江西省农业绿色全要素生产率时空演化

Temporal and spatial evolution of agricultural green total factorproductivity in Jiangxi Province

考虑碳排放约束,将农业碳排放作为非期望产出,运用全局Malmquist-Luenberger指数模型对江西省2011—2020年11个设区市的农业绿色全要素生产率进行测算,分析其时空演化格局,并探析可能的驱动来源。结果表明,江西省2011—2016年的农业绿色全要素生产率较为稳定,在经历2017年的低谷后,2018—2020年连年创下新高;不同区域的农业绿色全要素生产率指数存在明显差异,其中鹰潭市最高,其次是南昌市、九江市;而抚州市最低;2018年起农业绿色全要素生产率的变化主要由技术进步推动,且规模效率对技术效率的贡献逐渐降低。未来应因地制宜优化农业产业结构,农业技术人才、资本投入、水资源和土地利用等资源要素的配置,通过农业科技创新推动农业绿色低碳发展。

Considering the carbon emission constraint,taking agricultural carbon emission as the undesired output,Global Malmquist-Luenberger index model was used to measure the agricultural green total factor productivity(AGTFP)in 11 cities in Jiangxi Province from^(2)011 to 2020.Then the temporal and spatial evolution pattern was analyzed,and also the possible driving sources were explored.The results showed that the AGTFP in Jiangxi province was stable from^(2)011 to 2016,while from^(2)018 to 2020,it reached new high points after experiencing the low point in 2017.There were obvious differences in different regions,Yingtan had the highest AGTFP,followed by Nanchang,Jiujiang,while Fuzhou has the lowest AGTFP.The change of AGTFP was mainly driven by technological progress from^(2)018,and the contribution of scale efficiency to technological efficiency was gradually reduced.In the future,it is of vital importance to optimize the agricultural industrial structure,the allocation of resource factors such as agricultural technical personnel,agricultural capital input,water resources and land use,and promote the green and low-carbon development of agriculture through agricultural technological innovation.