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High-Speed Railway Network, City Heterogeneity, and City Innovation

Author

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  • Kunlun Zhao

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

  • Wenxing Li

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)

Abstract

The emergence of the time–space contraction effect from the high-speed railway (HSR) network in China has been beneficial in breaking down regional divisions, thus facilitating the circulation of resources and optimizing resource distribution and production efficiency. However, research has not adequately addressed the city disparities of the HSR network and their effects on city innovation. Through the heterogeneity perspective of ‘New’ new economic geography, this study employs the 2008–2019 panel data at the city level in China and builds a spatial Durbin model based on continuous spatial difference in differences to investigate the mechanism of the HSR network on city innovation and to analyze its agglomeration and diffusion effect of innovative factors under different city sizes and spatial perspectives. This study revealed that the HSR network could significantly increase the innovation of local cities and neighboring cities, yet there is a certain threshold of city size that affects city innovation. Large cities covered by HSRs can take advantage of gathering talent, financial capital, and industry from nearby regions, thus constructing a new spatial pattern of innovative development. This study also found that the innovation accelerative effect gradually decreases as the distance from the city covered by HSRs increases and completely disappears at the distance of 400 km. Therefore, it is necessary to optimize the HSR network and increase the mobility and agglomeration of innovative elements between cities, thus deepening the collaboration between cities through differentiated strategies. This will enhance the spatial spillover effect of innovation, thus ultimately achieving a balanced spatial pattern of city innovation.

Suggested Citation

  • Kunlun Zhao & Wenxing Li, 2023. "High-Speed Railway Network, City Heterogeneity, and City Innovation," Sustainability, MDPI, vol. 15(21), pages 1-19, November.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15648-:d:1274709
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    1. Pierre‐Philippe Combes & Gilles Duranton & Laurent Gobillon & Diego Puga & Sébastien Roux, 2012. "The Productivity Advantages of Large Cities: Distinguishing Agglomeration From Firm Selection," Econometrica, Econometric Society, vol. 80(6), pages 2543-2594, November.
    2. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    3. Gao, Yanyan & Zheng, Jianghuai, 2020. "The impact of high-speed rail on innovation: An empirical test of the companion innovation hypothesis of transportation improvement with China’s manufacturing firms," World Development, Elsevier, vol. 127(C).
    4. Wang, Jiating & Cai, Siyuan, 2020. "The construction of high-speed railway and urban innovation capacity: Based on the perspective of knowledge Spillover," China Economic Review, Elsevier, vol. 63(C).
    5. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    6. Fingleton, Bernard & Szumilo, Nikodem, 2019. "Simulating the impact of transport infrastructure investment on wages: A dynamic spatial panel model approach," Regional Science and Urban Economics, Elsevier, vol. 75(C), pages 148-164.
    7. Dong, Xiaofang & Zheng, Siqi & Kahn, Matthew E., 2020. "The role of transportation speed in facilitating high skilled teamwork across cities," Journal of Urban Economics, Elsevier, vol. 115(C).
    8. Nancy Qian, 2008. "Missing Women and the Price of Tea in China: The Effect of Sex-Specific Earnings on Sex Imbalance," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(3), pages 1251-1285.
    9. Bjorn Asheim & Helen Lawton Smith & Christine Oughton, 2011. "Regional Innovation Systems: Theory, Empirics and Policy," Regional Studies, Taylor & Francis Journals, vol. 45(7), pages 875-891.
    Full references (including those not matched with items on IDEAS)

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