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基于产业结构视角的县域农业增长空间特征研究
引用本文:刘玉,唐秀美,潘瑜春,胡月明.基于产业结构视角的县域农业增长空间特征研究[J].自然资源学报,2018,33(2):246-261.
作者姓名:刘玉  唐秀美  潘瑜春  胡月明
作者单位:1. 北京农业信息技术研究中心,北京 100097; 2. 国家农业信息化工程技术研究中心,北京 100097; 3. 华南农业大学信息学院,广州 510642
基金项目:北京市社会科学基金项目(15JGC167);北京市农林科学院科技创新能力建设专项(KJCX20170503,KJCX20170501)。
摘    要:基于产业结构视角,系统揭示区域农林牧渔业增长的空间特征,有助于制定科学的农业发展策略。研究借助Esteban-Marquillas拓展模型将县域农业增长分解为份额分量、产业结构分量、净竞争分量和资源配置分量,并借助ESDA方法系统分析2000—2014年京津冀地区县域农林牧渔业增长的空间特征。结果表明:1)2000—2014年,京津冀地区农林牧渔业总体呈现增长态势,且种植业和牧业是农业增长的主要产业。2)京津冀地区县域农业增长具有显著的同质集聚性,集聚效应表现为渔业>牧业>林业>种植业。就产业各分量而言,份额分量和结构分量的集聚效应最强,表现为渔业>牧业>林业>种植业;净竞争分量和资源配置分量仅有种植业和牧业的集聚效应通过统计性检验,并以种植业最强;各分量的显著高高(或低低)集聚县域表现出低重合度,京津冀地区县域农业生产格局尚待优化。3)农业资源配置流向相对合理的Ⅰ类型(竞争优势+专业化程度强)和Ⅳ类型(竞争劣势+专业化程度低)的县域数量不足50%(渔业除外),表明县域农业资源配置的比较优势不突出,县域间分工协作意识不强。建议加强县域间的经济联系和产业合作,提升资源配置效率,加快实现农业结构升级和布局优化。

关 键 词:Esteban-Marquillas拓展模型  京津冀地区  农业增长  偏离份额法  县域  
收稿时间:2016-12-28
修稿时间:2017-03-16

Spatial Features of Agricultural Growth by County from the Perspective of Industrial Structure
LIU Yu,TANG Xiu-mei,PAN Yu-chun,HU Yue-ming.Spatial Features of Agricultural Growth by County from the Perspective of Industrial Structure[J].Journal of Natural Resources,2018,33(2):246-261.
Authors:LIU Yu  TANG Xiu-mei  PAN Yu-chun  HU Yue-ming
Institution:1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China; 2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; 3. School of Information, South China Agriculture University, Guangzhou 510642, China
Abstract:A systematic revelation of the spatial features of growth in regional farming, forestry, animal husbandry and fishery from the perspective of industrial structure is conducive to the formulation of scientific agricultural development strategy. Based on the Esteban-Marquillas model, the study divides the agricultural growth into the weights of share, industrial structure, net competition and resource allocation. With the ESDA approach, the study carries out a systematic analysis on the spatial features of the growth in farming, forestry, animal husbandry and fishery at county level in Beijing-Tianjin-Hebei region from 2000 to 2014. The results are as follows: 1) From 2000 to 2014, the farming, forestry, animal husbandry and fishery in Beijing-Tianjin-Hebei region showed a growing trend with farming and animal husbandry being the major growing industries. 2) The agricultural growth at county level in Beijing-Tianjin-Hebei region shows obvious agglomerations, and the order of agglomeration degree in different industries from high to low is fishery, animal husbandry, forestry and farming. In terms of the four kinds of weights, the weights of share and industrial structure have the strongest agglomeration effect, and their agglomeration effect in different industries from high to low is fishery, animal husbandry, forestry and farming. The weights of net competition and resource allocation have agglomeration effects only in farming and animal husbandry, and their agglomeration effects in framing are the strongest. The high-high (or low-low) agglomerations of the four weights have low overlap, that is to say, the industrial pattern at county level in Beijing-Tianjin-Heibe need to be optimized. 3) The counties of Type Ⅰ (competitive advantages and high level of specialization) and Type Ⅳ (competitive disadvantages and low level of specialization) which have relatively reasonable agricultural resource allocation account for less than 50% (except for fishery). This shows that the comparative advantages of agricultural resource allocation at county level are not obvious and it lacks of coordination and division of responsibilities among counties. For the purpose of coordinated development of agriculture, a top-level design is needed to strengthen economic exchanges and industrial cooperation among counties. It is suggested to develop and implement differentiated agricultural development strategy and guide the flow of resources in case of excessive competition, and resource allocation efficiency should be improved to accelerate the agricultural structure and layout optimization.
Keywords:agricultural growth  Shift Share Method  Esteban-Marquillas extended model  county region  Beijing-Tianjin-Hebei region  
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