地理科学 ›› 2018, Vol. 38 ›› Issue (12): 1970-1978.doi: 10.13249/j.cnki.sgs.2018.12.004

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中国省际工业生态效率空间分布及影响因素研究

李成宇1(), 张士强1,2, 张伟2   

  1. 1.山东科技大学经济管理学院,山东 青岛266590
    2.济南大学绿色发展研究院,山东 济南250022
  • 收稿日期:2017-11-28 修回日期:2018-01-29 出版日期:2018-12-20 发布日期:2018-12-20
  • 作者简介:

    作者简介:李成宇(1990-),男,山东青州人,博士研究生,主要从事能源经济研究。E-mail:lig@nwu.edu.cn

  • 基金资助:
    国家社科重大项目(15ZDB163)、教育部人文社会科学研究规划基金项目(15YJAZH110)资助

Spatial Distribution Characteristics and Influencing Factors of China's Inter Provincial Industrial Eco-efficiency

Chengyu Li1(), Shiqiang Zhang1,2, Wei Zhang2   

  1. 1.College of Economics and Management,Shandong University of Science and Technology, Qingdao 266590, Shandong, China
    2. Institute of Green Development, University of Jinan,Jinan 250022, Shandong,China
  • Received:2017-11-28 Revised:2018-01-29 Online:2018-12-20 Published:2018-12-20
  • Supported by:
    Major Program of National Social Science Foundation of China (15ZDB163), Funding Project of Education Ministry for the Development of Liberal Arts and Social Sciences (15YJAZH110).

摘要:

将中国30省市(不含港、澳、台和西藏地区)作为研究对象,进行省际工业生态效率空间分布及影响因素研究。首先构建中国省际工业生态效率评价指标体系,其次利用DEA-BCC模型结合Malmquist指数对2006~2015年中国30省市在时空两个维度上的工业生态效率进行测算,再次运用Geoda软件分析中国工业生态效率的空间分布特征,最后通过空间误差模型对中国工业生态效率的影响因素进行检验。研究结果表明: 中国工业生态效率虽呈现小幅度下降趋势,但整体效率水平较高;30省市之间存在明显差异性,呈现出东部>中部>西部的分布格局。 中国工业生态效率Malmquist指数增长率水平较高;30省市Malmquist指数均为正向增长,呈现出稳定增长趋势;技术进步效率是Malmquist指数的主要推动力。中国30省市工业生态效率呈现正向空间自相关性,且存在明显的集聚状态,近邻效应显著。 中国省际工业生态效率的主要影响因素有经济发展水平、产业结构、政府规制、技术进步、外商投资和产业集聚。

关键词: 工业生态效率, BCC模型, Malmquist指数

Abstract:

Taking 30 provinces and cities of China as research objects, the spatial distribution and influencing factors of inter provincial industrial eco-efficiency are studied. The article sets up the evaluation index system of Chinese provincial industrial eco-efficiency. Combined with the Malmquist index model, the DEA-BCC model is used to measure the industrial eco-efficiency spatio-temporally in 2006-2015. And Goda software is used to analyze the spatial distribution characteristics of industrial ecological efficiency. Finally, the influencing factors of China's industrial eco-efficiency is examed through the spatial error model. The results show that: 1) China's industrial eco-efficiency, although showing a slight downward trend, but the overall high level of efficiency; there are obvious differences between the 30 provinces, showing a distribution pattern of the eastern> Central> West. 2) China's industrial eco-efficiency Malmquist index higher growth rates; Malmquist index of 30 provinces and cities are positive growth, showing a steady growth trend; improve efficiency technology is the main driving force Malmquist Index. 3) China 30 provinces and industrial eco-efficiency presents a positive spatial autocorrelation, and there is a significant gathering state, the neighbor effect is significant. 4) The level of economic development, industrial structure, government regulations, technological progress, foreign investment, and industrial agglomeration are the main factors affecting the eco-efficiency of the provinces.

Key words: industrial ecological efficiency, BCC model, Malmquist index

中图分类号: 

  • F205