地理学报 ›› 2021, Vol. 76 ›› Issue (4): 1019-1033.doi: 10.11821/dlxb202104016

• 地缘关系与区域发展 • 上一篇    下一篇

中国工业结对集聚和空间关联性分析

张可云1,2(), 朱春筱1   

  1. 1.中国人民大学应用经济学院,北京 100872
    2.中国人民大学书报资料中心,北京 100872
  • 收稿日期:2020-02-23 修回日期:2020-12-08 出版日期:2021-04-25 发布日期:2021-06-25
  • 作者简介:张可云(1964-), 男, 湖南临湘人, 教授, 博导, 主要从事区域经济政策、区域经济关系与行政区划等研究。E-mail: zkeyun@ruc.edu.cn
  • 基金资助:
    国家社会科学基金青年项目(19CJY002)

Coagglomeration and spatial relatedness of China's industry

ZHANG Keyun1,2(), ZHU Chunxiao1   

  1. 1. School of Applied Economics, Renmin University of China, Beijing 100872, China
    2. Information Center for Social Sciences, Renmin University of China, Beijing 100872, China
  • Received:2020-02-23 Revised:2020-12-08 Published:2021-04-25 Online:2021-06-25
  • Supported by:
    National Social Science Foundation of China(19CJY002)

摘要:

要推动形成优势互补高质量发展的区域经济布局,就需要从产业关联视角考察中国工业的空间格局。集聚是工业在空间的重要表现形式,通过把测度两两配对产业集聚的结对集聚指数和测度两两配对产业关联度的投入产出表相结合,首次构建集聚关联指数和关联集聚指数,以研究不同空间尺度下空间关联性的差异和出现差异的原因。通过整理中国工业企业数据库中的二位数行业数据发现,一个区域出现结对集聚的配对产业数多不意味着该区域的集聚关联度大。2003—2013年中国工业的集聚关联度先增加后下降;比较不同空间尺度发现,集聚关联度与研究空间大小正相关,与基本单元大小负相关;比较相近空间尺度发现,城市群和长江经济带内产业在区县和城市层次的集聚关联度较大。这种空间关联性的差异主要源于现有区域治理体系、区域内的产业构成和外部冲击,受区域与产业政策影响,不同的区域和产业将会演化出不同的产业空间格局。现阶段应继续以城市群和长江经济带为引领,补足城市间产业同构、空间关联性差的短板,增强产业在城市间的分工与合作,实现产业在空间的优化布局,推动区域协调发展。

关键词: 结对集聚, EG指数, 产业关联, 空间尺度, 区域经济布局

Abstract:

In order to promote the formation of a regional economic location with complementary advantages and high-quality development, it is necessary to examine the spatial pattern of Chinese industry from the perspective of industrial relatedness. Agglomeration is a common spatial pattern of industry. We construct two indices by combining coagglomeration and input-output linkages to analyze spatial relatedness. The first index is used to measure relatedness of agglomerated industries (hereafter ACX index). The second index is used to measure agglomeration of related industries (hereafter CXI index). Then, we use two-digit data from Chinese industrial enterprises database and measure the proposed indices to answer the following 2 questions: (1) whether the spatial relatedness is different at different spatial scales, and (2) what makes the difference in spatial relatedness. We find that more coagglomerations in a region do not mean that the ACX index is large. The ACX index of Chinese industry presents an inverted U-shaped distribution from 2003 to 2013. Comparing different spatial scales, we find that there is a positive correlation between the ACX index and size of the researched space, however, there is a negative correlation between ACX index and size of the basic unit. Comparing similar spatial scales, we find the ACX index is larger in city clusters and the Yangtze Economic Belt. These differences are mainly due to the existing regional governance system, the industrial composition of the region and external shocks. Different regions and industrial composition will evolve into different industrial spatial patterns. Therefore, it is necessary to create networks of cities and towns based on city clusters and the Yangtze River Economic Belt, so as to enhance industrial division and urban cooperation. In this way, the optimal regional economic location and coordinated regional development would be achieved.

Key words: coagglomeration, EG index, industrial relatedness, spatial scale, regional economic location