资源科学 ›› 2021, Vol. 43 ›› Issue (12): 2442-2450.doi: 10.18402/resci.2021.12.07

• “澜沧江—湄公河流域农业资源与环境”专栏 • 上一篇    下一篇

大湄公河次区域农业生产效率时空特征

屈秋实1,4(), 王礼茂2,3(), 王博2,3, 向宁2,3   

  1. 1.河北地质大学经济学院,石家庄 050031
    2.中国科学院地理科学与资源研究所,北京 100101
    3.中国科学院大学资源与环境学院,北京 100049
    4.河北地质大学自然资源资产资本研究中心,石家庄 050031
  • 收稿日期:2021-05-01 修回日期:2021-10-23 出版日期:2021-12-25 发布日期:2022-02-16
  • 通讯作者: 王礼茂,男,安徽巢湖人,研究员,主要从事能源经济与气候变化政策等方面的研究。E-mail: lmwang@igsnrr.ac.cn
  • 作者简介:屈秋实,女,黑龙江鹤岗人,讲师,主要从事资源经济与资源政策管理方面的研究。E-mail: quqs. 16b@igsnrr.ac.cn
  • 基金资助:
    国家自然科学基金项目(41971163);国家自然科学基金项目(41861028);澜沧江—湄公河合作专项;河北省高校基本科研业务费项目(QN202137)

Spatiotemporal characteristics of agricultural productivity in the Greater Mekong Subregion

QU Qiushi1,4(), WANG Limao2,3(), WANG Bo2,3, XIANG Ning2,3   

  1. 1. School of Economics, Hebei GEO University, Shijiazhuang 050031, China
    2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    3. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
    4. Institute of Natural Resources Asset Capital, Hebei GEO University, Shijiazhuang 050031, China
  • Received:2021-05-01 Revised:2021-10-23 Online:2021-12-25 Published:2022-02-16

摘要:

大湄公河次区域农业生产自然条件优越,但经济发展相对落后,农业生产对大湄公河次区域经济社会发展具有十分重要的作用。本文基于2000—2018年大湄公河次区域5国1省的面板数据,通过数据包络分析模型测算区域内农业生产效率,并从技术效率和规模效率两方面对其进行分解,分析大湄公河次区域农业生产效率的时空特征及其影响因素。研究发现:①2000—2018年大湄公河次区域农业生产综合效率呈现上升趋势,但效率水平整体较低。②农业生产综合效率空间分布整体呈现四周高、中间低特征,老挝一直是大湄公河次区域中农业生产效率最低的国家。③中国云南、越南、缅甸和泰国效率的提高主要依靠农业生产技术的拉动,农业生产技术对农业生产综合效率提升的贡献程度由初期的小于生产规模,逐渐转变为大于生产规模。④大湄公河次区域农业生产效率的时空特征是自然因素和生产要素综合影响的结果。气候水文因素是影响农业生产效率的最主要因素;随着农业生产技术的改进,地形地貌对农业生产效率的影响逐渐减弱;农业劳动力数量的增加对农业生产效率的提升作用有限;农业机械化水平与农业生产效率的时空格局呈显著正向关联。通过剖析大湄公河次区域农业生产效率时空特征及其影响因素,不仅揭示了大湄公河次区域农业生产状况,也可为区域内农业生产效率的提高提供建议。

关键词: 农业生产效率, 规模效率, 时空格局, 影响因素, 大湄公河次区域

Abstract:

The natural conditions of agricultural production in the Greater Mekong Subregion (GMS) are superior, but the economic development is relatively backward. Agricultural production plays a very important role in the economic and social development of the region. Based on the panel data of five countries and one province of China in the GMS from 2000 to 2018, this study estimated the regional agricultural production efficiency by using the data envelopment analysis model, and decomposed it into technical efficiency and scale efficiency to reveal the spatiotemporal characteristics of agricultural production efficiency in the region and its influencing factors. The study found that: (1) From 2000 to 2018, agricultural production efficiency in the GMS showed an upward trend, but the level of agricultural production efficiency was relatively low overall. (2) The spatial distribution of agricultural production efficiency is generally high in the periphery and low in the central areas. Laos has been the country with the lowest agricultural production efficiency in the region. (3) Yunnan Province of China, Vietnam, Myanmar, and Thailand have higher comprehensive efficiency of agricultural production, and the improvement of efficiency mainly depends on the pull of agricultural production technology. The contribution of agricultural production technology to the improvement of comprehensive efficiency of agricultural production gradually changed from less than the production scale in the initial stage to greater than the production scale. (4) The spatiotemporal characteristics of agricultural production efficiency in the GMS are the result of the comprehensive influence of natural factors and production factors. Climatic and hydrological factors are the most important factors affecting agricultural production efficiency. With the improvement of agricultural production technology, the effect of landform and topography on agricultural production efficiency is gradually weakened. The increase of the number of agricultural laborers has limited effect on the improvement of agricultural production efficiency. The spatiotemporal patterns of agricultural production efficiency are positively correlated with agricultural land use and agricultural mechanization level. By analyzing the spatial and temporal characteristics and influencing factors of agricultural production efficiency in the GMS, this study not only revealed the agricultural production status in the region, but also provided relevant recommendations for improving agricultural production efficiency in the GMS.

Key words: agricultural production efficiency, scale efficiency, spatiotemporal pattern, influencing factors, Greater Mekong Subregion