Investigating high-speed rail construction's support to county level regional development in China: An eigenvector based spatial filtering panel data analysis

Yu, Danlin; Murakami, Daisuke; Zhang, Yaojun; Wu, Xiwei; Li, Ding; Wang, Xiaoxi; Li, Guangdong

doi:10.1016/j.trb.2019.12.006

Cited by 37 publications

(19 citation statements)

References 87 publications

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“…As an extension of the SLM and SEM, the SDM identifies sources of spatial dependence of SO 2 emissions as the combination of the spatially lagged SO 2 emissions and the spatially lagged driving factors (Shi et al, 2020). Despite their advantages in identifying sources of spatial dependence, the SLM, SEM and SDM are essentially global models describing a spatial equilibrium state, making them disadvantageous in capturing the local relationships between SO 2 emissions and driving factors (Xu and Lee, 2019;Yu et al, 2020).…”

Section: Approaches For Dealing With Spatial Dependencementioning

confidence: 99%

“…As proved by Murakami and Griffith (2015) and Murakami et al (2017), the RE-ESF approach without and with SNVC demonstrated advantages in overcoming multicollinearity, improving computational efficiency, and increasing estimation accuracy. Moreover, both the global and local relationships between dependent variable and independent variables can be captured simultaneously, making it more popular in empirical studies (Yu et al, 2020). Then, the RE-ESF approach is identified in this paper to investigate spatial heterogeneity and economic driving factors of SO 2 emissions in China.…”

Section: Approaches For Dealing With Spatial Dependencementioning

confidence: 99%

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Spatial heterogeneity and economic driving factors of SO2 emissions in China: Evidence from an eigenvector based spatial filtering approach

Shi

Chang

et al. 2021

Ecological Indicators

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Sulfur dioxide (SO 2 ) emissions have been a great challenge in China over the last few decades due to their serious impact on the environment and human health. In this paper, a random effect eigenvector spatial filtering (RE-ESF) approach without and with non-spatially varying coefficients (SNVC) is identified to examine spatial heterogeneity and economic driving factors of SO 2 emissions in China from 2011 to 2017. Using the Moran eigenvectors to extract information on spatial dependence, the main findings of the RE-ESF approach are as follows: First, after comparing different approaches for dealing with spatial dependence, it is found that the RE-ESF approach demonstrates the best fit to the dataset. Second, the global investigation shows that SO 2 emissions are negatively determined by economic growth and government expenditure for environment protection, but are positively determined by road freight transport, coal consumption and oil consumption. Third, the local investigation indicates that the spatially varying coefficients of economic growth and coal consumption range from 0.1401 to 0.2732 with the median value of 0.2478 and from 0.2406 to 0.3611 with the median value of 0.3210, respectively, revealing significant spatial heterogeneity of SO 2 emissions driven by economic growth and coal consumption. These findings provide meaningful insights into centralized and province-specific policies for reducing SO 2 emissions.

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Section: Approaches For Dealing With Spatial Dependencementioning

confidence: 99%

Section: Approaches For Dealing With Spatial Dependencementioning

confidence: 99%

Spatial heterogeneity and economic driving factors of SO2 emissions in China: Evidence from an eigenvector based spatial filtering approach

Shi

Chang

et al. 2021

Ecological Indicators

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“…4). так и национальной экономики в целом Yu et al, 2020) и привело к следующим результатам по состоянию на 2018 г.: страна обладает самой протяженной в мире сетью дорог (25,2 тыс. км), включающей 32 выделенных линии, охватывающих все города с населением более 0,5 млн чел., ежегодный объем перевозимых системой ВСМ пассажиров составил 1,75 млрд чел.…”

Section: таблица 3 крупнейшие морские контейнерные порты мираunclassified

On PRC Transport Sector

Bardal¹

2020

Spatial Economics

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Аннотация. В обзоре рассматриваются тенденции формирования основных параметров транспортного комплекса КНР с момента провозглашения государства до настоящего времени. Прослеживается связь развития пространственных характеристик автомобильных и железнодорожных сетей, объектов портовой инфраструктуры, масштабов работы отдельных видов транспорта (грузооборот, объем перевозимых грузов, среднее расстояние перевозки) с общими процессами развития экономики в определенных ключевых этапах. Представлено изменение показателей транспортной работы в грузовых и пассажирских перевозках. Выделены условия стремительного развития морской портовой инфраструктуры КНР в рамках реализации политики открытости и реформ, предполагающей формирование модели экономики, ориентированной на внешний спрос. Рассмотрено развитие систем высокоскоростного железнодорожного движения и воздушного транспорта, простимулированных ростом уровня жизни и ориентацией на стимулирование внутреннего спроса. Показано изменение роли транспортного комплекса КНР: от сервисного сегмента экономики к самостоятельному субъекту экономических процессов, генерирующему технологии, осуществляющему трансфер инноваций и участвующему в формировании новых экспортных ниш страны на мировом рынке. Представлена значимость транспортного комплекса как инструмента стабилизационной политики КНР в период экономических кризисов 2008 и 2015 гг. Инвестиции в транспортную инфраструктуру в периоды спада имели существенный мультипликативный эффект и позволили создать новые рабочие места, обеспечить спрос на продукцию смежных отраслей (металлургия, производство строительных материалов, транспортное машиностроение), снизить затраты грузоотправителей, совершенствовать развитие условий транспортировки, стимулировать внутренний спрос.

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“…Hence, many countries have been making great efforts to develop HSRs, such as those being planned under the Biden administration (Savidge 2021). The effects of regional rail investments is a longstanding topic of interest in the fields of regional/urban planning, real estate, housing, tourism, transportation, politics and economic geography because regional rail is a popular public investment used to promoting the economic agglomeration level of the regional economy, mobility of skilled labor-force, and the reduction of greenhouse gas emissions (Pagliara and Mauriello 2020;Shao, Tian, and Yang 2017;Yu et al 2020;Audikana 2021;Tian et al 2021). Researchers examine regional rail benefits from various perspectives, for example, a conventional perspective of investigating the effects is by comparing land or housing values along the rail corridor before and after the start of the rail service.…”

Section: Introductionmentioning

confidence: 99%

Modelling impacts of high-speed rail on urban interaction with social media in China’s mainland

Gong

et al. 2021

Geo-spatial Information Science

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High-Speed Rail (HSR) has increasingly become an important mode of inter-city transportation between large cities. Inter-city interaction facilitated by HSR tends to play a more prominent role in promoting urban and regional economic integration and development. Quantifying the impact of HSR's interaction on cities and people is therefore crucial for long-term urban and regional development planning and policy making. We develop an evaluation framework using toponym information from social media as a proxy to estimate the dynamics of such impact. This paper adopts two types of spatial information: toponyms from social media posts, and the geographical location information embedded in social media posts. The framework highlights the asymmetric nature of social interaction among cities, and proposes a series of metrics to quantify such impact from multiple perspectives -including interaction strength, spatial decay, and channel effect. The results show that HSRs not only greatly expand the uneven distribution of inter-city connections, but also significantly reshape the interactions that occur along HSR routes through the channel effect.

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Investigating high-speed rail construction's support to county level regional development in China: An eigenvector based spatial filtering panel data analysis

Cited by 37 publications

References 87 publications

Spatial heterogeneity and economic driving factors of SO2 emissions in China: Evidence from an eigenvector based spatial filtering approach

Spatial heterogeneity and economic driving factors of SO2 emissions in China: Evidence from an eigenvector based spatial filtering approach

On PRC Transport Sector

Modelling impacts of high-speed rail on urban interaction with social media in China’s mainland

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