基于空间效应视角的农业经济增长与种植业面源污染排放的实证分析  

Empirical analysis of agricultural economic growth and planting non-point source pollution emissions from the perspective of spatial effects

作　　者：李新[1] 尚杰[1] LI Xin;SHANG Jie(College of Economics and Management,Northeast Forestry University,Harbin 150040,China)

机构地区：[1]东北林业大学经济管理学院,哈尔滨150040

出　　处：《中国生态农业学报（中英文）》2022年第9期1531-1544,共14页Chinese Journal of Eco-Agriculture

基　　金：国家自然科学基金项目(71573036);国家社会科学基金项目(20FGLB059)资助。

摘　　要：农业资源环境是保障农业生产发展、实现农业经济增长的基本资源和条件。从空间效应视角探析农业经济增长与种植业面源污染物排放量的关系,可为推进种植业面源污染防治政策实施提供理论支撑。本文采用等标污染负荷法测度2000—2019年全国31个省、直辖市、自治区(不包含香港、澳门、台湾)种植业面源污染物氨氮、化学需氧量、总氮、总磷的排放情况,运用空间杜宾模型剖析农业经济增长、消费能力、技术进步、农业现代化水平、风险感知、财政支持、受灾情况及产业结构对种植业面源污染物排放的空间效应,并对影响因素的空间效应进行分解。结果表明:1)全国31个省、直辖市、自治区的种植业面源污染排放存在显著正向全局空间自相关性,2019年空间格局特征主要表现为“高-高”聚集和“低-低”聚集,聚集区域主要表现在农业大省和经济发达地区。2)种植业面源污染排放具有显著负向空间溢出效应,空间滞后系数为−0.11,农业经济增长对本地区及邻接地区有相斥方向的显著性影响效应。3)SDM时间固定效应模型效应分解结果表明,8个影响因素中农业经济增长、消费能力、技术进步、农业现代化水平和风险感知的直接效应和间接效应均具有显著性。农业经济增长具有缓解本地区种植业面源污染的作用,估计系数为−0.175,但对邻接地区种植业面源污染排放具有加重作用,估计系数为0.397。据此,提高对农业经济增长、技术进步和财政支持等显著性影响因素的导向作用的重视,地方政府可积极发挥自身优势,联动邻接地区发挥空间交互作用,开展农业新型技术培训,建立有效的种植业面源污染防治监督管理体制,实现农业经济增长与种植业面源污染防治平衡发展。Agricultural resources and environment are the basic resources and necessary conditions for the development of agricultural production and realization of agricultural economic growth.Analyzing the relationship between agricultural economic growth and planting non-point source pollution from the perspective of spatial effects can help to explore a new direction for prevention and control of planting non-point source pollution,and provide theoretical support for promoting the implementation of the policy of prevention and treatment of planting non-point source pollution.Based on the provincial panel data from 2000 to 2019,this study used the equal-standard pollution load method to measure the planting non-point source pollution emissions;and used the spatial Durbin model to empirically analyze the spatial effect of agricultural economic growth,consumption capacity,technological progress,agricultural modernization level,risk perception,financial support,disaster situation,and industrial structure on the emission of planting non-point source pollution,and to split the spatial effect of the influencing factors into direct and indirect spatial effects.The results are as follow:1)A significant positive global spatial autocorrelation among the planting non-point source pollution in 31 provinces(cities,autonomous regions)was noted.In 2019,the spatial pattern was characterized by“high-high”and“low-low”aggregations,and the agglomerations were mainly in large agricultural provinces and economically developed areas.2)The planting non-point source pollution had a significant negative spatial spillover effect,with a spatial lag coefficient of−0.11,and agricultural economic growth had a significant effect on the region and adjacent regions in a mutually exclusive direction.3)The results of the effect of decomposition showed that the direct and indirect effects of agricultural economic growth,consumption capacity,technological progress,agricultural modernization level,and risk perception were significant at 5%confidence

关 键 词：种植业面源污染 农业经济增长 等标污染负荷法 空间效应 空间杜宾模型 

分 类 号：F323.22[经济管理—产业经济] X712[环境科学与工程—环境工程]