Positive Spatial Spillover Effect Research Articles

The role of China's carbon emission trading system in economic decarbonization: Evidence from Chinese prefecture-level cities

Based on the panel data from 283 prefecture-level cities in China between 2009 and 2019, this study examines the impact of China's carbon emissions trading system on reducing carbon emissions and its mechanisms, using the PSM-DID method. The findings demonstrate that the carbon emissions trading system can effectively decrease the total carbon emissions in pilot cities in China, and has a positive spatial spillover effect on neighboring cities of the pilot areas. The carbon emission trading system primarily reduces carbon emission by incentivizing businesses to implement eco-friendly practices and improve the industrial structure of pilot cities. Increased financial marketisation can promote the carbon emission reduction effects of the trading system. The impact of the carbon emission trading system on old industrial base cities and inland cities is more significant than those on non-old industrial base cities and coastal cities.

Spatial effect of digital economy on the coordinated development of Port cities

Under the background of thriving digital economy and the digitization of port industry, using data derived from port cities in Guangdong, this study intends to investigate the spatial effect of digital economy on the port city coordination. This paper firstly measures the port city coupling coordination degrees and the digital economy comprehensive development levels, then estimates the spatial spill over effect of digital economy on the port city coordination by constructing the dynamic Spatial Durbin Model (SDM). To further clarify local patterns of the spatial effect, this paper subsequently analyses the spatial effects within and between three sub regions in Guangdong. The results show that first, the port city coordination has a habit persistence; second, the digital economy development may be mainly due to the local policy; third, the digital economy has a positive spatial spillover effect on the port city coordination, and the effect will increase over time; forth, the spatial effects in the Pearl River Delta and in the western and eastern areas present different patterns. The quantitative research enriches the port city theory under the new circumstances of digital economy, and brings new insights into regional integration and sustainable development.

The impact of urban green business environment on FDI quality and its driving mechanism: Evidence from China

The world's leading recipient of foreign direct investment (FDI), China should pay attention to both the volume and quality of FDI as it seeks to integrate more fully into globalization. At this stage of development, establishing an environmentally friendly business environment has become a critical strategy for improving the quality of FDI. So, this paper constructs the index system of the urban green business environment and the measurement of FDI quality to test the driving mechanism of the urban green business environment on FDI quality. The study draws the following conclusions. Firstly, the green business environment can significantly enhance FDI quality, and this impact exhibits a positive spatial spillover effect overall. However, regionally, only the eastern region demonstrates a positive spillover effect. Secondly, the mechanism test results reveal that public services, financial services, market environment, ecological environment, human resources, and legal environment are the key driving factors of the urban green business environment on FDI quality. Moreover, the intermediary effect test establishes that the urban green business environment enhances FDI quality by mitigating risks. Thirdly, the heterogeneity test results indicate that the green business environment can enhance FDI quality for cities with varying income and pollution levels. The research results provide a new perspective for improving FDI quality and optimizing the green business environment. They hold significant implications for enlightening the coordinated development of the urban green business environment and FDI quality in different regions, as well as for maximizing the influence of the green business environment on FDI quality.

The relationship between green space accessibility by multiple travel modes and housing prices: A case study of Beijing

Green space accessibility affects housing prices, which is an issue that has been underappreciated. This paper takes Beijing's central urban area as an example. First, the Gaussian-based two-step floating catchment area (G2SFCA) method is used to measure four levels (community green space, subdistrict green space, district green space, and municipal green space) of green space accessibility by multiple travel modes (walking, cycling and driving). Second, the spatial error model (SEM) is used to examine the factors influencing housing prices. Finally, the geographically weighted regression (GWR) model is introduced to explore the spatial relationship between green space accessibility by walking, cycling and driving and housing prices. The results show the following: (1) The SEM shows that only driving accessibility has a positive spatial spillover effect on housing prices, indicating that the spatial inequity of local community green spaces by driving will exacerbate surrounding spatial inequity. (2) The GWR model shows that from the perspective of walking and driving accessibility, most areas within the Second Ring Road show spatial equity in green spaces, while cycling accessibility shows that the spatial inequity of green space exists only outside the Second Ring Road. (3) We find that municipal green space and subdistrict green space most affect the spatial equity of green spaces. Community green space, which is not open to the public, plays a minimal role. Regarding walking and driving accessibility, municipal green space increases the spatial equity of green spaces. In contrast, this type of green space can promote the spatial equity of green spaces regarding cycling accessibility. This study can significantly improve the quality of urban settlements in the Global South and has important implications for policy-makers, planners, and stakeholders in other large cities worldwide to create green and liveable cities.

Study of the space–time transition and spatial spillover effects of tourism green production efficiency in the Yangtze River Delta—a reanalysis from the perspective of tourism carbon sinks

Tourism green production efficiency serves as the foundation for assessing the mutual coupling performance of the tourism economy and the ecological environment. In this paper, the tourism carbon sink is included in the measurement framework, and the TGPE of 41 cities in the Yangtze River Delta region from 2011 to 2019 is estimated by the Super-SBM model. Furthermore, kernel density estimate, spatial autocorrelation, Markov chain and spatial Durbin model are further integrated to explore its spatio-temporal evolution process, spatial effects and influencing factors. The results show that 1) TGPE in the Yangtze River Delta has been increasing during the study period. The high-efficiency and low-efficiency areas of the TGPE have a bipolar pattern characterized by “low–low convergence” and “high–high convergence.” 2) There is considerable spatial variation in TGPE from north to south. The number of hot spots and sub-hot spots increases in volatility, whereas the number of sub-cold spots and cold spots decreases. 3) Although cities with low levels of TGPE have a higher probability of moving to the next level, grade transformation across hierarchies is difficult to attain. When considering the factor of adjacent types and the influence of spatial lag on the transfer probability. 4) The positive spatial spillover effects of TGPE is significant. At the same time, economic development level, transport accessibility and tourism industry agglomeration have positive spillover effects on neighboring cities. Conversely, urbanization level and openness level have negative spillover effects.

The carbon emission reduction effect of digital infrastructure development: Evidence from the broadband China policy

Digital technologies are a key driver of carbon peaking and carbon neutrality. However, as the physical foundation supporting digital technology, how digital infrastructure affects carbon emissions is unclear. Based on the panel data from 2008 to 2019, this paper examines the impact of the Broadband China Policy on carbon emissions by adopting a multi-period difference-in-differences (DID) method. The empirical findings indicate that, first, digital infrastructure development plays a significant role in reducing carbon emissions in China. Second, the Broadband China Policy significantly reduces carbon emissions especially in China's low-carbon emission regions, high-level digitization regions, and non-resource-cursed regions. Third, the implementation of the Broadband China Policy facilitates carbon emissions reduction through the promotion of green technology progress, optimization of industrial structures, green transformation of residents' lifestyles, and electrification of energy mix. Finally, the Broadband China Policy has a positive spatial spillover effect on the carbon intensity in the surrounding regions of pilot cities, but it has no significant effect on the total carbon emissions and per capita carbon emissions in the surrounding regions. The results provide important insights for digital infrastructure construction to achieve a win-win situation for economic development and emission reduction.

Facilitating or inhibiting? Spatial effects of the digital economy affecting urban green technology innovation

As a new engine for driving high-quality economic development, the rapid development of the digital economy may become the key to stimulating green technology innovation within Chinese urban areas. Based on the panel data of 286 Chinese cities from 2011 to 2019, this study utilizes the spatial Durbin model to decompose the spatial effect of the digital economy on urban green technology innovation. The results show that: (1) The digital economy has a significant role in promoting green technology innovation in Chinese cities and manifests positive spatial spillover effects. (2) Mechanism analysis indicates that the digital economy mainly affects urban green technology innovation through three paths: human capital, financial development, and government support. The magnitude of its role reveals obvious nonlinear effects with an increase in the size of mechanism variables. (3) Heterogeneity analysis demonstrates that the digital economy in eastern cities illustrates a notable spillover effect, while city clusters present a U-shaped impact feature, that is, the “empowerment effect” on green technology innovation in neighboring areas can only be displayed when the digital economy develops to a certain level. The findings offer a more valuable reference for making decisions to enhance comprehension of the spatial effects of the digital economy development and realize the synergistic development of digitalization and greenization among cities.

The green economic impact of a green comprehensive industry agglomeration: An example from the sports industry

The optimization of industrial structure and layout is essential for promoting the high-quality development of the regional economy. As a typical example of a green comprehensive industry, the agglomerations of the sports industry have the potential to release additional green benefits. Consequently, this paper uses the balanced panel data of 30 provinces, municipalities, and autonomous regions in China from 1998 to 2021 as samples and, based on the strategic background of China's dual-carbon target and the re-interpretation of the green economy, uses the Super-SBM model to re-measure the green economic efficiency of each region and applies the dynamic spatial Durbin model and the dynamic panel system GMM model to evaluate the direct effect, mediating mechanism, spatial spillover effect, and heterogeneity effect of sports industry agglomeration on the regional green economic efficiency. Empirical findings indicate that: (1) The improvement of green economic efficiency under China's dual-carbon target has the characteristics of dynamic accumulation, and there is a siphon effect between neighboring regions. (2) The effects of sports industry agglomeration on local green economy efficiency show an "inverted U-shape" with a positive spatial spillover effect on the green economy efficiency of neighboring regions; this conclusion is robust. (3) The green economy effect of sports industry agglomeration is more significant in the central and western regions, regions with strict environmental regulations, and regions with a higher willingness for resident participation in sports due to industrial density, compliance costs, and characteristics of sports industry development. (4) Sports industry agglomeration can promote regional green economy efficiency by escaping natural resource dependence and increasing healthy human capital; technological innovation, rationalization of industrial structure, and labor transfer serve as "inverted U-shaped" mediators between sports industry agglomeration and regional green economy efficiency. This study expands the meso- and spatial-level perspectives of the impact of the agglomeration of green industries and comprehensive industries on green development. It is of great theoretical and practical importance for promoting the construction of a regional green industrial system and the high-quality development of the green economy.

How FinTech affects total factor energy efficiency? Evidence from Chinese cities

The advancement of Financial Technology (FinTech) is crucial for government entities, the National Grid, and various energy corporations to facilitate the transition towards sustainable and green production methods. This study investigates the relationship between FinTech and Total Factor Energy Efficiency (TFEE) using data from a selected sample of 254 city groups in China. We examine how the development of FinTech impacts TFEE from both non-spatial and spatial perspectives. The results from the non-spatial panel model indicate that FinTech development has a significant positive impact on TFEE. Comparative studies were conducted using fixed effects (FE), feasible generalized least squares (FGLS) models, and system generalized method of moments (GMM) models, and the main findings remained consistent, confirming the robustness of our conclusions. Spatial autocorrelation results reveal a significant positive spatial spillover effect on TFEE. Both the spatial Durbin model and the dynamic spatial Durbin model demonstrate that FinTech also has a significant positive impact on TFEE, and this effect increases over time. These conclusions remain robust even after considering various spatial weight matrices and alternative methods for calculating TFEE. Additionally, we discovered that the digital economy plays a vital role in strengthening the relationship between FinTech and TFEE. Heterogeneity analysis indicates that, compared to cities without resource-based economies, FinTech development in growing resource-based cities has a more substantial impact on TFEE.

Measurement and characteristics of the temporal-spatial evolution of China’s healthcare services efficiency

BackgroundHealthcare services efficiency (HSE) is directly related to the healthcare demands of the general public and also plays an essential role in the country’s coordinated economic and social development.MethodsIn this study, the stochastic frontier approach (SFA)-Malmquist model was applied to measure the HSE of 31 Chinese provinces based on panel data from 2010–2020. Then, kernel density estimation, Markov chain, and exploratory spatial data analysis were adopted to study the temporal-spatial dynamic evolution characteristics of the HSE.ResultsThe study found that China’s HSE showed an average value of approximately 0.841, indicating room for improvement. The HSE varied significantly across regions, presenting an “East > Central > West” distribution layout. The TFP of healthcare services in China grew by 1.6% per year, driven mainly by technological progress of 1.8% per year. The trend of the HSE shifting to a high level in China was significant, but its evolution exhibited stability of maintaining the original state, and it was harder to achieve leapfrog transfer. The temporal-spatial evolution of the HSE was also significantly affected by geospatial factors, with a clear spatial spillover effect and spatial agglomeration characteristics. Provinces with high-level HSE exhibited positive spatial spillover effects, while provinces with low-level HSE had negative spatial spillover effects. Thus, the “club convergence” phenomenon of “high efficiency concentration, low efficiency agglomeration, high levels of radiation, and low levels of suppression” was formed in the spatial distribution.ConclusionsThe results indicate that countermeasures should be taken to improve the HSE in China. Theoretical support for the improvement of HSE is provided in this paper.

The impact of transportation and information infrastructure on urban productivity: Evidence from 256 cities in China

Improving total factor productivity is an important driving force for achieving high-quality economic development. Based on the panel data of 256 cities in China from 2009 to 2019, this paper investigates the effect of transportation and information infrastructure on urban productivity. The results show that transportation and information infrastructure promote urban productivity, and the effect in eastern regions and megacities is more obvious. The mechanism analysis shows that transportation infrastructure enhances urban productivity by promoting economic agglomeration, and information infrastructure enhances urban productivity by promoting labor mobility, economic agglomeration, financial agglomeration and industrial agglomeration. The spatial spillover effect shows positive spatial autocorrelation of urban productivity. Transportation and information infrastructure have significant positive spatial spillover effects on urban productivity. China should continue to promote the construction of transportation infrastructure, strengthen investment in information infrastructure, and promote the joint construction, sharing, coordination and integration of transportation and information infrastructure.

Path mechanism and spatial spillover effect of green technology innovation on agricultural CO2 emission intensity: A case study in Jiangsu Province, China

Green technology innovation (GTI) is one of the most important factors influencing agricultural carbon emission intensity (ACEI). Various studies have explored the impact of GTI on ACEI, but the path mechanism has not been fully explained. This study incorporates GTI and ACEI into the constant elasticity of substitution (CES) production function and constructs a theoretical model to analyse their direct impact mechanisms. Drawing on the substitution effect theory and the Marshall–Arrow–Romer (MAR) externalities theory, this study introduces two regulatory mechanisms: optimization of energy structure and agricultural industry agglomeration (AIG). Additionally, it explores the pathway mechanisms under the influence of spatial spillover effects based on Tobler’s first law of geography. Then, taking Jiangsu Province in China as a case study, empirical tests are conducted using LSDVC and dynamic spatial SAR models. The results are as follows. (1) GTI effectively inhibits ACEI directly, and has significantly positive spatial spillover effects on ACEI reduction in the short and long terms. (2) Energy structure optimization positively regulates the effect of GTI on ACEI reduction, and energy structure optimization in nearby cities may help GTI restrain ACEI in the local city in the short term. (3) AIG has a positive regulating effect on GTI reducing ACEI, and the moderating effect of AIG has positive spillover effects in the short term. (4) When both regulatory pathways are employed simultaneously, the moderating effect of AIG in local or neighbouring areas is expected to become ineffective. These findings are useful for solving the problem of ACEI reduction by managing the transfer and distribution of GTI between different regions, considering spatial spillover and moderating effects.

The impact of environmental tournament on CO2 emissions from the perspective of synergizing the reduction of pollution and carbon emissions

Synergizing the reduction of pollution and carbon emissions is the essential way for the construction of ecological civilization in the new era. Based on the panel data of 278 Chinese cities from 2006 to 2020, we study the effect of environmental tournament on carbon dioxide (CO2) emissions. The results show that environmental tournaments have both effectiveness and limitations. The effectiveness is reflected in the fact that the environmental tournament is beneficial for the reduction of the pollution and CO2 emissions, and possesses a long-term effect. Green technology innovation, official promotion and foreign investment are identified as the main channels of influence. Moreover, the carbon reduction of the environmental tournament involves a positive spatial spillover effect, which means that the CO2 reduction can be radiated to the neighboring areas. However, environmental tournaments also have limitations. The results of the environmental tournament in the last year could bring pressure on cities to reduce pollution in the current year. The present study reveals a positive U-shaped relationship between the pollution reduction pressure and CO2 emissions. The pressure is beneficial to CO2 emissions reduction as the pollution reduction pressure is less than the extreme point; otherwise, CO2 emissions increase. The government's environmental attention strengthens the internal motivation of local participation in the environmental championship through policy orientation, and alleviates the negative impact caused by the limited nature of the environmental championship. The results of this study provide new ideas for improving China's environmental governance policy system and improving the governance efficiency of local governments.

Nonlinear impact and spatial effect of tourism urbanization on human settlement environment: Evidence from the Yellow River Basin, China

The human settlement environment is the concrete embodiment of measuring the sustainable development of tourism urbanization. Previous studies have preliminarily verified that there is a coupling relationship between tourism urbanization and human settlement environment. However, whether tourism urbanization can effectively improve human settlement environment, especially in the most vulnerable watershed area in China, the Yellow River Basin, is still unclear. Therefore, the purpose of this study is to explore the degree and direction of the impact of tourism urbanization on human settlement environment in 78 prefecture-level cities in the Yellow River Basin from 2005 to 2019 under the influence of nonlinear and spatial spillover effects. This paper uses the PSTR (panel smooth transition regression) model SDM (spatial Durbin) model to reveal the following results: First, tourism urbanization can significantly improve human settlement environment in the Yellow River Basin. After crossing the second threshold (0.434), the nonlinear effect of tourism urbanization on human settlement environment is the strongest, but only a very small number of cities cross the threshold. Secondly, the improvement of the level of tourism urbanization has effectively improved production environment and living environment of the region, but it has had a significant negative impact on ecological environment of the region. Finally, the combined effect of regional geographical proximity and economic interaction is conducive to the positive spatial spillover effect of tourism urbanization on production environment and living environment of surrounding areas of the Yellow River Basin. The current empirical results reveal the key role of tourism urbanization in improving human settlement environment in the Yellow River Basin, and clearly outline that the development of tourism urbanization should be consistent with the national strategy of ecological protection and high-quality development in the Yellow River Basin.

How Can the Digital Economy Promote the Integration of Rural Industries—Taking China as an Example

The rapid development of China’s digital economy has promoted the digital transformation of Chinese society and become a new driving force for China’s social development. Furthermore, increasing farmers’ income is the central task of China’s “three rural issues” project, and the integrated development of primary, secondary, and tertiary rural industries is an important way to revitalize rural industries and broaden farmers’ income channels, so it is very important to promote the integrated development of rural industries. In the context of the rapid development of China’s digital economy, it is of great significance to study how the digital economy promotes the integration of rural industries. Therefore, this study analyzed how China’s digital economy promotes the integration of rural industries by using the panel data and regression models of 30 provinces (municipalities and districts) in China from 2011 to 2021. The results show that (1) there is a significant positive relationship between the development level of the digital economy and the level of rural–industrial integration and that the development of the digital economy promotes the process of rural–industrial integration; (2) intermediary effect analysis shows that as the digital economy promotes rural–industrial integration, scientific and technological innovation levels and rural human capital are important intermediary channels; and (3) spatial analysis shows that the development of the digital economy can not only promote the integration of rural industries in the province but also have a positive spatial spillover effect on neighboring provinces. Therefore, it is necessary to create a good atmosphere for the development of the digital economy, constantly promote the development of the digital economy, pay attention to scientific and technological innovation and rural talent training, and promote the integration and coordinated development of the digital economy and rural industries between regions in order to improve the level of rural–industrial integration and contribute to the rural revitalization strategy.

The green innovation effect of urban energy saving construction: A quasi-natural experiment from new energy demonstration city policy

Energy-saving construction has promoted the sustainable development of cities and is an important measure to achieve carbon neutrality and peak carbon. This paper uses the synthetic control method(SCM), propensity score matching difference-in-difference model(PSM-DID), spatial Durbin difference-in-difference model (SDM-DID) and other methods to explore the policy effect of energy-saving policy on the green innovation efficiency of Chinese cities based on the New Energy Demonstration City(NEDC) policy as a quasi-natural experiment. The paper has found that establishing NEDC can significantly improve the green innovation efficiency of pilot cities, and its positive impact continues to increase over time. The effect of energy-saving policy has regional heterogeneity, and NEDC can promote the improvement of urban green innovation efficiency more in eastern and central China. The results of PSM-DID further verify the robustness of the previous conclusion. The results of SDM-DID show that NEDC has a positive spatial spillover effect on the improvement of urban green innovation efficiency. NEDC policy can effectively promote the improvement of green innovation efficiency in neighboring cities of pilot cities. Mechanism analysis shows that NEDC affects urban green innovation efficiency by optimizing industrial structure, reducing resource dependence and gathering innovative elements. This paper enriches the research on the effect of urban energy-saving policies and provides policy references for improving urban green innovation capabilities.

How does green fiscal expenditure promote green total factor energy efficiency? — Evidence from Chinese 254 cities

This paper explores how green fiscal expenditure affects Green Total Factor Energy Efficiency (GTFEE) from both non-spatial and spatial perspectives based on selected panel data of 254 cities in China. The results of the non-spatial panel model indicate that green fiscal expenditure has a significant positive impact on GTFEE. A comparative study of different econometric models shows that the main parts of the results are largely consistent, which indicates that the conclusions are robust. The spatial autocorrelation findings indicate a statistically significant presence of positive spatial spillover effects in the GTFEE of Chinese cities. Spatial Durbin Model (SDM) and Dynamic Spatial Durbin Model (DSDM) indicate that green fiscal expenditure has a similarly significant positive effect on GTFEE, which will increase over time. This paper considers different spatial weight matrices and changing measures to measure GTFEE, and the conclusions remain robust. Furthermore, industrial structure upgrading, and digital economy are vital in strengthening the relationship between local governments' green fiscal expenditure and GTFEE. According to heterogeneity analysis, green fiscal expenditure has a more significant effect on the GTFEE in mature resource-based cities and non-resource-based cities.

How do R&D capital market distortions affect innovation efficiency in China? Some evidence about spatial interaction and spillover effects

Improving innovation efficiency (IE) and refining capital market distortions are important considerations for promoting national innovation strategies. This study uses the dynamic spatial Durbin model and mechanism tests to explore the direct impacts, spatial effects, and influencing mechanisms of R&D capital market distortions on IE based on Chinese provincial panel data from 2009 to 2019. The main results can be summarized as follows. First, China’s IE is characterized by temporal inertia and spatial agglomeration. In both the spatial and temporal dimensions, IE in neighboring areas in the previous period can inhibit local IE in the current period. Second, R&D capital market distortions have a weakening effect on IE in the short- and long-term. Third, R&D capital market distortions have significant spatial interaction and persistent positive spatial spillover effects on IE. Finally, R&D capital mismatch and technology lock-in effects are essential mechanisms related to R&D capital market distortions that can inhibit IE. Based on these results, policy recommendations have been proposed to improve IE.

Smart city construction and urban green development: empirical evidence from China

Smart city construction represents an advanced stage of China's urbanisation process and plays an important role in promoting green economic growth and sustainable development. Propensity score matching is combined with the difference-in-difference method to analyse the data of 221 prefecture-level cities in China from 2006 to 2020 to assess the impact of smart city construction on urban green development. We found that smart city construction can significantly contribute to urban green development; this contribution has long-term benefits. Further analysis shows that smart city construction promotes urban green development via industrial structure and green technology innovation and that smart city construction has a significant positive spatial spillover effect, i.e., it promotes urban green development locally while significantly contributing to urban green development in neighbouring regions.

Can digital economy improve tourism economic resilience? Evidence from China

The digital economy has become an important driver of resilient growth in tourism economy. Taking China as the research object, it is found that the digital economy not only has a positive spatial spillover effect on tourism economic resilience but also mitigates the negative impact of the COVID-19 pandemic. The heterogeneity test shows that the digital economy has a spatial diffusion effect on tourism economic resilience in the eastern, western, and southern regions and a spatial siphoning effect on the non-pilot areas of the National Smart Tourism Pilot Policy. The result of influence mechanism test proves that the digital economy can contribute to the tourism economic resilience by stimulating tourism fiscal expenditure, guiding tourism industry cluster, and increasing tourism consumption. The findings of the study have important policy implications for China and other countries around the world in using the digital economy to promote sustainable tourism development.