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
大规模农业人口向城镇及第二、三产业转移,引起其他农业生产要素改变,最终影响耕地利用效率。本文以江西省11个地级市为研究区域,运用超效率EBM(Epsilon Based Measure)模型测度2007-2016年江西省各地市耕地利用效率,通过面板门槛模型...大规模农业人口向城镇及第二、三产业转移,引起其他农业生产要素改变,最终影响耕地利用效率。本文以江西省11个地级市为研究区域,运用超效率EBM(Epsilon Based Measure)模型测度2007-2016年江西省各地市耕地利用效率,通过面板门槛模型以农业转移人口占农业人口比重为门槛变量,分析农业人口转移对耕地利用效率的影响。研究表明:考察期内江西省各地市农业转移人口与耕地利用效率均呈上升趋势,且区域差异显著;2016年江西省大多数地市农业人口转移对耕地利用效率的影响表现出门槛效应,在门槛值(0.428)前后,农业人口转移始终促进耕地利用效率提升,但跨越门槛值后其影响系数减小,由0.5089降至0.2495,促进作用减弱51%。可按农业人口转移程度是否跨越门槛值进行分区,针对不同区域提出差异化的耕地利用效率提升对策。展开更多
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.
文摘大规模农业人口向城镇及第二、三产业转移,引起其他农业生产要素改变,最终影响耕地利用效率。本文以江西省11个地级市为研究区域,运用超效率EBM(Epsilon Based Measure)模型测度2007-2016年江西省各地市耕地利用效率,通过面板门槛模型以农业转移人口占农业人口比重为门槛变量,分析农业人口转移对耕地利用效率的影响。研究表明:考察期内江西省各地市农业转移人口与耕地利用效率均呈上升趋势,且区域差异显著;2016年江西省大多数地市农业人口转移对耕地利用效率的影响表现出门槛效应,在门槛值(0.428)前后,农业人口转移始终促进耕地利用效率提升,但跨越门槛值后其影响系数减小,由0.5089降至0.2495,促进作用减弱51%。可按农业人口转移程度是否跨越门槛值进行分区,针对不同区域提出差异化的耕地利用效率提升对策。
