Abstract

High-speed rail (HSR) can potentially influence various economic activities across space. Estimating the impacts of HSR on service-sector agglomeration (SSA) was proven to be difficult but meaningful. In this paper, prefectural-level data from 1998 to 2016 and a panel data program evaluation method are employed to evaluate the effect of the Wuhan–Guangzhou HSR (WGHSR) on the SSA along the route. In this way, we construct hypothetical counterfactuals for SSA index of the WGHSR cities in the absence of the HSR projects using the SSA index in selected non-HSR cities. By comparing the counterfactual index and the actual index, the evaluation of the WGHSR’s impact on the SSA along the route can be obtained. The results show that: (a) the WGHSR has increased the SSA by 9.44% on average for cities along the WGHSR, and (b) the impacts of the WGHSR on the SSA are heterogeneous. The WGHSR has brought about both spillover effect and “siphon” effect. In addition, whether the HSR influences and how much it could influence the SSA requires other supplementary conditions to be met. As a national strategy in China, the construction plan of HSR should fully consider its heterogeneity of impact on regional development. Policies should be formulated to drive the HSR’s spillover effect to promote regional sustainable development.

Highlights

  • Lines designed for speeds above 250 km/h and upgraded existing lines for speeds of up to 200 km/h are considered as high-speed rail [1]

  • Based on establishing the optimal control-group cities synthesis for each control group city, we evaluated how the Wuhan–Guangzhou HSR (WGHSR) affects the service-sector agglomeration (SSA) along the line

  • As High-speed rail (HSR) significantly reduces the restrictions of spatial distance on the flows of factor resources, it exerts a profound impact on the service-sector with fast flows of factor resources

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Summary

Introduction

Lines designed for speeds above 250 km/h and upgraded existing lines for speeds of up to 200 km/h are considered as high-speed rail [1]. It is generally believed that HSR could improve accessibility, produce the time-space compression effect, facilitate the spatial (re)distribution of factor resources and exert impacts on regional economy. Some studies point out that HSR can accelerates the resources flowing and promotes economic development [23,24,25,26]; Second, some studies suggest that HSR has a disadvantage on the economic development to some extent, which largely due to its high-cost of building, operating, maintaining, and so on [27,28,29,30]; Third, it is found that HSR exerts uneven impacts across the space, which means HSR’s impacts vary across different cities or different stages of the operation of HSR. Evaluating the impact of HSR is of great significance for balancing regional economy and promoting sustainable development. Study Lu et al (2013) [23] Chen and Haynes (2017) [24] Shao et al (2017) [25] Wetwitoo and Kato (2017) [26] Zhao et al (2015) [28] Wu et al (2014) [29] Wang et al (2017) [30] Kim and Sultana (2015) [31]

Conclusion
Introduction to Research Subjects
Treatment Group Cities Selection
Candidate Control Group Cities Selection
A Brief Introduction of the HCW Model
Descriptive Statistical Analysis
HCW Model Results and Analysis
F Statistics
Robustness Check
Conclusions and Policy Implications
Full Text
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