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The Dynamic Evolution of the Structure of an Urban Housing Investment Niche Network and Its Underlying Mechanisms: A Case Study of 35 Large and Medium-Sized Cities in China

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  • Linyan Wang

    (School of Economics and Management, Xi’an University of Technology, Xi’an 710054, China)

  • Haiqing Hu

    (School of Economics and Management, Xi’an University of Technology, Xi’an 710054, China)

  • Xianzhu Wang

    (School of Business, Anhui University of Technology, Ma’anshan 243002, China)

Abstract

With the growth of urban agglomerations, the spatial diffusion of housing investment is clear; however, little research has been carried out to address its network characteristics and underlying mechanisms of influence. Using data on 35 large and medium-sized cities, this paper applies niche theory to housing investment, constructing a housing investment niche index that includes resources, the housing market, the social economy, and policy. The purpose is to study the characteristics of the network structure and its mechanisms of influence based on an improved gravity model and a temporal exponential random graph model (TERGM). Supported by the analysis of the network structure, we find that the node degree within the network is low, the network density exhibits an inverted “V” shape, and the network level suggests the existence of a “rich cities club”. According to the local network clustering analysis, the cities are divided into three clusters: the Yangtze River Delta region, the Beijing–Tianjin–Hebei region, and the central and eastern regions. Furthermore, analysis of the endogeneity in the structure reveals that there is a hierarchy of cities with high economic development levels, which makes it difficult to establish an investment network with strong relationships. The effects of the attributes are consistent with the predictions of location theory and new economic geography theory. The external network effects conform to the law of the general gravity model. Our research provides insights into the ways in which the misplaced competition in housing investment between cities in a region and the flow of production factors can be reasonably guided.

Suggested Citation

  • Linyan Wang & Haiqing Hu & Xianzhu Wang, 2022. "The Dynamic Evolution of the Structure of an Urban Housing Investment Niche Network and Its Underlying Mechanisms: A Case Study of 35 Large and Medium-Sized Cities in China," Sustainability, MDPI, vol. 14(6), pages 1-21, March.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3523-:d:773180
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    References listed on IDEAS

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    1. Hillebrand, Marten & Kikuchi, Tomoo, 2015. "A mechanism for booms and busts in housing prices," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 204-217.
    2. Desmarais, B.A. & Cranmer, S.J., 2012. "Statistical mechanics of networks: Estimation and uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1865-1876.
    3. Evert Meijers & Martijn Burger & Roberto Camagni & Roberta Capello & Andrea Caragliu, 2016. "Static vs. dynamic agglomeration economies. Spatial context and structural evolution behind urban growth," Papers in Regional Science, Wiley Blackwell, vol. 95(1), pages 133-158, March.
    4. Stefano Battiston & Joao F. Rodrigues & Hamza Zeytinoglu, 2007. "The Network Of Inter-Regional Direct Investment Stocks Across Europe," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 29-51.
    5. Hongjie Bao & Ling Shan & Yufei Wang & Yuehua Jiang & Cheonjae Lee & Xufeng Cui, 2021. "How Does Local Real Estate Investment Influence Neighborhood PM 2.5 Concentrations? A Spatial Econometric Analysis," Land, MDPI, vol. 10(5), pages 1-21, May.
    6. Joshua Aizenman & Yothin Jinjarak & Huanhuan Zheng, 2019. "Housing Bubbles, Economic Growth, and Institutions," Open Economies Review, Springer, vol. 30(4), pages 655-674, September.
    7. Evert Meijers & Martijn Burger & Edward L. Glaeser & Giacomo A. M. Ponzetto & Yimei Zou, 2016. "Urban networks: Connecting markets, people, and ideas," Papers in Regional Science, Wiley Blackwell, vol. 95(1), pages 17-59, March.
    8. Peter Byrne & Stephen Lee, 2010. "Spatial concentration in industrial real estate," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 28(1), pages 6-23, February.
    9. Leifeld, Philip & Cranmer, Skyler J., 2019. "A theoretical and empirical comparison of the temporal exponential random graph model and the stochastic actor-oriented model," Network Science, Cambridge University Press, vol. 7(1), pages 20-51, March.
    10. Evert Meijers & Martijn Burger & Evert J. Meijers & Martijn J. Burger & Marloes M. Hoogerbrugge, 2016. "Borrowing size in networks of cities: City size, network connectivity and metropolitan functions in Europe," Papers in Regional Science, Wiley Blackwell, vol. 95(1), pages 181-198, March.
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    Cited by:

    1. Xuhong Zhang & Haiqing Hu & Cheng Zhou, 2023. "Spatiotemporal Evolution and Cause Analysis of Innovation Ecosystem Niche Fitness: A Case Study of the Yellow River Basin," Sustainability, MDPI, vol. 15(12), pages 1-16, June.

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