system.