地理学报

地理学报 ›› 2011, Vol. 66 ›› Issue (8): 1011-1022.doi: 10.11821/xb201108001

• 城市研究 •    下一篇

中国城市群投入产出效率的综合测度与空间分异

方创琳1, 关兴良1,2   

  1. 1. 中国科学院地理科学与资源研究所, 北京 100101;
    2. 中国科学院研究生院, 北京 100049
  • 收稿日期:2010-03-25 修回日期:2010-12-20 出版日期:2011-08-20 发布日期:2011-08-20
  • 作者简介:方创琳(1966-), 男, 博士, 研究员, 博士生导师, 中国地理学会会员(S110001715M), 近年来主要从事城市发展与城市规划等研究。E-mail: fangcl@igsnrr.ac.cn
  • 基金资助:

    国家自然科学基金项目(40971101); 中国科学院知识创新工程重要方向性项目(KZCX2-YW-321-05); 国家“ 十一五”科技支撑计划重大项目课题(2006BAJ14B03; 2006BAJ05A06)

Comprehensive Measurement and Spatial Distinction of Input-output Efficiency of Urban Agglomerations in China

FANG Chuanglin1, GUAN Xingliang1,2   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2010-03-25 Revised:2010-12-20 Online:2011-08-20 Published:2011-08-20
  • Supported by:

    National Natural Science Foundation of China, No.40971101; National Key Technology R&D Program during the 11th Five-year Plan Period, No.2006BAJ14B03, No.2006BAJ14B03; Key Knowledge Innovation Project of the CAS, No. KZCX2-YW-321-05

PDF (PC)

赞

被引次数

330

摘要： 中国城市群是中国未来经济发展格局中最具活力和潜力的核心地区,是中国主体功能区划中的重点开发区和优化开发区,在全国生产力布局格局中起着战略支撑点、增长极点和核心节点的作用。但城市群高密度的聚集导致高强度的相互作用,在拉动城市群高速度成长的同时,造成了高风险的生态环境威胁。如何客观评价城市群高密度集聚的效果?基于这一问题,本文从投入产出效率视角,构建城市群投入产出效率指标体系,采用CRS 模型、VRS 模型和Bootstrap-DEA 方法,综合测算了中国城市群投入产出效率、变化趋势及空间分异特征。结果表明,中国城市群投入产出效率总体较低且呈下降趋势,2002 年、2007 年中国城市群投入产出综合效率为0.853 和0.820,分别达到最优水平的85%和82%,平均综合效率下降了0.033；基于Bootstrap-DEA 纠偏后的中国城市群投入产出效率更低,但更可靠有效；城市群投入产出综合效率、纯技术效率和规模效率总体表现为东部高于中部,中部高于西部的区域空间格局,呈现出与中国东、中、西区域经济发展格局相似的特征；2002-2007 年中国城市群规模效率指数微弱上升,全要素生产率指数、综合效率指数、技术效率变化指数以及纯技术效率指数下降趋势显著。该研究旨在为评估我国城市群高密度集聚的效果提供定量的测算依据,进而为提高中国城市群的投入产出效率与空间集聚效率奠定科学的决策基础。

关键词: 城市群, 投入产出效率, 纯技术效率, 规模效率, Bootstrap-DEA模型, 中国

Abstract: Urban agglomerations in China which perform a vital role in distribution of productive forces are the most dynamic and potential core area in future economic development, and are the key and optimized development districts in the division of main-function zones. However, while driving up rapid economic growth of urban agglomerations, high-intensity interaction caused by high-density aggregation also contributed to high-risk threats to natural environment. How do we assess the effect of high-density urban agglomerations? Accordingly, from the perspective of input and output efficiency, this paper established input and output efficiency indicator system of urban agglomerations, using CRS model, VRS model and Bootstrap-DEA, and measured the changing trend and spatial differentiation of input and output efficiency of urban agglomerations in China comprehensively. Results showed that input and output efficiency of urban agglomerations in China is low and slipping. In 2002 and 2007, comprehensive input and output efficiency of urban agglomerations in China was respectively 0.853 and 0.820, which dropped by an average of 0.033. Similarly, technical and scale efficiency of urban agglomerations in China is low and slipping; Input and output efficiency of urban agglomerations in China modified by Bootstrap-DEA model is lower but more reliable and effective. Input and output efficiency of urban agglomerations decreases gradually from the eastern region to the central and western regions of China. In 2002 and 2007, comprehensive input and output efficiency, technical efficiency and scale efficiency of urban agglomerations in eastern and central regions were higher than those in the western region, which was correlated with the regional economic development pattern in China. Otherwise, technical and production efficiency of urban agglomerations also decreases gradually from the eastern to the central and western regions. This study aims to provide a quantitative basis for assessing the effect of high-density urban agglomerations in China, and further lay a solid foundation for decision-making of improving input and output and spatial agglomeration efficiency of urban agglomerations in China.

Key words: urban agglomeration, input and output efficiency, technical efficiency, scale efficiency, Bootstrap-DEA model, China