Significant Spatial Spillover Effect Research Articles

Aggravating or alleviating? Smart city construction and urban inequality in China

A series of studies have been conducted in recent years to address the academic and policy debate on smart cities, some of which argue that the adoption of smart technologies to manage cities can exacerbate inequalities in urban development by favoring the classes that benefit from this model. However, to date, the links between smart cities and urban inequality (UI) has never been empirically tested at the city level of statistical inference. Therefore, with a combination of the difference-in-difference (DID) model and heterogeneity-robustness estimate, a quasi-natural experiment concerned with China’s smart city policy was carried out. The following are the primary conclusions: First, smart city construction alleviates urban inequality. Following several robustness tests, the finding is still reliable. Second, the effect of smart city construction on inequality is heterogeneous. Third, there is a significant positive spatial spillover effect of the impact of smart city construction on inequality. Therefore, it is suggested to formulate targeted smart city development strategies from the following aspects: strengthening the overall planning and strategic layout of smart city projects, focusing on social equity and protecting the interests of vulnerable groups, improving regional cooperation mechanisms, attracting and cultivating innovative talents, giving priority to the impact of heterogeneous cities, and emphasizing the participation and autonomy of grassroots communities, so as to tap the potential of digital technology in sustainable cities and societies.

Research on the impact of digital economy on green total factor productivity: theoretical mechanism and multidimensional empirical analysis

The digital economy (DE) is emerging as a crucial driver of economic growth and an effective tool for alleviating resource and environmental pressures, thereby evolving into a significant force in facilitating green transformation. This study elaborates on the theoretical mechanism of the impact of DE on green total factor productivity (GTFP), and conducts multidimensional empirical tests using panel data from 284 cities in China. The main findings are as follows: (1) DE exerts significant positive direct, indirect, and spatial spillover effects on GTFP, signifying its growing role as a robust driver of GTFP. Notably, technological innovation emerges as a key mediator of DE’s impact on GTFP. (2) The impact of DE on GTFP exhibits a distinct pattern: initially pronounced, gradually diminishing, and then rebounding as DE progresses. (3) DE tends to exacerbate, rather than alleviate, the development divide and resource curse, especially in underdeveloped and resource-rich cities where its benefits are constrained. (4) Government behavior is pivotal in influencing DE’s impact on GTFP. Supportive policies and strict environmental regulations are critical in harnessing DE’s positive contributions to GTFP. This study lays a scientific foundation for leveraging the “green attributes” of DE and offers insights into bridging the developmental disparities among cities.

Can the Establishment of National Parks Promote the Coordinated Development of Land, the Environment, and Residents’ Livelihoods?

National parks play a crucial role in the worldwide system of natural conservation, significantly influencing land utilization, the sustainability of local livelihoods, and the environmental integrity of nearby regions. In this study, the coupled coordination model and ArcGIS tools are applied to examine the temporal and spatial progression of the coordination of the system of land, the environment, and residents’ livelihoods (the LEL system). The construction of the LEL system and the use of natural geographic and socio-economic data are the main innovations of this research. The findings indicate that over the last 15 years, Wuyishan National Park has witnessed growth in its ecological and agricultural areas alongside a decline in its water-based ecological zones. The creation of the national park has obviously promoted the coordination of the LEL systems in nearby areas and has a significant spatial spillover effect. Consequently, for the upcoming development of Wuyishan National Park, it is crucial to modify the framework of the agricultural sector, enhance local public infrastructure, and bolster the safeguarding of water ecological areas.

Elucidating transport dynamics and regional division of PM2.5 and O3 in China using an advanced network model

Air pollution exhibits significant spatial spillover effects, complicating and challenging regional governance models. This study innovatively applied and optimized a statistics-based complex network method in atmospheric environmental field. The methodology was enhanced through improvements in edge weighting and threshold calculations, leading to the development of an advanced pollutant transport network model. This model integrates pollution, meteorological, and geographical data, thereby comprehensively revealing the dynamic characteristics of PM2.5 and O3 transport among various cities in China. Research findings indicated that, throughout the year, the O3 transport network surpassed the PM2.5 network in edge count, average degree, and average weighted degree, showcasing a higher network density, broader city connections, and greater transmission strength. Particularly during the warm period, these characteristics of the O3 network were more pronounced, showcasing significant transport potential. Furthermore, the model successfully identified key influential cities in different periods; it also provided detailed descriptions of the interprovincial spillover flux and pathways of PM2.5 and O3 across various time scales. It pinpointed major pollution spillover and receiving provinces, with primary spillover pathways concentrated in crucial areas such as the Beijing-Tianjin-Hebei (BTH) region and its surrounding areas, the Yangtze River Delta, and the Fen-Wei Plain. Building on this, the model divided the O3, PM2.5, and synergistic pollution transmission regions in China into 6, 7, and 8 zones, respectively, based on network weights and the Girvan Newman (GN) algorithm. Such division offers novel perspectives and strategies for regional joint prevention and control. The validity of the model was further corroborated by source analysis results from the WRF-CAMx model in the BTH area. Overall, this research provides valuable insights for local and regional atmospheric pollution control strategies. Additionally, it offers a robust analytical tool for research in the field of atmospheric pollution.

Impact of agricultural digitalization on carbon emission intensity of planting industry: Evidence from China

Studying the impact of agricultural digitalization (ADT) on the carbon emission intensity of planting industry (PCI) can help promote sustainable development and realize the “dual carbon” goal. Based on the panel data of 31 provinces in China from 2010 to 2020, this study uses the entropy weight method and emission coefficient method to measure the development level of ADT and PCI, respectively. By using the regression analysis method, as well as the robustness test, heterogeneity test, and spatial spillover effect and threshold tests, the impact of ADT on PCI was examined. The results are as follow: (1) PCI is high in the north and low in the south, and the north-south divide is becoming prominent. (2) ADT in China can significantly reduce PCI, as verified through the robustness test. (3) Regional differences exist in the impact of ADT on PCI, with the most significant effect observed in the northeast region, followed by the western and central regions. (4) ADT exerts a significant spatial spillover effect on PCI and an inhibitory effect on PCI of adjacent provinces. (5) The proportion of urban population exerts a threshold effect in the impact of ADT on PCI. When the urban population ratio crosses 69 %, the inhibitory effect of agricultural carbon emissions decreases marginally. Therefore, promoting the green and low-carbon development of the planting industry is highly recommended.

Spatial Effects of Economic Modernization on Carbon Balance in China

Exploring the impact of economic modernization on carbon balance is an essential endeavor to achieve carbon neutrality and combat climate change. However, the spatial impact of economic modernization on carbon balance remains ambiguous. Therefore, this study aims to explore the spatial spillover effects of agricultural modernization, industrialization, and urbanization on carbon balance during the economic modernization process in China, taking 30 provinces and cities in China as examples from 2010 to 2021. This study utilizes the spatial Durbin model to derive the following results: In the past decade, the carbon balance ratio has shown a fluctuating and decreasing dynamic evolution trend. There is an increase in regions with serious carbon deficits. Further investigation into the spatial spillover effect of carbon balance unveils that for every 1% increase in the carbon balance ratio of a province, neighboring provinces experience a decrease of 0.833%. Additionally, the spatial spillover effects of the three modernizations in China on the carbon balance ratio behave differently. Agricultural modernization and urbanization demonstrate negative spatial spillover effects on the carbon balance in neighboring regions, while industrialization exerts a significant positive spatial spillover effect on the carbon balance of neighboring regions. Regarding control variables, the level of innovation solely contributes to local carbon balance realization without generating a trickle-down effect, whereas infrastructure development operates inversely. At the same time, there are differences in the spatial effects of agricultural modernization and industrialization on the carbon balance between the eastern region and the central and western regions. The study underscores the importance of economic modernization and development processes focusing on fostering synergistic growth between economic and environmental benefits within both local and neighboring areas.

Spatial spillover effects of conversion of new and old driving forces on high-quality development: Evidence from 283 cities in China

Converting the forces driving is essential for breaking away from the traditional unsustainable development model and achieving High-Quality Development (HQD). Understanding how the conversion from old to new forces influences HQD is crucial for achieving sustainable development. Therefore, the assessment framework for Conversion of New and Old Driving Forces (CNODF) and HQD are established. From an efficiency perspective, the Super-Efficiency slacks-based model (SBM) model, considering undesirable outputs, is used to measure HQD levels in Chinese cities. The entropy weight method is applied to measure CNODF levels. By integrating coupling coordination degree and relative development degree, the matching and synchronization between HQD and CNODF are categorized. Further, the study introduces the Spatial Durbin Model to quantitatively identify the spatial relationships between HQD and CNODF at both national and urban agglomerations scales. The research findings indicate that from 2006 to 2019, the national average HQD level increased by 50.5 %, and the average CNODF level increased by 11.5 %. The association between the two has strong spatial heterogeneity. At the national scale, CNODF has significant nonlinear spatial spillover effects on HQD. These findings provide theoretical insights for advancing the conversion of driving forces, and can help inform regional high-quality development strategies.

Impact of green finance on carbon emissions and spatial spillover effects: Empirical evidence from China

Green finance is a financial innovation that directs capital allocation towards green industries. How will this affect regional carbon emissions? Based on the data on green finance and carbon emissions of 30 provinces in China from 2008 to 2019, this paper employs a multivariate linear regression model and a spatial econometric model to empirically study the impact of green finance on carbon emissions. The results find that (1) green finance significantly reduces provincial carbon emissions, specifically through promoting a cleaner energy structure and an advanced industrial structure, as well as improving the quality of green innovation. (2) Heterogeneity exists between regions. In eastern regions and areas characterized by high levels of marketization and minimal fiscal pressure, the role of green finance in promoting provincial carbon emission reduction is more pronounced. (3) Spatial econometric analysis found that green finance has a significant spatial spillover effect on carbon reduction in adjacent regions. Specifically, the flow of green resources and green ideas between provinces facilitates the formation of regional radiation, while green competition generates a siphon effect on neighboring regions. These findings provide some meaningful policy implications to achieve China's dual-carbon goal by promoting green finance.

The effects of tourism on economic growth targets achievement

ABSTRACT Exploring the impact of tourism on economic growth targets achievement (EGTA) can not only effectively combine the tourism-induced economic growth hypothesis with political promotion tournament theory but also help guide the economic decisions of local officials. Based on panel data from 277 cities in China, this paper examines the impact of tourism on EGTA. The results show that tourism revenue is not favourable to EGTA, but tourist arrivals are. The significant effect of tourism on EGTA is only found in eastern China. Tourism in cities not driven by tourism often fails to stimulate EGTA. In regions with higher levels of economy and technological innovation, tourism has a greater positive impact on EGTA, but fixed asset investment amplifies tourism’s negative impact on EGTA. In addition, tourist arrivals have a significant spatial spillover effect on EGTA. This paper reveals the theoretical mechanism of tourism-induced EGTA and is also an important attempt to integrate the political promotion tournament theory with the tourism-induced economic growth hypothesis.

Popularization of plant protection UAVs and farmers’ income increases: a quasinatural experiment

ABSTRACT The long-term stability of a developing country hinges on the imperative to increase farmers’ incomes. Based on county-level data from China from 2009 to 2019, we use the implementation of a pilot policy that subsidizes plant protection unmanned aerial vehicles (UAVs) as a quasinatural experiment to examine the impact of popularizing plant protection UAVs on farmers’ incomes. The results show that the popularization of plant protection UAVs may significantly increase farmers’ incomes via mechanisms that include not only labor transfer and agricultural productivity improvements but also unique mechanisms related to green agricultural development. The marginal income-increasing effect of the popularization of plant protection UAVs is higher in counties with farmers with high incomes, in major grain-producing areas and in areas with plains. In addition, the popularization of plant protection UAVs has a significant positive spatial spillover effect on farmers’ incomes in neighboring counties. We provide not only an empirical reference for the popularization of plant protection UAVs in China but also new ideas for compensating for the shortcomings of China’s agricultural mechanization and realizing the strategy of increasing farmers’ incomes and rural revitalization. More importantly, we provide Chinese wisdom for promoting agricultural development and farmers’ incomes in other developing countries.

The impact of high-speed railway construction on regional economic development in Hubei Province

Based on the panel data of 16 cities in Hubei Province from 2009 to 2019 (excluding the data during Covid-19 pandemic period), we construct multi-temporal difference-in-differences model (DID) and Spatial Durbin model (SDM) to explore the impact of the High-speed Railway (HSR) construction on the regional economic development in terms of direct economic effect, indirect economic effect and spatial spillover effect. The main conclusions of this paper are as follows: firstly, HSR construction promotes the economic development of cities in Hubei Province in a long time and in a large spatial scope. And the impacts on the economic development are significantly heterogeneous among different types of cities. Also, HSR construction has widened the economic development gap among cities to some extent. Secondly, the upgrading of an industrial structure and the improvement of urbanization level both play mediating roles in the economic impact of HSR construction. Thirdly, the HSR construction has significant spatial spillover effect on economic development, but the spillover effect becomes insignificant with the increase of distance.

Evaluation the impact of electricity consumption on China's air pollution at the provincial level.

As the world's largest electricity-consuming country, China faces the challenge of energy conservation and environmental pollution. Therefore, it is imperative that China takes decisive action to address these issues. Based on the panel data of 30 provinces (cities, districts) in China from 2011 to 2020, we use the entropy method to measure the air pollution index in different provinces, construct two fixed effects models, panel quantile model, and spatial Durbin model to empirically analyze the impact of electricity consumption on air pollution in China's provincial regions. The experimental results show that: (1) Electricity consumption has a significant positive impact on the provincial air pollution index in China and the higher the index is, the more serious the air pollution is. When the electricity consumption increases 1%, the air pollution index will increase of by 0.0649% as accompanied. (2) Through comparison of different times, we found that the degree of increase in air pollution index caused by electricity consumption would be reduced due to the improvement of environmental protection efforts. From the perspective of different geographical locations, the electricity consumption in the southeast side of the "Hu Line" has exacerbated the impact on air pollution index. (3) According to the panel quantile regression results, the marginal effect of electricity consumption on air pollution is positive. With the increase of quantiles, the impact of electricity consumption on air pollution is increasing. (4) Spatial effect analysis shows that electricity consumption has a significant positive spatial spillover effect on air pollution index. The increase in electricity consumption not only increases the air pollution index in the local region, but also leads to an increase in the air pollution index in surrounding areas. These findings contribute to the governance of air pollution and the promotion of sustainable economic, environmental and energy development.

Research on the spatial spillover effect of carbon trading market development on regional emission reduction

This paper introduces the current situation of carbon trading market in China and the effect of carbon emission reduction in each region. Theoretically, it expounds the influence mechanism and spatial spillover way of carbon trading market on regional carbon emission. Next, we use the data of 30 provinces in China from 2006 to 2019 to build a continuous spatial difference in difference model (SDM-DID) to empirically study the spatial spillover effect of carbon trading market on regional emission reduction. The results are as follows: First, the implementation of the pilot policy of carbon emission trading has significantly promoted the carbon emission reduction in the pilot areas. From the perspective of impact mechanism, the implementation of carbon trading pilot policy promotes carbon emission reduction in pilot areas by promoting clean transformation of energy consumption structure, improving technology absorption capacity and stimulating development of low-carbon technologies. From the perspective of spatial spillover effect, China’s regional carbon emissions have significant spatial spillover effect, and carbon emissions trading has spatial spillover effect. From the perspective of spatial spillover, the carbon emission trading market promotes the carbon emission reduction in neighboring areas by promoting the clean transformation of energy structure in neighboring areas, improving technology absorption capacity and promoting technological progress.

Spatial effects of green innovation and carbon emission reduction in China: Mediating role of infrastructure and informatization

Green innovation (GI) plays a vital role in mitigating urban carbon dioxide (CO2) emissions and fostering sustainable development in China. This study examines the impact of GI on CO2 emissions, underscoring its significance for environmental sustainability. The analysis of data from 253 Chinese cities from 2010 to 2020 shows a transition in GI from a “multipoint” sporadic pattern to a “clustered” aggregation, indicative of significant polarization. Concurrently, a converging trend in the CO2 emissions kernel density curve reflects the initial success of carbon reduction initiatives, demonstrating a notable “high in the north and low in the south” spatial disparity. Critically, the findings reveal that GI induces significant spatial spillover effects, reducing CO2 emissions not only locally but also in adjacent areas. The mediation analysis reveals that the level of infrastructure development acts as a masking factor, suggesting that despite infrastructure expansion potentially escalating CO2 emissions, alignment with GI principles steers its environmental impact towards a positive direction. Additionally, informatization's modest mediating role suggests that its enhancement, driven by GI, further mitigates CO2 emissions through improved resource efficiency. These insights highlight the importance of integrating GI into urban policy frameworks, emphasizing its role in environmental management and CO2 emission reduction.

Haze Pollution, Climate Risk Perception and Demand for Commercial Health Insurance

Haze pollution not only affects the quality of economic growth and the image of the government, but also seriously affects public health. With the improvement of climate risk perception, the public is actively seeking all kinds of risk management measures to combat the hazards of haze pollution. The study of the relationship between haze pollution, climate risk perception and the development of commercial health insurance is of great significance to the formulation of haze control policies and the improvement of social security system. This paper attempts to explore the relationship between haze pollution, climate risk perception and commercial health insurance demand by establishing static and dynamic models based on panel data from 31 provinces in China from 2005 to 2022. Also, the spatial spillover effects of haze pollution in different regions on the development of commercial health insurance in other regions are investigated by establishing a spatial Durbin model. It is found that (1) haze pollution has a lagged positive effect on the demand for commercial health insurance; (2) haze pollution has a significant spatial spillover effect on the development of commercial health insurance; (3) this study used Python technology to construct a climate risk perception index, and found that the moderating effect of the residents’ perception of climate risk existed significantly, and that the residents might take other measures to manage the risk in the short term, but in the long term, the climate risk perception showed a positive correlation with the level of education. This paper provides implications for government departments and social media to strengthen education and publicity, improve residents’ awareness of risk diversification, and deepen the concept of commercial health protection.

The spatial spillover effects of clean energy consumption and production on sustainable economic development in China

The massive consumption of fossil energy has resulted in high CO2 emissions, posing a formidable challenge to global sustainable economic development (SED). As countries endeavor to shift from fossil to clean energy sources to achieve SED, research on the impact of clean energy is scarce, and quantitative analysis is lacking. This study measured China's SED and used a spatial econometric model to examine the impact of clean energy consumption and production on SED across 30 provinces in China from 2008 to 2020. Results show that (1) China's SED exhibits significant positive spatial autocorrelation characteristics, forming a “point-to-area” development pattern. (2) Clean energy consumption, production, and consumption structure all contribute to the promotion of SED in the region and have positive spatial spillover effects. (3) A considerable regional disparity exists in the spatial impact of clean energy on SED. The eastern and central regions have significant positive spatial spillover effects, whereas the western region is opposite. Notably, the estimated coefficient of the spatial Durbin model is relatively small, reflecting China's ongoing transition to clean energy and its limited role in promoting economic sustainability. Joint efforts and differentiated policies are essential to develop clean energy and sustainable economic.

The spatiotemporal effects on ecosystem services supply-demand from industrial transformation and upgrading: Promotion or inhibition?

Traditional industrial development models have already caused an imbalance in ecosystem services supply and demand (ESSD). As a response strategy, industrial transformation and upgrading (ITU) are increasingly playing a vital role in regulating the relationship among ESSD. However, research on the interplay and impact of these two aspects remains insufficient. Therefore, a comprehensive analysis of the complex effects of ITU on ESSD is essential for industrial planning and environmental management. We developed a theoretical framework to interpret how ITU impacts ESSD, from the perspective of the natural-social-economic composite ecosystem. Using the Yangtze River Economic Belt (YREB) as an example, we employed the Dynamic Spatial Durbin model (DSDM) to reveal the spatiotemporal effects of ITU on ESSD for four distinct types. The results indicated that from 2010 to 2021, the total supply of ecosystem services in the YREB exceeded the demand. The kernel density curves of ESSD ratios related to food production, carbon sequestration, water conservation, and soil conservation all show a trend of peak shifting to the bottom right over time. Additionally, pronounced spatial heterogeneity was observed in the ESSD ratios, with a notable clustering trend over time. Furthermore, the analysis of spatiotemporal effects decomposition revealed that ITU had a detrimental influence on the equilibrium between the supply and demand of food production, with this adverse effect intensifying and manifesting a stronger spatial spillover as time progressed. Positive effects were observed in the supply and demand for carbon sequestration and water conservation, both demonstrating significant spatial spillover effects. Steady negative spatiotemporal effects were noted for soil conservation supply and demand. Finally, we clarified the principal pathways through which ITU impacts ESSD. It offers policy recommendations for industrial development and ecosystem stewardship to mitigate the ESSD imbalance.

The impact of digital economy on rural revitalization: Evidence from Guangdong, China

BackgroundDigital technology and economy have profound impact on rural revitalization and become important initiatives to promote rural development. This study analyzes the spatial effect of digital economy on rural revitalization in Guangdong, China. MethodThe entropy weight method is used to evaluate the level of rural revitalization and digital economy in 20 prefecture level cities of Guangdong province during 2011–2021. Spatial panel model is used to analyze the spatial spillover effect of digital economy on rural revitalization. Threshold model is employed to analyze the marginal effects of the digital economy on rural revitalization. Heterogeneous analysis is made by grouping the prefecture-level cities into four regions: the Pearl River Delta (PRD), the East Wing, the West Wing and the Mountainous region. ResultsBoth the level of rural revitalization and digital economy development in every prefecture-level city experienced an increase during 2011–2021 and the PRD region take the lead in both the rural revitalization and digital economy. There is significant spatial spillover effect of digital economy on the rural revitalization as a whole (the coefficient is about 0.3537). However, in the regions with a low level of digital economic development, there is a negative impact (−0.1847) of the digital economy on rural revitalization; while in regions with medium or high level of digital economy, it has a significant positive effect (0.3835) on rural revitalization. The impact of digital economy on rural revitalization development is significantly greater in the PRD (0.3141), the East Wing (0.7215), the West Wing (0.5467) than in the mountainous region (0.2238). ConclusionsThere is significant spatial differentiation in the digital economy and rural revitalization. The digital economy has significant spatial spillover effect on the rural revitalization. And this effect is found out to have heterogeneous and non-linear characteristics. In order to promote rural revitalization, it is necessary to make full use of the digital economy and technology in rural areas. Besides, it is important to improve the digital skills and literary of the rural population so that the digital economy could play a greater role in rural revitalization.

Clean air policy and green total factor productivity: Evidence from Chinese prefecture-level cities

Clean air policy is an important mechanism for improving the urban environment and promoting green economic development. Green total factor productivity (GTFP) is an important way to measure these impacts. We apply the super-efficiency slack-based measure model, considering undesirable output, and the Global Malmquist-Luenberger index to measure the GTFP of 278 prefecture-level cities in China from 2005 to 2020. We find that GTFP growth is driven by both green technology progress (GTC) and green technology efficiency change (GEC). The traditional total factor productivity is overestimated, because energy and environmental factors are not considered. GTFP growth is higher in the cities in the eastern coastal regions compared to the western regions. We analyze the effect of clean air policy on GTFP using a difference-in-differences model and spatial-difference-in-differences model, and further conduct a heterogeneity analysis and mechanism analysis. The results show that clean air policy promotes GTFP growth. In addition, there is a significant negative spatial spillover effect with respect to the impact of clean air policy on GTFP. The heterogeneity analysis results show that the impact of clean air policy on GTFP growth is lower in resource-based cities and cities in the northern region, compared with non-resource-based cities and cities in the southern region. Further, the impact of clean air policy on GTFP growth is mainly achieved through GTC, GEC, innovation, and financial development. In resource-based cities and cities in the northern region, clean air policy decreases GTFP by inhibiting GTC, innovation, and financial development.

Carbon emissions trading, industrial structure upgrading and green development: Excess benefits of combined actions

Clarifying the influence mechanisms of carbon emissions trading scheme (ETS), industrial structure upgrading (ISU), and green development is of great theoretical and practical significance. Existing studies have only focused on the role of ETS or ISU on green development and have not included them in an analytical framework. The DID model and the moderating effect model are therefore combined in this work to to explore how the ETS will affect the link between ISU and green development throughout the period of 2008 to 2019 using panel data from 271 Chinese cities. Through a series of robustness and endogeneity tests, we find that: (1) ETS can significantly moderate the U-shaped relationship between ISU and green development, and this impact is significant in both the long and short term; (2) When ETS and ISU are implemented at the same time, the effect of the combined actions is greater than the sum of the effects of the two policies implemented separately, which means that the combined actions has excess dividends; (3) ETS and ISU have significant direct effects and spatial spillover effects on green development, and the excess dividends of combined actions also exist significantly at the spatial level. The research results of this paper provide an important theoretical and empirical basis for establishing the combined actions of ETS and ISU.