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Research on the Measurement and Path of Urban Agglomeration Growth Effect

Author

Listed:
  • Jing Han

    (School of Economics and Resource Management, Beijing Normal University, Beijing 100875, China)

  • Ming Gao

    (School of Economics and Resource Management, Beijing Normal University, Beijing 100875, China)

  • Yawen Sun

    (School of Economics and Resource Management, Beijing Normal University, Beijing 100875, China)

Abstract

This paper employed dynamic generalized method of moment methods to measure the growth effect of 202 prefecture-level cities covered by 14 national urban agglomerations in China from 2007 to 2016. Based on this, this paper further explored the main factors affecting the growth of urban agglomeration and the path to achieving sustainable growth from the aspects of system, technology, structure, and influencing factors, and used the dynamic panel data (DPD) model and threshold panel data to empirically test the growth effect of urban agglomerations. The empirical results showed the following. (1) From the perspective of influencing factors, the improvement of technology and the increase in technology expenditure had a good growth effect on urban agglomeration, and this growth effect became more and more significant as the economic development level within the urban agglomeration narrowed; moreover, the increase of the agglomeration degree could alleviate the negative externality caused by the expansion of the urban scale and produce the dispersion effect to relieve the pressure of urban agglomeration. (2) From the results of the growth effect of urban agglomerations, the growth effect of multi-core urban agglomerations was more significant than that of single-core and dual-core urban agglomerations, and technology, agglomeration degree, foreign direct investment and human capital all significantly promoted the growth of urban agglomerations. Compared with trans-provincial urban agglomerations, provincial urban agglomerations have less resistance due to administrative jurisdiction, and the growth effect was obvious. (3) From the perspective of regional differences, the growth momentum of urban agglomerations in the eastern region was significantly stronger than that in the central and western regions, and the growth effect of agglomeration degree, technology, and human capital on urban agglomeration were all stronger than that in the central and western regions. Considering that the spatial distance between the edge cities and the central cities of the urban agglomeration will have an important impact on the overall growth of the urban agglomeration, this paper then used the panel threshold method to deeply discuss the influence mechanism and path dependence of the agglomeration degree on the growth of urban agglomerations. The results showed that within a certain spatial scale, a higher agglomeration degree of an urban agglomeration creates a stronger radiation effect of the core city and more obvious growth momentum of the urban agglomeration. In the future development of urban agglomerations, it is necessary to clarify the functions of the core city, vigorously develop new technologies, strengthen the construction of the core city as well as maximize its radiation and driving effect on the surrounding cities. Meanwhile, the government should improve transportation, increase the construction of urban expressways and railways, strengthen the connection between cities, strengthen regional integration and cooperation, and give play to the role of human capital in promoting growth to achieve the stable and continuous growth of urban agglomerations.

Suggested Citation

  • Jing Han & Ming Gao & Yawen Sun, 2019. "Research on the Measurement and Path of Urban Agglomeration Growth Effect," Sustainability, MDPI, vol. 11(19), pages 1-19, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5179-:d:269391
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    References listed on IDEAS

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    1. Peirong Chen & Ruhe Xie & Mingxuan Lu, 2020. "“Resource Conservation” or “Environmental Friendliness”: How do Urban Clusters Affect Total-Factor Ecological Performance in China?," IJERPH, MDPI, vol. 17(12), pages 1-28, June.
    2. Nelunika Priyashani & Nayomi Kankanamge & Tan Yigitcanlar, 2023. "Multisource Open Geospatial Big Data Fusion: Application of the Method to Demarcate Urban Agglomeration Footprints," Land, MDPI, vol. 12(2), pages 1-23, February.

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