中国农业全要素生产率的空间关联网络结构及驱动因素研究

The spatial correlation network structure and the driving forces of China’s agricultural total factor productivity

提高农业全要素生产率是实现中国农业高质量发展的重要路径。本文建立了中国农业全要素生产率的空间关联网络模型,运用社会网络分析法从网络整体特征、局部特征和个体特征三个层面对网络结构进行了考察,并揭示了中国农业全要素生产率空间关联性的驱动因素。研究发现:1)中国农业全要素生产率具有十分明显的空间关联和溢出效应,其空间关联网络处于连通状态,样本考察期内网络密度呈现V型波动趋势,且等级森严的结构逐渐被打破,网络稳定性逐步增强。2)在中国农业全要素生产率空间关联网络中,西部地区属于净受益板块,华南和西南地区为"经纪人"板块,环渤海、京津冀和东北地区为双向溢出板块,华东和部分中南地区省市为净溢出板块。3)湖北、内蒙古、河南、山东和陕西在空间关联网络中处于绝对核心位置,对农业生产要素的支配作用较强;吉林、海南和青海等地区在网络中处于绝对边缘位置。4)地理邻接关系对农业全要素生产率空间关联性具有正向影响,农业结构差异和要素产出水平差异等因素具有负向影响。本文为从整体上把握和提升中国农业全要素生产率提供理论依据和参考。

Improving agricultural total factor productivity (TFP) is an important way to achieve high-quality agricultural development in China.This paper constructed a spatial association network model of China’s agricultural TFP to analyze the overall characteristics,local characteristics,and individual characteristics of the network and examined the driving forces of the special correlation network of China’s agricultural TFP.Results show that 1) there are a very obvious spatial correlation and spillover effects in China’s agricultural TFP.The spatial correlation network is in a connected state.The network density shows a V-shaped fluctuating trend.In addition,the hierarchical structure is gradually broken and the network stability is gradually enhanced;2) in the spatial network of China’s agricultural TFP,the western region belongs to the net beneficiary sector,the south and southwest regions belong to the "brokers sector",and the Bohai Rim,Beijing-Tianjin-Hebei,and northeast regions belong to the two-way spillover sector;3) five major provinces,including Hubei,Inner Mongolia,Henan,Shandong,and Shaanxi Province,are in the absolute core position in the spatial correlation network of China’s agricultural TFP,and they have stronger influences on the factors of agricultural production,while other provinces,including Jilin,Hainan,Qinghai,Tianjin,and Shanghai,are in an absolute marginal and passive position in the network;and 4) geographic adjacency has a positive effect on the spatial correlation of China’s agricultural TFP,and other factors such as differences in agricultural structure and differences in factor output levels have some negative effects.This paper provides a general theoretical basis and reference for understanding and improving China’s agricultural TFP.