IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i19p8239-d424440.html
   My bibliography  Save this article

Does High-Speed Rail Network Access Enhance Cities’ Innovation Performance?

Author

Listed:
  • Qunyang Du

    (School of Economics, Zhejiang University of Technology, Hangzhou 310023, China)

  • Hangdong Yu

    (School of Economics, Zhejiang University of Technology, Hangzhou 310023, China)

  • Cheng Yan

    (School of Economics, Zhejiang University of Technology, Hangzhou 310023, China)

  • Tianle Yang

    (School of Economics, Zhejiang University of Technology, Hangzhou 310023, China)

Abstract

This study investigates the impacts of access to high-speed railway networks (HSRN) on urban innovative performance using a difference-in-difference method and a unique dataset including patents, nighttime lights, and HSRN at the city-level in China. First, access to HSRN significantly and positively affects the city’s innovative performance. Results remain robust after substituting different innovation indicators and controlling for city-level factors. Second, the impacts vary with the size of cities. Specifically, the benefits of access to HSRN for large and small cities are greater than for medium-sized cities, which shows a quasi-U-shaped relationship. Third, the positive effects of access to HSRN on innovation performance are stronger in knowledge-intensive industries for large cities and where there is high population mobility among cities.

Suggested Citation

  • Qunyang Du & Hangdong Yu & Cheng Yan & Tianle Yang, 2020. "Does High-Speed Rail Network Access Enhance Cities’ Innovation Performance?," Sustainability, MDPI, vol. 12(19), pages 1-13, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:8239-:d:424440
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/19/8239/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/19/8239/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Xiaofang Dong & Siqi Zheng & Matthew E. Kahn, 2018. "The Role of Transportation Speed in Facilitating High Skilled Teamwork," NBER Working Papers 24539, National Bureau of Economic Research, Inc.
    3. Riccardo Crescenzi & Andrés Rodríguez-Pose & Michael Storper, 2012. "The territorial dynamics of innovation in China and India," Journal of Economic Geography, Oxford University Press, vol. 12(5), pages 1055-1085, September.
    4. Adam B. Jaffe & Manuel Trajtenberg & Rebecca Henderson, 1993. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(3), pages 577-598.
    5. Daron Acemoglu & Ufuk Akcigit, 2012. "Intellectual Property Rights Policy, Competition And Innovation," Journal of the European Economic Association, European Economic Association, vol. 10(1), pages 1-42, February.
    6. Thorsten Beck & Ross Levine & Alexey Levkov, 2010. "Big Bad Banks? The Winners and Losers from Bank Deregulation in the United States," Journal of Finance, American Finance Association, vol. 65(5), pages 1637-1667, October.
    7. Benjamin Faber, 2014. "Trade Integration, Market Size, and Industrialization: Evidence from China's National Trunk Highway System," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(3), pages 1046-1070.
    8. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    9. Baum-Snow, Nathaniel & Henderson, J. Vernon & Turner, Matthew A. & Zhang, Qinghua & Brandt, Loren, 2020. "Does investment in national highways help or hurt hinterland city growth?," Journal of Urban Economics, Elsevier, vol. 115(C).
    10. Banerjee, Abhijit & Duflo, Esther & Qian, Nancy, 2020. "On the road: Access to transportation infrastructure and economic growth in China," Journal of Development Economics, Elsevier, vol. 145(C).
    11. Yu Qin, 2017. "‘No county left behind?’ The distributional impact of high-speed rail upgrades in China," Journal of Economic Geography, Oxford University Press, vol. 17(3), pages 489-520.
    12. Nathaniel Baum-Snow & Loren Brandt & J. Vernon Henderson & Matthew A. Turner & Qinghua Zhang, 2017. "Roads, Railroads, and Decentralization of Chinese Cities," The Review of Economics and Statistics, MIT Press, vol. 99(3), pages 435-448, July.
    13. 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).
    14. Dang, Jianwei & Motohashi, Kazuyuki, 2015. "Patent statistics: A good indicator for innovation in China? Patent subsidy program impacts on patent quality," China Economic Review, Elsevier, vol. 35(C), pages 137-155.
    15. Lin, Yatang, 2017. "Travel costs and urban specialization patterns: Evidence from China’s high speed railway system," Journal of Urban Economics, Elsevier, vol. 98(C), pages 98-123.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Xiang & Cheng, Zhonghua, 2022. "Does high-speed rail improve urban carbon emission efficiency in China?," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    2. Eryu Zhang & Xiaoyu He & Peng Xiao, 2022. "Does Smart City Construction Decrease Urban Carbon Emission Intensity? Evidence from a Difference-in-Difference Estimation in China," Sustainability, MDPI, vol. 14(23), pages 1-16, December.
    3. Wu, Rong & Li, Yingcheng & Wang, Shaojian, 2022. "Will the construction of high-speed rail accelerate urban land expansion? Evidences from Chinese cities," Land Use Policy, Elsevier, vol. 114(C).
    4. Yang, Xuehui & Zhang, Huirong & Li, Yan, 2022. "High-speed railway, factor flow and enterprise innovation efficiency: An empirical analysis on micro data," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hanley, Douglas & Li, Jiancheng & Wu, Mingqin, 2022. "High-speed railways and collaborative innovation," Regional Science and Urban Economics, Elsevier, vol. 93(C).
    2. Anna Bottasso & Maurizio Conti & Simone Robbiano & Marta Santagata, 2022. "Roads to innovation: Evidence from Italy," Journal of Regional Science, Wiley Blackwell, vol. 62(4), pages 981-1005, September.
    3. Liaoliao Duan & Dongxiao Niu & Weizeng Sun & Siqi Zheng, 2021. "Transportation infrastructure and capital mobility: evidence from China’s high-speed railways," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(3), pages 617-648, December.
    4. Jingbo Cui & Tianqi Li & Zhenxuan Wang, 2023. "Research collaboration beyond the boundary: Evidence from university patents in China," Journal of Regional Science, Wiley Blackwell, vol. 63(3), pages 674-702, June.
    5. 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).
    6. Haoran Zhang & Ying Chai & Xuyu Yang & Wenli Zhao, 2022. "High-Speed Rail and Urban Growth Disparity: Evidence from China," Sustainability, MDPI, vol. 14(13), pages 1-13, July.
    7. Kang, Meiling & Li, Yucheng & Zhao, Zhongkuang & Song, Min & Yi, Jun, 2023. "Travel costs and inter-city collaborative innovation: Evidence of high-speed railway in China," Structural Change and Economic Dynamics, Elsevier, vol. 65(C), pages 286-302.
    8. Li, Chunying & Zhang, Jinning & Lyu, Yanwei, 2022. "Does the opening of China railway express promote urban total factor productivity? New evidence based on SDID and SDDD model," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    9. Chang, Zheng & Zheng, Longfei, 2022. "High-speed rail and the spatial pattern of new firm births: Evidence from China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 373-386.
    10. Dongxiao Niu & Weizeng Sun & Siqi Zheng, 2020. "Travel costs, trade, and market segmentation: Evidence from China's high‐speed railway," Papers in Regional Science, Wiley Blackwell, vol. 99(6), pages 1799-1825, December.
    11. Yatang Lin & Yu Qin & Johan Sulaeman & Jubo Yan & Jialiang Zhang, 2023. "Expanding Footprints: The Impact of Passenger Transportation on Corporate Locations," Review of Finance, European Finance Association, vol. 27(3), pages 1119-1154.
    12. Baek, Jisun & Park, WooRam, 2022. "The impact of improved passenger transport system on manufacturing plant productivity," Regional Science and Urban Economics, Elsevier, vol. 96(C).
    13. Xiao Ke & Yuanke Yan, 2021. "Can proactive fiscal policy achieve the goal of “Beyond Keynesianism”?," Review of Development Economics, Wiley Blackwell, vol. 25(2), pages 1078-1103, May.
    14. Xu, Yang & Yang, Xi, 2021. "Access to ports and the welfare gains from domestic transportation infrastructure," Journal of Urban Economics, Elsevier, vol. 126(C).
    15. Yahong Liu & Daisheng Tang & Tao Bu & Xinyuan Wang, 2022. "The spatial employment effect of high-speed railway: quasi-natural experimental evidence from China," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 69(2), pages 333-359, October.
    16. Koster, Hans & Hayakawa, Kazunobu & Thisse, Jacques-François, 2021. "High-speed Rail and the Spatial Distribution of Economic Activity: Evidence from Japan's Shinkansen," CEPR Discussion Papers 15771, C.E.P.R. Discussion Papers.
    17. Yanyan Gao & Yongqing Nan & Shunfeng Song, 2022. "High‐speed rail and city tourism: Evidence from Tencent migration big data on two Chinese golden weeks," Growth and Change, Wiley Blackwell, vol. 53(3), pages 1012-1036, September.
    18. He, Guojun & Xie, Yang & Zhang, Bing, 2020. "Expressways, GDP, and the environment: The case of China," Journal of Development Economics, Elsevier, vol. 145(C).
    19. Xiao Ke & Justin Yifu Lin & Caihui Fu & Yong Wang, 2020. "Transport Infrastructure Development and Economic Growth in China: Recent Evidence from Dynamic Panel System-GMM Analysis," Sustainability, MDPI, vol. 12(14), pages 1-22, July.
    20. Xiaoqian Liu & Han Li & Yongzhi Sun & Chang’an Wang, 2022. "High‐speed railway and urban productivity disparities," Growth and Change, Wiley Blackwell, vol. 53(2), pages 680-701, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:8239-:d:424440. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.