自然资源学报 ›› 2019, Vol. 34 ›› Issue (3): 573-585.doi: 10.31497/zrzyxb.20190311

• 资源经济 • 上一篇    下一篇

重庆市农业转型发展的时空演进及问题区识别——基于全要素生产率视角

尹朝静1,2(), 李兆亮3(), 李欠男4, 赵同琳1,2   

  1. 1. 西南大学农村经济与管理研究中心,重庆 400715
    2. 西南大学经济管理学院,重庆 400715
    3. 武汉工程大学法商学院,武汉 430205
    4. 华中农业大学经济管理学院,武汉 430070
  • 收稿日期:2018-09-26 修回日期:2019-01-10 出版日期:2019-03-28 发布日期:2019-03-28
  • 作者简介:

    作者简介:尹朝静(1989- ),男,四川内江人,博士,讲师,主要从事农业技术经济学和资源与环境经济学研究。E-mail: yinchaojing@163.com

  • 基金资助:
    教育部人文社会科学研究项目(18XJC790018);重庆市人文社科重点研究基地项目(18SKB033);国家自然科学基金青年项目(71803145)

Spatiotemporal evolvement and problem region diagnosis of agricultural transformation in Chongqing city: Based on a total factor productivity perspective

YIN Chao-jing1,2(), LI Zhao-liang3(), LI Qian-nan4, ZHAO Tong-lin1,2   

  1. 1. Research Centre of Rural Economics and Management, Southwest University, Chongqing 400715, China
    2. College of Economics & Management, Southwest University, Chongqing 400715, China
    3. School of Law and Business, Wuhan Institute of Technology, Wuhan 430205, China
    4. College of Economics & Management, Huazhong Agricultural University, Wuhan 430070, China
  • Received:2018-09-26 Revised:2019-01-10 Online:2019-03-28 Published:2019-03-28

摘要:

研究农业全要素生产率时空演进规律对于合理制定农业转型升级政策具有重要意义。在使用DEA-Malmquist指数模型测算出重庆市37个县(区)2000-2016年农业全要素生产率增长的基础上,结合空间分析方法和核密度估计方法考察农业TFP的时空演进特征,并识别出问题区域。研究表明:(1)2000-2016年间重庆市农业全要素生产率呈上升趋势,农业TFP指数呈“U”型和阶段性波动的变化趋势,并且表现出明显的空间不平衡性。(2)农业TFP指数增减趋势与技术进步指数的变化趋势基本一致,技术进步是影响农业全要素生产率的主要因素。(3)从全市来看,农业TFP的核密度曲线不断向右移动,且波峰高度持续上升,波峰形态由“单峰”分布向“多峰”分布转变,说明重庆市农业全要素生产率的地区差距在考察期内呈增大趋势。(4)依据TFP增长、技术进步和技术效率的关联关系,识别出三种类型的问题区域,并针对每类问题区域提出农业转型发展的政策建议。

关键词: 农业TFP, 时空演进, 核密度估计, 问题区域

Abstract:

Studying the law of spatiotemporal evolution of agricultural total factor productivity is of great significance to formulate the agricultural transformation and upgrading policies rationally. This paper, which is based on the calculation of agricultural total factor productivity growth from 37 counties in Chongqing over the period 2000-2016 by using DEA-Malmquist index model, investigates characteristics of spatiotemporal evolution of agricultural total factor productivity by using spatial analysis and Kernel density estimation methods and identifies the problem regions of Chongqing. The results are listed as follows: (1) From 2000 to 2016, the agricultural total factor productivity is on the rise. The agricultural total factor productivity index has a tendency of "U" type and periodic fluctuation, which shows obvious spatial imbalance. (2) The change trend of agricultural total factor productivity index is similarly consistent with that of technical progress index, which indicates that the technology progress is the main reason for total factor productivity growth. (3) From the view of the whole city, the Kernel density curve of agricultural total factor productivity keeps moving to the right, and the crest height continues to rise. The crest shape changes from "unimodal" to "multi-modal" distribution, which implies that the regional disparity of agricultural total factor productivity shows an increasing trend during the study period. (4) According to the relationship among agricultural total factor productivity growth, technical progress and technical efficiency, three types of problem regions are identified. Then policy suggestions for agricultural transformation and development are proposed for each type of problem region.

Key words: agricultural total factor productivity, spatiotemporal evolution, Kernel density estimation, problem region