EconPapers    
Economics at your fingertips  
 

Spatial Structure Evolution and Economic Benefits of Rapidly Expanding the High-Speed Rail Network in Developing Regions: A Case Study in Western China

Bo Yang, Yaping Yang, Yangxiaoyue Liu and Xiafang Yue
Additional contact information
Bo Yang: State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Yaping Yang: State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Yangxiaoyue Liu: State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Xiafang Yue: State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Sustainability, 2022, vol. 14, issue 23, 1-20

Abstract: High-speed rail (HSR) is an important form of transportation that affects the economic development of the regional spatial structure. However, there is less discussion about the impact of economically underdeveloped regions and the rapid construction of HSR on the region. This study uses a spatial econometric model to explore whether a rapidly formed high-speed rail network with changes in the network structure can bring economic effects based on the spatio-temporal panel data on high-speed rail construction and economic development in western China from 2015 to 2020. First, data of the daily departures between high-speed rail cities were used to analyze the western high-speed rail network’s spatial and temporal evolution characteristics. Second, we analyzed the changes in the centrality, external and internal connectivity, and transfer potential of the economic gap of the western HSR network. Finally, we analyzed the different economic effects of the HSR network structure by combining the Cobb–Douglas production function with the spatial econometric model. The conclusions are as follows: (1) The HSR network in western China is dense at the intra-provincial HSR network; then it expands along the cross-provincial region; and is gradually embedded in the national HSR network, forming a figure-8-shaped spatial structure. (2) In the rapid expansion and densification of the HSR network in western China, connectivity takes precedence, and dominance and control are then increased. The external connectivity of the western HSR city network develops first and shows fluctuating growth, while the internal connectivity improves relatively slowly. (3) The connectivity, convenience of transit, transshipment capacity, and internal and external connection structure of the HSR network all contribute to the economic development of western cities. The transfer potential of economic gaps is detrimental to their economic development but has a positive effect on adjacent cities.

Keywords: high-speed railway network; economic effect; spatial-temporal evolution; spatial econometric model; western China (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/23/15914/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/23/15914/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:23:p:15914-:d:987953

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:15914-:d:987953