| 摘要: |
| ［目的］考虑空间因素的影响，分析农业全要素生产率增长的空间收敛性，以期为缩小中国农业发展的地区差距提供指导。［方法］运用DEA Malmquist指数方法对1978—2015年中国大陆28个省（市、区）农业全要素生产率进行测算。在此基础上，运用Moran′s I指数对农业全要素生产率的空间相关性进行检验，并使用空间误差模型探讨其收敛性。［结果］农业全要素生产率增长呈现较为明显的地区非均衡性特征； 根据农业全要素生产率增长差异将28个省（市、区）划分为“快速上升型”“平稳上升型”和“持续下降型”3种类型； 农业全要素生产率表现出“弱→强→弱”的空间相关性特征； 在考虑空间溢出效应的情况下，农业全要素生产率的空间收敛速度加快； 分阶段来看，市场经济制度正式确立之后，空间收敛速度明显降低； 从农业全要素生产率构成来看，技术进步与技术效率存在空间收敛趋势； 分地区来看，农业全要素生产率空间收敛速度呈现中部、西部、东部依次递减的格局。［结论］考虑空间因素的收敛性分析更能客观反映农业发展的地区差距，应充分重视地区间的空间效应，通过加大农业投资力度、提高农村人力资本水平等措施，逐步缩小农业发展的地区差距。 |
| 关键词: 农业全要素生产率地区差距空间收敛性Moran′s I指数空间误差模型 |
| DOI： |
| 分类号:F323 |
| 基金项目:国家自然科学基金“中国农业全要素生产率增长的微观基础及若干农业政策的生产率效应评估”（71873050）； 国家自然科学基金“劳动力成本上升对农业生产的影响机理与实证研究”（71473100）； 教育部人文社会科学研究项目“中国县域农业绿色全要素生产率测算、收敛及其影响因素研究”（18XJC790018）； 中央高校基本科研业务费专项资金项目“新型城镇化下成渝地区农业全要素生产率测算及提升机制研究”（SWU1909419）； 重庆市人文社科重点研究基地项目“资源环境紧约束下重庆农业全要素生产率时空演变与协同提升路径研究”（18SKB033） |
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| ANALYSIS OF REGIONAL GAP AND SPATITAL CONVERGENCE OF AGRICULTURAL TOTAL FACTOR PRODUCTIVITY GROWTH |
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Li Qiannan1,2, Li Guchengv1,2※, Gao Xue1,2, Yin Chaojing3
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1. Economics and Management College of Huazhong Agricultural University, Wuhan, Hubei 430070, China;2. Center for Hubei Rural Development, Wuhan, Hubei 430070, China;3. Economics and Management College of Xi′nan Agricultural University, Chongqing 400715, China
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| Abstract: |
| Considering the influence of spatial factors, the paper analyzes the spatial convergence of agricultural total factor productivity growth in order to provide guidance for narrowing the regional gap of agricultural development in China. The DEA Malmquist index method was used to measure the total factor productivity of 28 provinces (cities, districts) in mainland China from 1978 to 2015, then Moran′I index was adopted to test the spatial correlation of agricultural total factor productivity, and spatial error model was used to explore its convergence. Research results were showed as follows. Firstly, the growth of agricultural total factor productivity showed obvious regional non equilibrium feature, 28 provinces (cities, districts) were divided into three types including "rapid rise", "stable rise" and "continuous decline" according to the difference in agricultural total factor productivity growth, and agricultural total factor productivity showed the spatial correlation characteristics of "weak→strong→weak". Secondly, if spatial spillover effect was considered, the spatial convergence rate of agricultural total factor productivity accelerated. Thirdly, in stages, the spatial convergence speed significantly reduced after the formal establishment of market economy system. Fourthly, from the perspective of the composition of agricultural total factor productivity, technological progress and technical efficiency presented a spatial convergence trend. Finally, from the perspective of regions, the spatial convergence rate of agricultural total factor productivity showed a pattern of decreasing in the central, western and eastern regions. If spatial convergence factors are considered, it can more objectively reflect the regional gap of agricultural development. It should pay full attention to the spatial effects between regions, and gradually narrow the regional gap in agricultural development by increasing agricultural investment and improving rural human capital. |
| Key words: agricultural total factor productivity reginal gap spatial convergence Moran′s I index spatial error model |
