农业新质生产力发展水平时空演化及障碍因素研究

Spatial and temporal evolution of the development of new quality productivity of agricultural and obstacles to further development

  • 摘要: 新质生产力有望成为未来中国经济发展的新引擎, 培育农业农村领域的新质生产力, 不仅事关农村经济增长, 也是推进农业现代化进程的重要抓手。因此尝试构建农业新质生产力的评价指标体系, 采用2012—2022年中国30个省、自治区、直辖市(不包括中国香港、澳门、台湾和西藏)的面板数据, 使用纵横向拉开档次、Kernel密度估计、传统及空间Markov链、Dagum基尼系数测算分解和障碍度模型等方法对农业新质生产力发展水平、时空分异特征、区域差异以及障碍因子等进行测度和识别。研究发现: 考察期内农业新质生产力发展水平呈平稳上升趋势; 东中西部地区之间及粮食主产区和非粮食主产区之间发展水平表现出明显差异。从各维度来看, 农业绿色生产力及数字生产力发展状况较好, 且研究期内数字生产力表现出强劲的增长势头。各省份的发展水平存在空间溢出效应, 会对邻近省份发展产生正向或负向的影响。东中西部区域间差异逐渐成为农业新质生产力发展的主要差异来源。准则层方面的科技生产力和融合生产力、指标层方面的农村数字基地数量和一、三产业融合程度成为农业新质生产力发展的主要障碍因素。

     

    Abstract: New quality productivity is predicted to become a new engine for driving China’s future economic development, consequently, cultivating new quality productivity in agricultural and rural areas will not only contribute to the growth of the rural economy but also play an important role in promoting the process of agricultural modernization. In this study, we developed an evaluation index system of new quality productivity in agriculture using panel based on data obtained for 30 provinces (cities, autonomous regions) in China (excluding Xizang, Hong Kong, Macao, and Taiwan) from 2012 to 2022. Using longitudinal and transversal pulling grades, kernel density estimates, traditional and spatial Markov chain models, Dagum Gini coefficient measurement decomposition, and an obstacle degree model, we analyzed the levels of new quality productivity development in agriculture and found that these could be measured and identified using the following methods: the characteristics of spatial and temporal differentiation, regional differences, and obstacle factors. We found that the levels of new agricultural quality productivity development showed a steady upward trend during the examination period, and detected notable differences in the levels of development among the eastern, central, and western regions, and between the main grain-producing regions and the non-grain-producing regions. In terms of dimensions, green and digital productivity in agriculture were found to be in a more advanced state of development, and digital productivity showed strong growth during the study period. The level of development in each province was established to have certain spatial spillover effects, which had either a positive or negative influence on the development of neighboring provinces. The difference among the east, center, and west regions gradually emerged as the main sources of differences in the development of new agricultural quality productivity. Similarly, the criterion level of the differences among regions in the east, center and west have gradually emerged as the main sources of differences in the development of new quality agricultural productivity, scientific and technological productivity, and integration productivity in the criterion layer, whereas the number of rural digital bases and the degree of integration of primary and tertiary industries in the indicator layer were currently the main obstacles to the further development of new quality agricultural productivity.

     

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