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Transportation infrastructure and capital mobility: evidence from China’s high-speed railways

The Annals of Regional Science volume 67, pages 617–648 (2021)Cite this article

Abstract

Using the data on venture capital investment in China and high-speed railway (HSR) construction as a natural experiment, this study presents empirical evidence about the impact of transportation infrastructure on capital mobility. The study finds that one new HSR train serving a city increases venture capital inflow to and outflow from that city by 1.0% and 1.6%, respectively. The heterogeneous analyses indicate that small cities, high-tech industries, and younger firms are significantly affected by HSR connections, which show that the accelerated information transmission and investors’ incremental growth expectations may account for the observed effect.

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Notes

  1. The four vertical HSR lines consist of Beijing–Shanghai, Beijing–Wuhan–Guangzhou–Shenzhen (Hong Kong), Beijing–Shenyang–Harbin (Dalian), and Shanghai–Hangzhou–Ningbo–Fuzhou–Shenzhen. The four horizontal HSR lines include Xuzhou–Zhengzhou–Lanzhou, Shanghai–Hangzhou–Nanchang–Changsha–Kunming, Qingdao–Shijiazhuang–Taiyuan, and Shanghai–Nanjing–Wuhan–Chongqing–Chengdu.

  2. In 2015, the national VC investment amount (including both intercity and intracity deals) was 259 billion RMB, accounting for only 0.4% of national total fixed asset investments (55,159 billion RMB).

  3. Historical exchange rates are collected from CSMAR Database (www.gtarsc.com).

  4. As there may be more than one HSR station for the connected cities and we have no access to the exact longitude and latitude for each VC participant, all the stations within a city are treated as a whole and transportation within the city was not considered. Specifically, information on both VC and HSR was aggregated at the city level. For instance, if there are 50 HSR trains in Shanghai South Railway Station and 30 in Shanghai West Railway Station, then based on our definition, there are 80 HSR connections for Shanghai. For future study, researchers could introduce a more precise transportation measure by geocoding every HSR location and calculate the accessibility of the stations to better examine the effect of transportation on other outcomes.

  5. The frequency of HSR connections to a city is the city-level HSR trains that depart, stop by, or arrive at the city. For instance, we assume that there are only two trains under operation—G10 and G30. The stops of G10 are Shanghai–Nanjing–Jinan–Beijing, and the stops of G13 are Beijing–Jinan–Nanjing–Suzhou–Shanghai. Thus, while the total number of HSR trains here is 2, the HSR connections for Beijing, Jinan, Nanjing, Suzhou, Shanghai are 2, 2, 2, 1, and 2, respectively.

  6. Column (1) of Table A1 reports the first-stage specification result, suggesting that our IV is significantly correlated with the key explanatory variable, hsr. The F-statistics is 13.58, indicating a pass of the weak IV test. Columns (2) to (7) of Table A1 show the empirical test for exclusion restriction where we include both the HSR and 1978 railway connection in the second-stage regression. In all regressions, the coefficients of IV are insignificant, indicating that the IV only affects the VC flow through the channel of HSR construction.

  7. The coefficient of HSR for capital inflow (0.010) multiplied by the average HSR connections (71.4) is equal to 71.4%. The average venture capital inflow is 29.1 million, so 71.4% of this is 20.7 million.

  8. Belke et al. (2003) report the elasticity of VC investment with respect to employment ranging from 0.006 to 0.03, so the employment growth rate caused by VC is between 0.3 and 1.8%.

  9. The 35 major cities in China include Beijing, Tianjin, Shijiazhuang, Taiyuan, Hohhot, Shenyang, Dalian, Changchun, Harbin, Shanghai, Nanjing, Hangzhou, Ningbo, Hefei, Fuzhou, Xiamen, Nanchang, Ji’nan, Qingdao, Zhengzhou, Wuhan, Changsha, Guangzhou, Shenzhen, Nanning, Haikou, Chongqing, Chengdu, Guiyang, Kunming, Xi’an, Lanzhou, Xining, Yinchuan, and Urumchi.

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Acknowledgements

Weizeng Sun thanks the National Natural Science Foundation of China for the support (No. 71903210).

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Authors and Affiliations

  1. Hang Lung Center for Real Estate and Department of Construction Management, Tsinghua University, Beijing, 100084, China

    Liaoliao Duan & Dongxiao Niu

  2. Sustainable Urbanization Lab and Center for Real Estate, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA

    Dongxiao Niu & Siqi Zheng

  3. School of Economics, Central University of Finance and Economics, 39 South College Road, Haidian District, Beijing, 100081, China

    Weizeng Sun

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  1. Liaoliao Duan
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Duan, L., Niu, D., Sun, W. et al. Transportation infrastructure and capital mobility: evidence from China’s high-speed railways. Ann Reg Sci 67, 617–648 (2021). https://doi.org/10.1007/s00168-021-01059-w

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