Impacts of high-speed rail on intercity patient mobility: evidence from chronic kidney disease hospitalization in China

The continuous improvement of urban accessibility has had an increasingly prominent impact on the housing market, especially on urban housing prices. In this process, high speed rail (HSR) can play a key role. Based on urban panel data relating to the Yangtze River Delta in China (2010–2018), this paper discusses the direct impact and spatial spillover effect of HSR on urban housing prices, using a spatial econometric model. The results show that improvements in the HSR services not only significantly increased urban housing prices but also had a positive spatial spillover effect. Morover, due to the space–time compression consequence of HSR, the extant "ripple effect" of housing prices has been further strengthened, and improvements in the service frequency of HSR has brought about a stronger spatial spillover effect on housing prices. This study fills a gap in previous spatial perspective research on the impact of HSR on urban housing prices and offers significant theoretical explanations and empirical evidence. Our research provides valuable inputs for the planning and implementing of stratgies aiming to promote urban development and create economic growth through HSR construction.

Did high speed rail accelerate the development of tourism economy? – Empirical analysis from Northeast China

This study investigates the impact of the Chinese high-speed rail (HSR) systems on its international tourism demand. A panel data set of 21 countries over the period 1997 to 2012 is analysed using dynamic panel modeling following the classical tourism demand model. The empirical examination confirms the overall impact of HSR is positive, but the small elasticity of HSR station on international tourism demand may imply the negligible influence of the large number of small HSR stations.

Improving energy efficiency is an important measure of environmental governance. At present, studies on the impact of high-speed rail on energy efficiency need to be further studied. This paper constructs panel data of 285 cities at prefecture-level and above in China from 2003 to 2017, and uses the difference-in-difference (DID) to study the impact of high-speed railway on urban energy efficiency. Based on the theories of "factor flow," "knowledge spillover," and "center-periphery," this paper discusses the influence mechanism and heterogeneity of high-speed railway on energy efficiency. The empirical results show that high-speed railway can significantly improve energy efficiency, and the conclusion is still valid after parallel trend test, propensity score matching and difference-in-difference (PSM-DID) test, and instrumental variable method. The results remained true after a series of robustness tests. Mechanism analysis shows that high-speed railway can improve energy efficiency by promoting industrial structure upgrading, technological innovation, and market integration. Analysis of heterogeneity shows that the promotion effect of high-speed railway on energy efficiency is greater in central and western cities and core cities. This study provides useful enlightenment for optimizing China's high-speed rail construction planning and seizing the opportunity of high-speed rail development to improve energy efficiency.

The impact of high-speed rail and low-cost carriers on European air passenger traffic

High Speed Rail (HSR) plays a significant role in economic urbanization and environmental impacts. India is also debating on the importance and impacts of HSR on climate. HSR is already operational in several countries today and a total of 12 HSR corridors are already planned in India, of which the construction of the Mumbai – Ahmedabad corridor is already underway. Even though there are several studies in literature in the context of various countries related to the impact of HSR on CO2 emissions, however such studies are very limited in Indian context. Keeping in mind that passenger travel is a major human activity contributing to CO2 emissions, the prime objective of this research is to study the impacts of HSR on CO2 emissions in Indian corridors. Hence a study of the Bengaluru – New Delhi corridor is taken. The hypothesis of the study is that introduction of HSR between Bengaluru – New Delhi will reduce CO2 emissions. Revealed Preference and Stated Preference survey was conducted using interview method for the purpose of data collection. Percentage shift of passengers from air travel to HSR was calculated. Thereafter the percentage reduction in CO2 emissions was calculated using emission factors from literature. It was found that there is a percentage reduction in CO2 emissions for all HSR options, and more so for the HSR option with night journey (with speed of 200 kmph) and moderate fare levels equivalent to the Rajdhani Express 2nd AC fares and that of a half day or night journey (with speed of 350 kmph) with fares equivalent to that of the Rajdhani 1st AC fare. The study suggests different possible options to introduce HSR in India that can reduce CO2 emissions from passenger travel and can help the Indian Government with some policy decision support.

This paper explores the relationship between high-speed rail (HSR) and industrial agglomeration within urban agglomerations. The paper selects the data of the Beijing–Tianjin–Hebei Urban Agglomeration (BJHUA) and Central Plains Urban Agglomeration (CPUA) from 2002 to 2016 as the research object. The time-varying difference-in-difference (TVDID) model is innovatively applied to analyze the impact of HSR on the agglomeration of secondary and tertiary industries in urban agglomerations, and the industrial agglomeration effects of the two urban agglomerations are compared. The results show that the influence of high-speed railways on the industrial agglomeration of urban agglomerations is heterogeneous. In the BJHUA, the impact of HSR on the agglomeration of secondary and tertiary industries is not particularly significant. On the other hand, in the CPUA, HSR does not have a significant impact on the agglomeration of secondary industry. However, it does have a significant negative effect on the agglomeration of tertiary industry. In addition, further analysis reveals significant variations in the impact of HSR on the agglomeration of industries within urban agglomerations after excluding the central cities. It is important to note that the impact of HSR on regional industries can be complex and multifaceted. The findings enrich the theoretical understanding of the relationship between HSR and industrial agglomeration.

There has been long and ongoing interest in the impacts of high-speed rail (HSR) on regional spatial development. Most existing studies, however, reported findings at relatively coarse geographic scales, i.e., at the prefecture-city or above level in the Chinese context. This paper presents the empirical evidence of HSR impacts from the county-level cities in China’s Mid-Yangtze River City-Cluster Region (MYRCCR). The study utilized rail time data and the socio-economic data for MYRCCR’s 185 county-level cities in the years of 2006 (without HSR) and 2014 (with HSR) and analyzed the impacts of HSR on inter-city travel times, accessibility, spatial inequality, and regional economic linkages among the MYRCCR cities. The results show that, from 2006 to 2014, HSR reduced city-to-city average travel time by 34.5% or 124 min and improved accessibility to all cities in the MYRCCR. HSR’s impacts on accessibility and spatial equality exhibited a scale-differentiated pattern. MYRCCR-wide, HSR transformed a pattern of spatial polarization towards the one of corridorization. Cities located on major HSR corridors became more balanced in 2014 than in 2006. Nevertheless, at the county-city level, the gap between cities with the most and the least accessibility gains was much greater than the gap between those with the largest and the smallest travel time savings. Attributable to HSR services, the intensity of economic linkage increased between MYRCCR cities, especially between the provincial capital cities and those on the major lines of the national HSR grid, which implies an emerging process towards territorial cohesion in MYRCCR. National, provincial, and local governments should consider transportation as well as non-transportation policies and measures to direct HSR impacts towards further enhanced spatial development and regional equality.

Transportation infrastructure is crucial for economic growth. Nonetheless, conclusions from empirical investigations concerning the impacts of high-speed rail (HSR) on regional economic growth exhibit inconsistency and are even controversial. In this work, we incorporate the HSR variable into the traditional Dixit–Stiglitz–Krugman (DSK) model, and establish both a structural equation model (SEM) and a threshold model to verify the nonlinear and volatile relationship between HSR development and regional economic growth. The main conclusions are as follows: The opening of HSR (HSR_O), the service intensity of HSR (HSR_S), and the time-cumulative effect of HSR (HSR_T) all have a positive impact on regional economic growth through market size, with labor and capital stock acting as moderating variables. Only under the condition that the regional capital stock exceeds 141.90 million yuan (US$20.56 million), 122.24 million yuan (US$17.71 million), and 128.70 million yuan (US$18.65 million), respectively, will HSR_O, HSR_S, and HSR_T have a favorable effect on regional economic growth. However, the varying influence on regional economic growth is minimally related to labor stock. Finally, directions for further research, and policy implications of the development of HSR for regional planners and local authorities are proposed.

The correlation between high-speed rail (HSR) and regional innovation is vital for studying the economic impacts of HSR. Using 2003–2018 panel data on prefecture-level cities in China’s Yangtze River Delta (YRD), this paper investigates the impact of HSR on regional innovation using a multiperiod difference-in-differences (DID) model. HSR operations have a significant positive impact on urban innovation, as supported by robustness tests. Heterogeneity analysis reveals a threshold effect of cognitive capital on the promoting effect of HSR on regional innovation that is maximized when cognitive capital capacity falls within the range of 0.1254 to 0.1876. Mechanism analysis suggests that HSR construction facilitates the cross-regional mobility of highly skilled individuals. This expanded movement increases innovation within cities due to the resulting knowledge spillovers. Moreover, HSR operations and civil aviation, as well as internet communication tools, play a significant complementary role in promoting regional innovation. This study deepens the understanding of the impact of HSR operations on regional innovation from the perspective of the interregional mobility of highly skilled people. Furthermore, ArcGIS is used to construct the ‘least cost path’ of the HSR network, providing a new approach to addressing the endogeneity of HSR station locations.

The impact of high-speed rail (HSR) on urban spatial structure has attracted much attention since the 1970s. It mainly realizes the change of urban spatial structure by affecting the spatial distribution of population and economy. Based on population and industry data on 29 cities in the Central Plains Urban Agglomeration (CPUA) located in central China during 2005–2017, in this paper difference-in-difference (DID) models are utilized to explore the influence of HSR on the spatial structure of prefecture-level cities at the single/multicenter levels according to the dimensions of polycentricity and dispersion. The main conclusions are shown as: (1) HSR on the spatial structure of the CPUA has a monocentric trend, but the characteristics of different prefecture-level cities vary. Currently, agglomeration remains the dominant force of the spatial structure of the CPUA in prefecture-level cities. (2) HSR have a noticeable effect on the spatial structure of industry, whereas the influences of the HSR on the spatial structure of the population are insignificant. Its development is the result of the combined effects of many factors, including natural factors, socioeconomic factors, policies, and transportation factors. Among the controlling factors, the administrative area, economic development level, urban population, and number of research units are the critical factors having a hold on the population spatial structure of the CPUA.

Impact of high-speed rail on regional economic disparity in China

As an important indicator for measuring the development level of low-carbon tourism, reducing the carbon emissions of tourism transportation has become an essential strategic goal and task for the sustainable development of tourism. Among many tourism vehicles, high-speed rails have a significant role in reducing the carbon emissions of tourism transportation. To clarify the impact of high-speed rails on the development efficiency of low-carbon tourism, using the relevant data of Zhengzhou urban agglomeration from 2010 to 2020, the DEA-BCC model and the Malmquist index method were used to measure these data. The results show the following: (1) the average comprehensive development efficiency of the Zhengzhou metropolitan high-speed rail for low-carbon tourism is low, and the comprehensive development efficiency of each city varies greatly; (2) the impact of high-speed rails on the development efficiency of low-carbon tourism in some underdeveloped areas is increasing. The impact on the development efficiency of low-carbon tourism in more developed areas is declining; (3) affected by COVID-19, tourism carbon emissions have shown a downward trend, reflecting the importance of low-carbon travel to low-carbon tourism to a certain extent. The research results not only verify the existing research conclusions but also verify the role of high-speed rails in the development of low-carbon tourism, and have practical value with respect to targeted guidance for the development of low-carbon tourism.

As an environmentally friendly means of transport, the high-speed rail (HSR) is conducive to promoting corporate performance. An innovative approach extends the impact of HSR networks on pollution emissions from the regional level to the micro-enterprise level. Based on the quasi-natural experiment of the opening of HSR, a difference-in-difference model is used to investigate the impact of HSR on enterprise pollution emission levels and its action mechanism by using the matched data from the Chinese Enterprise Pollution Emission Database, the Chinese Industrial Enterprise Database, and the Chinese City Statistical Yearbook from 2000 to 2010. The results show that opening HSR significantly reduces the enterprises' pollution emission level, while reducing the number of polluting enterprises and transportation costs as well as improving the innovation capacity of enterprises are the corresponding action mechanisms. The impact of HSR on the enterprises' pollution emission varies with industry intensity, population size, and regional economic development level. The conclusions not only provide important insights to increase the ecological quality of China's environment through transportation infrastructure upgrades but also bring some guidance to more developing countries to improve their air environment.

Are conventional train passengers underserved after entry of high-speed rail?-Evidence from Chinese intercity markets