Influence of high-speed railway network on individual income: evidence from China’s microeconomic data

Abstract

China’s increasingly developed high-speed railways (HSR) network has been found to have important influences on economic development, but analysis of its effect on individual income is inadequate. Based on the data of Chinese Household Income Project Survey (CHIP07 and CHIP13) and China’s HSR data, this paper examines HSR’s influence on residents’ income and the underlying mechanism. Using the difference-in-differences (DID) approach, we document that the connection of HSR network increases both urban and rural residents’ income. Besides, to address the potential endogeneity, we construct the least cost path spanning tree network to be served as an instrumental variable (IV) of HSR and the results confirm the reliability of the conclusion. What’s more, a HSR-induced industrial restructuring mechanism is revealed by further study, and those who received the higher education is proved to benefit most from HSR. Therefore, education turns out to be an effective way to enhance HSR’s income effect.

KEYWORDS:

• China’s HSR
• individual income
• least cost path spanning tree network
• heterogeneity

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. gov.cn/xinwen/2016-07/20/content_5093165.htm

2. Newly built passenger dedicated lines with (actual or reserved) speed of 250 km/h and above (Order No. 34, 2013 from China’s Ministry of Railways).

3. Law of Nation Shinkansen Railway. 1970. Law, No.71. May 18.

4. UIC, 2013. High-speed lines of the world. uic.org/spip.php?mot8 .

5. By the State Department of China.

6. National Railway Administration (NRA), 2014. Railway Safety Management Regulations. Beijing: China Railway Publishing House.

7. Sometimes, China’s HSR is called CRH short for ‘China’s Railway High-speed’ in document.

8. According to finance.sina.com.cn/china/gncj/2017-02-19/doc-ifyarzzv3199194.shtml

9. Shanghai, Guangzhou, Shenzhen, Dongguan, Nanjing, Wuxi, Hangzhou, Ningbo, Wuhan, Chongqing, Chengdu, Hefei, Bangbu, Luoyang, and Zhengzhou, respectively.

10. sohu.com/a/132907706_648458.

11. From National Highway Network Planning(2013–2030)

12. From Long-term Railroad Network Planning(2016)

13. Red lines indicate the HSR network by 2013, and the black lines are results of least cost path spanning tree network.

14. The data of STRM are collected under the cooperation of The space agency NASA and NIMA.

15. The platform presents public data by Computer Network Information Center of Chinese Academy of Sciences. gscloud.cn/

16. By the State Bureau of Quality and Technical Supervision and China National Standardization Management Committee.

17. An outline of China to build into a country with strong transportation network: the construction will roughly process in two phases: Firstly, from 2020 to 2035, basically building China’s strength in transportation and struggling to join the ranks of countries with strong transportation network. Secondly, from 2036 to the mid-century, finishing building China into a country with strong transportation network and making China a leading power in the world in terms of transportation. (By Central Committee of the Communist Party of China and the state council,September2019)

Additional information

Funding

This study was supported by National Social Science Foundation of China [18VSJ023]; the China Postdoctoral Science Foundation [2020M681803]; and the Zhejiang Provincial Natural Science Foundation of China [LQ21G030002].