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江苏省农业绿色化转型的驱动性要素分析
引用本文:郭承龙,张杰.江苏省农业绿色化转型的驱动性要素分析[J].中国农机化学报,2022,43(11):224.
作者姓名:郭承龙  张杰
作者单位:南京林业大学经济管理学院,南京市,210037
基金项目:2022年江苏省高等学校大学生创新创业训练计划项目(202210298029Z);2021年江苏省社科应用研究精品工程课题(21SYB—004);2020年江苏高校哲学社会科学一般研究项目(2020SJA0156)
摘    要:驱动性要素是农业绿色化转型政策的实施载体。以生产资料投入、现代生产方式、环境友好和绿色经济效益为维度,设计17个二级指标构建江苏省农业绿色化转型评价体系。测量指标采取耦合方法得到相应的维度变量值。回归计算结果表明:生产资料投入、现代生产方式和环境友好对农业绿色经济效益的标准化回归系数依次为0.959、0.803和0396,对绿色经济效益的驱动效应依次下降。使用农村人均可支配收入和农村人均居住面积作为替代变量,计算结果证实生产资料投入、现代生产方式和环境友好对绿色经济效益的驱动效应是稳健的。因此,应坚持从农业化肥、农药的减量化行动入手,细化农业现代化生产方式的具体举措等,推进江苏省农业绿色化深度发展与转型。


Analysis on driving factors on agricultural green transformation in Jiangsu Province
Abstract:Driving factors are the implementation carrier of agricultural green transformation policy. Evaluation system of agricultural green transformation in Jiangsu Province was constructed by 17 secondary indexes from the dimension of agricultural means of production, modern production modes, environmental friendliness and green economic benefits. The corresponding variable values were obtained by the coupling method for the indexes under each dimension. The results of regression showed that the standardized regression coefficients of agricultural means of production, modern production modes and environmental friendliness towards green economic benefits were 0.959, 0.803 and 0.396, respectively. The driving effect on green economic benefits declined in turn. The calculation results confirmed that the regression model was robust by per capita rural disposable income and per capita rural living as the surrogate variables. The driving effects of agricultural means of production, modern production modes and environmental friendliness towards green economic benefits were reliable. Therefore, it should persist on the reduction of agricultural fertilizers and pesticides, refine the specific measures of modern agricultural production modes, and further promote the green development and transformation of agriculture.
Keywords:green agriculture  transformation  robustness  coupling  agricultural means of production  driving effects  
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