IDEAS home Printed from https://ideas.repec.org/p/spa/wpaper/2022wpecon19.html
   My bibliography  Save this paper

The Impact of High-Speed Rail on Labor Spatial Misallocation– Based on Spatial Difference-in-Differences Analysis

Author

Listed:
  • Linnan Yan
  • Menger Tu
  • Andre Luis Squarize Chagas
  • Lufeng Tai

Abstract

Existing studies neglected to assess the resource allocation effect of high-speed railway (HSR). This paper examines the impact of HSR on labor spatial misallocation in China by applying a modifified spatial difference-in-differences approach, which identify local treatment effect, spillover effect on treated and untreated regions. The study fifinds: (1) Opening HSR alleviates not only the local labor misallocation but also the misallocation in surrounding areas to a greater extent, including cities with HSR (treatment group) and without HSR (control group), which contributes to the overall productivity increase. The spillover effect of HSR is larger than the direct effect. (2) The largest spillover effect occurs in adjacent areas near 350 km apart, while the spillover effect disappears beyond 500 km. (3) The direction and magnitude of HSR effect depend on the urban scale. For large-scale cities, the impact of opening HSR is greater versus small-scale ones.

Suggested Citation

  • Linnan Yan & Menger Tu & Andre Luis Squarize Chagas & Lufeng Tai, 2022. "The Impact of High-Speed Rail on Labor Spatial Misallocation– Based on Spatial Difference-in-Differences Analysis," Working Papers, Department of Economics 2022_19, University of São Paulo (FEA-USP).
    • Handle: RePEc:spa:wpaper:2022wpecon19
    as

    Download full text from publisher

    File URL: http://www.repec.eae.fea.usp.br/documentos/Yan_Tu_Chagas_Tai_19WP.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bartelsman, Eric & Dobbelaere, Sabien & Peters, Bettina, 2013. "Allocation of Human Capital and Innovation at the Frontier: Firm-Level Evidence on Germany and the Netherlands," IZA Discussion Papers 7540, Institute of Labor Economics (IZA).
    2. Delgado, Michael S. & Florax, Raymond J.G.M., 2015. "Difference-in-differences techniques for spatial data: Local autocorrelation and spatial interaction," Economics Letters, Elsevier, vol. 137(C), pages 123-126.
    3. 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.
    4. Remi Jedwab & Alexander Moradi, 2016. "The Permanent Effects of Transportation Revolutions in Poor Countries: Evidence from Africa," The Review of Economics and Statistics, MIT Press, vol. 98(2), pages 268-284, May.
    5. Kim, Hyojin & Sultana, Selima, 2015. "The impacts of high-speed rail extensions on accessibility and spatial equity changes in South Korea from 2004 to 2018," Journal of Transport Geography, Elsevier, vol. 45(C), pages 48-61.
    6. 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.
    7. Komei Sasaki & Tadahiro Ohashi & Asao Ando, 1997. "High-speed rail transit impact on regional systems: does the Shinkansen contribute to dispersion?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 31(1), pages 77-98.
    8. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    9. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    10. Chang-Tai Hsieh & Enrico Moretti, 2019. "Housing Constraints and Spatial Misallocation," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(2), pages 1-39, April.
    11. Piet Rietveld & Frank Bruinsma, 1998. "The Accessibility of Cities in European Infrastructure Networks," Advances in Spatial Science, in: Is Transport Infrastructure Effective?, chapter 5, pages 115-139, Springer.
    12. Roberto Ramos & Manuel García-Santana & Jose Asturias, 2014. "Misallocation, Internal Trade, and the Role of Transportation Infrastructure," 2014 Meeting Papers 1035, Society for Economic Dynamics.
    13. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    14. Chang-Tai Hsieh & Peter J. Klenow, 2009. "Misallocation and Manufacturing TFP in China and India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(4), pages 1403-1448.
    15. Andrew B. Bernard & Andreas Moxnes & Yukiko U. Saito, 2019. "Production Networks, Geography, and Firm Performance," Journal of Political Economy, University of Chicago Press, vol. 127(2), pages 639-688.
    16. 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.
    17. 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.
    18. 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.
    19. Aoki, Shuhei, 2012. "A simple accounting framework for the effect of resource misallocation on aggregate productivity," Journal of the Japanese and International Economies, Elsevier, vol. 26(4), pages 473-494.
    20. Fu, Shihe & Gu, Yizhen, 2017. "Highway toll and air pollution: Evidence from Chinese cities," Journal of Environmental Economics and Management, Elsevier, vol. 83(C), pages 32-49.
    21. 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.
    22. Chagas, André L.S. & Azzoni, Carlos R. & Almeida, Alexandre N., 2016. "A spatial difference-in-differences analysis of the impact of sugarcane production on respiratory diseases," Regional Science and Urban Economics, Elsevier, vol. 59(C), pages 24-36.
    23. Benjamin Moll, 2014. "Productivity Losses from Financial Frictions: Can Self-Financing Undo Capital Misallocation?," American Economic Review, American Economic Association, vol. 104(10), pages 3186-3221, October.
    24. Abhijit V. Banerjee & Benjamin Moll, 2010. "Why Does Misallocation Persist?," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(1), pages 189-206, January.
    25. Solmaria Halleck Vega & J. Paul Elhorst, 2015. "The Slx Model," Journal of Regional Science, Wiley Blackwell, vol. 55(3), pages 339-363, June.
    26. Moshe Givoni, 2006. "Development and Impact of the Modern High‐speed Train: A Review," Transport Reviews, Taylor & Francis Journals, vol. 26(5), pages 593-611, January.
    27. Hodgson, Charles, 2018. "The effect of transport infrastructure on the location of economic activity: Railroads and post offices in the American West," Journal of Urban Economics, Elsevier, vol. 104(C), pages 59-76.
    28. Li, Pei & Lu, Yi & Wang, Jin, 2016. "Does flattening government improve economic performance? Evidence from China," Journal of Development Economics, Elsevier, vol. 123(C), pages 18-37.
    29. 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. Jiao, Jingjuan & Zhao, Hongyu & Lyu, Guowei, 2024. "How does high-speed rail affect off-site investments? Evidence from the Yangtze River Delta, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    2. Wen Yang & Quanliang Chen & Jing Yang, 2022. "Factors Affecting Travel Mode Choice between High-Speed Railway and Road Passenger Transport—Evidence from China," Sustainability, MDPI, vol. 14(23), pages 1-17, November.
    3. Dong, Dayong & Jiang, Danling & Wu, Keke & Zhu, Hongquan, 2024. "Game in another town: Geography of stock watchlists and firm valuation," Journal of Banking & Finance, Elsevier, vol. 163(C).

    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. Yan, Linnan & Tu, Menger & Chagas, André L.S. & Tai, Lufeng, 2022. "The impact of high-speed railway on labor spatial misallocation—Based on spatial difference-in-differences analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 164(C), pages 82-97.
    2. 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).
    3. Xinyuan Wang & Daisheng Tang & Yahong Liu & Tao Bu, 2023. "The impact of high-speed railway on labor market between the North and South: evidence from China," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 71(2), pages 487-515, October.
    4. Laiqun Jin & Xiuyan Liu & Sam Hak Kan Tang, 2021. "High-Technology Zones, Misallocation of Resources among Cities and Aggregate Productivity: Evidence from China," Economics Discussion / Working Papers 21-11, The University of Western Australia, Department of Economics.
    5. 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.
    6. Ma, Liya & Niu, Dongxiao & Sun, Weizeng, 2021. "Transportation infrastructure and entrepreneurship: Evidence from high-speed railway in China," China Economic Review, Elsevier, vol. 65(C).
    7. 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.
    8. Bo, Shiyu, 2020. "Centralization and regional development: Evidence from a political hierarchy reform to create cities in china," Journal of Urban Economics, Elsevier, vol. 115(C).
    9. 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).
    10. Zhang, Xueliang & Hu, Yuqi & Lin, Yongran, 2020. "The influence of highway on local economy: Evidence from China's Yangtze River Delta region," Journal of Transport Geography, Elsevier, vol. 82(C).
    11. Okamoto, Chigusa & Sato, Yasuhiro, 2021. "Impacts of high-speed rail construction on land prices in urban agglomerations: Evidence from Kyushu in Japan," Journal of Asian Economics, Elsevier, vol. 76(C).
    12. Yang, Xiaolan & Wang, Rui & Guo, Dongmei & Sun, Weizeng, 2020. "The reconfiguration effect of China's high-speed railway on intercity connection ——A study based on media attention index," Transport Policy, Elsevier, vol. 95(C), pages 47-56.
    13. Nannan Yu & Tianhang Cui & Si Lv, 2023. "Does the High-Speed Rail Improve Employment in Peripheral Cities? Evidence From China’s Beijing–Shanghai HSR Line," SAGE Open, , vol. 13(4), pages 21582440231, December.
    14. Chang, Zheng & Diao, Mi & Jing, Kecen & Li, Weifeng, 2021. "High-speed rail and industrial movement: Evidence from China's Greater Bay Area," Transport Policy, Elsevier, vol. 112(C), pages 22-31.
    15. 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.
    16. Xiaole Wang & Feng Dong & Yuling Pan & Yajie Liu, 2022. "Transport Infrastructure, High-Quality Development and Industrial Pollution: Fresh Evidence from China," IJERPH, MDPI, vol. 19(15), pages 1-24, August.
    17. Zhigang Li & Hangtian Xu, 2018. "High‐speed railroads and economic geography: Evidence from Japan," Journal of Regional Science, Wiley Blackwell, vol. 58(4), pages 705-727, September.
    18. Fan, Xiaomin & Xu, Yingzhi, 2024. "How does the opening of high-speed railway affect the regional pollution gap in China? From the perspective of knowledge spillover," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    19. 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.
    20. 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.

    More about this item

    Keywords

    high-speed railway; spatial difference-in-differences; labor spatial;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:spa:wpaper:2022wpecon19. 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: Pedro Garcia Duarte (email available below). General contact details of provider: https://edirc.repec.org/data/deuspbr.html .

    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.