IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i13p3681-d245684.html
   My bibliography  Save this article

The Impact of High-Speed Rail on Housing Prices: Evidence from China’s Prefecture-Level Cities

Author

Listed:
  • Rong Wang

    (School of Economics and Management, Hebei University of Technology, Tianjin 300401, China)

  • Li Ye

    (School of Economics and Management, Hebei University of Technology, Tianjin 300401, China)

  • Liwen Chen

    (School of Economics and Management, Hebei University of Technology, Tianjin 300401, China)

Abstract

The rapid development of the high-speed rail (HSR) network enhanced the regional accessibility between cities, drove the rise in cities’ investment levels, and expanded the activity radius of the labor force, causing changes in housing prices along the rail lines. Based on panel data of 285 cities in China from 2008–2016, this study used the difference-in-difference based on propensity score matching (PSM-DID) method to calculate the impact of HSR on housing prices. The conclusions of the study indicated that, at the regional level, HSR significantly promoted the rise in housing prices in HSR cities along the rail line. HSR had a positive effect on housing prices, where the coefficient of HSR influence was 0.1511 and passed a 1% significance test. From the perspective of the combination of sub-regional and sub-city scales, HSR mainly played a significant role in promoting housing prices in “small and medium-sized cities” and “central and western cities”, especially in small and medium-sized cities in the central and western regions; in general, HSR can narrow the housing price gap between “small and medium-sized HSR cities” in the central and western regions and large HSR cities in the east region. Lastly, the results of the intermediary mechanism test showed that the income level of residents and employment levels played an intermediary role in the influence of HSR on the housing prices of cities along the rail line. Thus, this paper suggests that the Chinese government needs to formulate housing price control policies that suit local conditions according to the characteristics of different cities.

Suggested Citation

  • Rong Wang & Li Ye & Liwen Chen, 2019. "The Impact of High-Speed Rail on Housing Prices: Evidence from China’s Prefecture-Level Cities," Sustainability, MDPI, vol. 11(13), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:13:p:3681-:d:245684
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/13/3681/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/13/3681/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shaw, Shih-Lung & Fang, Zhixiang & Lu, Shiwei & Tao, Ran, 2014. "Impacts of high speed rail on railroad network accessibility in China," Journal of Transport Geography, Elsevier, vol. 40(C), pages 112-122.
    2. Ke, Xiao & Chen, Haiqiang & Hong, Yongmiao & Hsiao, Cheng, 2017. "Do China's high-speed-rail projects promote local economy?—New evidence from a panel data approach," China Economic Review, Elsevier, vol. 44(C), pages 203-226.
    3. Zhang, Yue-Jun & Peng, Yu-Lu & Ma, Chao-Qun & Shen, Bo, 2017. "Can environmental innovation facilitate carbon emissions reduction? Evidence from China," Energy Policy, Elsevier, vol. 100(C), pages 18-28.
    4. Chen, Zhenhua & Xue, Junbo & Rose, Adam Z. & Haynes, Kingsley E., 2016. "The impact of high-speed rail investment on economic and environmental change in China: A dynamic CGE analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 232-245.
    5. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    6. Richard Blundell & Monica Costa Dias, 2000. "Evaluation methods for non-experimental data," Fiscal Studies, Institute for Fiscal Studies, vol. 21(4), pages 427-468, January.
    7. Svein Olav Krakstad & Are Oust, 2015. "Are house prices in the Norwegian capital too high?," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 8(2), pages 152-168, June.
    8. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(1), pages 1-19.
    9. Vickerman, Roger, 2015. "High-speed rail and regional development: the case of intermediate stations," Journal of Transport Geography, Elsevier, vol. 42(C), pages 157-165.
    10. Changkyu Choi & Hojin Jung, 2017. "Does an economically active population matter in housing prices?," Applied Economics Letters, Taylor & Francis Journals, vol. 24(15), pages 1061-1064, September.
    11. Chandra, Shailesh & Vadali, Sharada, 2014. "Evaluating accessibility impacts of the proposed America 2050 high-speed rail corridor for the Appalachian Region," Journal of Transport Geography, Elsevier, vol. 37(C), pages 28-46.
    12. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    13. Baier, Scott L. & Bergstrand, Jeffrey H., 2009. "Estimating the effects of free trade agreements on international trade flows using matching econometrics," Journal of International Economics, Elsevier, vol. 77(1), pages 63-76, February.
    14. Alberto Abadie & Guido W. Imbens, 2008. "On the Failure of the Bootstrap for Matching Estimators," Econometrica, Econometric Society, vol. 76(6), pages 1537-1557, November.
    15. Tierney, Sean, 2012. "High-speed rail, the knowledge economy and the next growth wave," Journal of Transport Geography, Elsevier, vol. 22(C), pages 285-287.
    16. Christopher Mayer, 2011. "Housing Bubbles: A Survey," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 559-577, September.
    17. Wang, Songtao & Yang, Zan & Liu, Hongyu, 2011. "Impact of urban economic openness on real estate prices: Evidence from thirty-five cities in China," China Economic Review, Elsevier, vol. 22(1), pages 42-54, March.
    18. Jia, Shanming & Zhou, Chunyu & Qin, Chenglin, 2017. "No difference in effect of high-speed rail on regional economic growth based on match effect perspective?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 144-157.
    19. Chen, Zhenhua & Haynes, Kingsley E., 2015. "Impact of high speed rail on housing values: an observation from the Beijing–Shanghai line," Journal of Transport Geography, Elsevier, vol. 43(C), pages 91-100.
    20. Yingchao Lin & Zhili Ma & Ke Zhao & Weiyan Hu & Jing Wei, 2018. "The Impact of Population Migration on Urban Housing Prices: Evidence from China’s Major Cities," Sustainability, MDPI, vol. 10(9), pages 1-14, September.
    21. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    22. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    23. Shao, Shuai & Tian, Zhihua & Yang, Lili, 2017. "High speed rail and urban service industry agglomeration: Evidence from China's Yangtze River Delta region," Journal of Transport Geography, Elsevier, vol. 64(C), pages 174-183.
    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. Lan, Hao & Moreira, Fernando & Zhao, Sheng, 2023. "Can a house resale restriction policy curb speculation? Evidence from a quasi-natural experiment in China," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 841-859.
    2. Seunghoon Kim, 2020. "The Social Justice Impact of the Transit-Oriented Development," Societies, MDPI, vol. 11(1), pages 1-19, December.
    3. Jianling Li & Changdong Ye & Jiangxue Yang, 2022. "Rail-Induced Social Changes in Central Guangzhou, China," Sustainability, MDPI, vol. 14(21), pages 1-13, October.
    4. Suchi Kapoor Malhotra & Howard White & Nina Ashley O. Dela Cruz & Ashrita Saran & John Eyers & Denny John & Ella Beveridge & Nina Blöndal, 2021. "Studies of the effectiveness of transport sector interventions in low‐ and middle‐income countries: An evidence and gap map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(4), December.

    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. Yang, Zhiwei & Li, Can & Jiao, Jingjuan & Liu, Wei & Zhang, Fangni, 2020. "On the joint impact of high-speed rail and megalopolis policy on regional economic growth in China," Transport Policy, Elsevier, vol. 99(C), pages 20-30.
    2. Li, Hui & Dong, Xiucheng & Jiang, Qingzhe & Dong, Kangyin, 2021. "Policy analysis for high-speed rail in China: Evolution, evaluation, and expectation," Transport Policy, Elsevier, vol. 106(C), pages 37-53.
    3. Jin, Mengjie & Shi, Wenming & Liu, Yu & Xu, Xiaoling & Li, Kevin X., 2022. "Heterogeneous impact of high speed railway on income distribution: A case study in China," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    4. Li, Xiaolong & Wu, Zongfa & Zhao, Xingchen, 2020. "Economic effect and its disparity of high speed rail in China: A study of mechanism based on synthesis control method," Transport Policy, Elsevier, vol. 99(C), pages 262-274.
    5. Junhui Shi & Fang Wang, 2022. "The Effect of High-Speed Rail on Cropland Abandonment in China," Land, MDPI, vol. 11(7), pages 1-16, July.
    6. Liu, Mengsha & Jiang, Yan & Wei, Xiaokun & Ruan, Qingsong & Lv, Dayong, 2023. "Effect of high-speed rail on entrepreneurial activities: Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    7. Li, Yan & Chen, Zhenhua & Wang, Peng, 2020. "Impact of high-speed rail on urban economic efficiency in China," Transport Policy, Elsevier, vol. 97(C), pages 220-231.
    8. 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).
    9. Wang, Yongpei & Guan, Zhongyu & Zhang, Qian, 2023. "Railway opening and carbon emissions in distressed areas: Evidence from China's state-level poverty-stricken counties," Transport Policy, Elsevier, vol. 130(C), pages 55-67.
    10. Zhang, Yuxin & Xu, Dafeng, 2023. "Service on the rise, agriculture and manufacturing in decline: The labor market effects of high-speed rail services in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 171(C).
    11. Di Matteo, Dante & Mariotti, Ilaria & Rossi, Federica, 2023. "Transport infrastructure and economic performance: An evaluation of the Milan-Bologna high-speed rail corridor," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    12. (Ato) Xu, Wangtu & Zhou, Jiangping & Yang, Linchuan & Li, Ling, 2018. "The implications of high-speed rail for Chinese cities: Connectivity and accessibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 308-326.
    13. Jin, Mengjie & Lin, Kun-Chin & Shi, Wenming & Lee, Paul T.W. & Li, Kevin X., 2020. "Impacts of high-speed railways on economic growth and disparity in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 158-171.
    14. Kim, Hyojin & Sultana, Selima & Weber, Joe, 2018. "A geographic assessment of the economic development impact of Korean high-speed rail stations," Transport Policy, Elsevier, vol. 66(C), pages 127-137.
    15. Xinhai Lu & Yifeng Tang & Shangan Ke, 2021. "Does the Construction and Operation of High-Speed Rail Improve Urban Land Use Efficiency? Evidence from China," Land, MDPI, vol. 10(3), pages 1-15, March.
    16. Zheng, Longfei & Long, Fenjie & Chang, Zheng & Ye, Jingsong, 2019. "Ghost town or city of hope? The spatial spillover effects of high-speed railway stations in China," Transport Policy, Elsevier, vol. 81(C), pages 230-241.
    17. Jiao, Jingjuan & Wang, Jiaoe & Zhang, Fangni & Jin, Fengjun & Liu, Wei, 2020. "Roles of accessibility, connectivity and spatial interdependence in realizing the economic impact of high-speed rail: Evidence from China," Transport Policy, Elsevier, vol. 91(C), pages 1-15.
    18. Liu, Liwen & Zhang, Ming, 2018. "High-speed rail impacts on travel times, accessibility, and economic productivity: A benchmarking analysis in city-cluster regions of China," Journal of Transport Geography, Elsevier, vol. 73(C), pages 25-40.
    19. Huang, Ying & Xu, Wangtu (Ato), 2021. "Spatial and temporal heterogeneity of the impact of high-speed railway on urban economy: Empirical study of Chinese cities," Journal of Transport Geography, Elsevier, vol. 91(C).
    20. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.

    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:11:y:2019:i:13:p:3681-:d:245684. 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.