运用含非期望产出的超效率SBM(slack based measure)模型和GML(global Malmquist-Luenberger)指数,对中国与世界主要国家1991—2016年的分别在考虑和不考虑环境约束下的技术效率和全要素生产率进行测度与比较。研究发现,不考虑环境约束...运用含非期望产出的超效率SBM(slack based measure)模型和GML(global Malmquist-Luenberger)指数,对中国与世界主要国家1991—2016年的分别在考虑和不考虑环境约束下的技术效率和全要素生产率进行测度与比较。研究发现,不考虑环境约束的测度结果忽略了一国发展所造成的污染损失,导致技术效率与生产率被高估;中国的技术效率在考虑环境因素后显著下降,总效率排名从样本中的第16位下降至第40位。时间趋势上,中国的环境效率与技术效率的差距呈现先扩大后缩小,且近年来有逐渐趋同的态势;动态视角上,不考虑环境约束时中国的全要素生产率变化总体呈现增长趋势,但在考虑环境因素后中国的环境全要素生产率转变为下降趋势,这其中,技术进步的下降是影响环境全要素生产率变化的主要因素。展开更多
As a traditional agricultural country,China has always prioritized agricultural development,and has increasingly focused on green and sustainable agricultural development.Based on the inter-provincial panel data for C...As a traditional agricultural country,China has always prioritized agricultural development,and has increasingly focused on green and sustainable agricultural development.Based on the inter-provincial panel data for China from 1997 to 2019,this study divided these data into five periods according to the Five-Year Plan(FYP)of China,measured the agricultural eco-efficiency(AEE)values using the Super-SBM model,and then determined the spatial association network of the inter-provincial AEE of China using the improved gravity model.Finally,social network analysis(SNA)was used to further analyze the evolution process of AEE,and we de-veloped a framework of how multidimensional proximity,which includes geographical,economic,technological,cognitive,and institutional proximity,made an influence on the formation of AEE spatial relation network.The findings indicated that:1)in 1997−2019,the AEE in China was present in some spatial and temporal differences characteristics at the provincial scale,and we specifically found that national macro-regulation and policy incentives played a positive role in the long-term development of AEE.2)The spatial correlation of AEE development among provincial regions were becoming closer and exhibits obvious spatial correlation and spillover effects.The evolution of the AEE network has clearly observable trends of hierarchization and aggregation,and the complexity of the correlation network continues to increase and exhibits spatial clustering characteristics that are dense in the east and sparse in the west.The network structure has changed from monocentric radiation to a multicentric network,and network nodes select the more advantageous nodes with which to connect.3)Finally,the geographical proximity had a significant negative effect;the economic,technological,and institutional proximities were all observed to contribute to the AEE network formation,and cognitive proximity did not significantly influence this network formation.展开更多
文摘运用含非期望产出的超效率SBM(slack based measure)模型和GML(global Malmquist-Luenberger)指数,对中国与世界主要国家1991—2016年的分别在考虑和不考虑环境约束下的技术效率和全要素生产率进行测度与比较。研究发现,不考虑环境约束的测度结果忽略了一国发展所造成的污染损失,导致技术效率与生产率被高估;中国的技术效率在考虑环境因素后显著下降,总效率排名从样本中的第16位下降至第40位。时间趋势上,中国的环境效率与技术效率的差距呈现先扩大后缩小,且近年来有逐渐趋同的态势;动态视角上,不考虑环境约束时中国的全要素生产率变化总体呈现增长趋势,但在考虑环境因素后中国的环境全要素生产率转变为下降趋势,这其中,技术进步的下降是影响环境全要素生产率变化的主要因素。
基金Under the auspices of National Key R&D Program of China(No.2018YFD 1100104)Natural Science Foundation of Anhui Province(No.2108085-MD29)National Natural Science Foundation of China(No.41571400)。
文摘As a traditional agricultural country,China has always prioritized agricultural development,and has increasingly focused on green and sustainable agricultural development.Based on the inter-provincial panel data for China from 1997 to 2019,this study divided these data into five periods according to the Five-Year Plan(FYP)of China,measured the agricultural eco-efficiency(AEE)values using the Super-SBM model,and then determined the spatial association network of the inter-provincial AEE of China using the improved gravity model.Finally,social network analysis(SNA)was used to further analyze the evolution process of AEE,and we de-veloped a framework of how multidimensional proximity,which includes geographical,economic,technological,cognitive,and institutional proximity,made an influence on the formation of AEE spatial relation network.The findings indicated that:1)in 1997−2019,the AEE in China was present in some spatial and temporal differences characteristics at the provincial scale,and we specifically found that national macro-regulation and policy incentives played a positive role in the long-term development of AEE.2)The spatial correlation of AEE development among provincial regions were becoming closer and exhibits obvious spatial correlation and spillover effects.The evolution of the AEE network has clearly observable trends of hierarchization and aggregation,and the complexity of the correlation network continues to increase and exhibits spatial clustering characteristics that are dense in the east and sparse in the west.The network structure has changed from monocentric radiation to a multicentric network,and network nodes select the more advantageous nodes with which to connect.3)Finally,the geographical proximity had a significant negative effect;the economic,technological,and institutional proximities were all observed to contribute to the AEE network formation,and cognitive proximity did not significantly influence this network formation.
