Significant Spatial Spillover Research Articles

Does green innovation reduce carbon emission intensity of Chinese cities? Analysis based on GS2SLS

ABSTRACT In the 14th Five-Year Plan, China’s economic and social development aims to focus on carbon peaking and carbon neutrality. On the basis of panel data of 284 prefecture-level cities in China from 2011 to 2020, this study uses the generalized spatial two-stage least squares method (GS2SLS) to analyse empirically the relationship and mechanism between the green innovation and carbon emission intensity（CEI） of Chinese cities. The research reveals several findings. (1) The CEI of Chinese cities has a significant spatial spillover effect. Moreover, green innovation has reduced the CEI of Chinese cities. The robustness and endogenous tests further verified this conclusion. (2) The carbon emission reduction effect of green innovation shows significant regional heterogeneity, which is more significant in eastern regions and cities with high innovation capabilities. In contrast, this outcome is not significant in regions with weaker innovation capabilities and in the central and western regions. (3) Green innovation mainly reduces the CEI of Chinese cities by promoting the upgrading of industrial structures. A higher level of digital economy development will also have a significantly positive catalytic effect on green innovation to inhibit CEI.

How does the robot adoption promote carbon reduction?: spatial correlation and heterogeneity analysis.

Along with the continuous improvement of industrial intelligence, robots are widely used in various aspects of production and life, playing an essential role in achieving carbon reduction targets. However, the existing research on the carbon reduction effect of robots and its mechanism is limited. Therefore, this study aims to explore the impact of robot adoption on carbon emissions and analyzes the mechanism by taking 30 provinces in China from 2006 to 2019 as research objects. It found that robot adoption can significantly reduce carbon emissions. However, the degree of marketization plays a masking effect, which limits robots' carbon reduction effect to some extent. Furthermore, the carbon reduction effect of robot adoption is stronger in provinces with lower carbon emissions. Finally, robot adoption has a significant spatial spillover effect on neighboring regions. The improvement of robot adoption will positively affect the region's and surrounding areas' carbon emission reduction. The relevant findings provide empirical support for further deepening the policy implementation of robot-assisted carbon emission reduction.

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.

The impact of environmental regulation on renewable energy development in China from the perspective of spatial effects.

From a spatial perspective, this paper constructs a spatial Durbin model based on the adjacent weight matrix to analyze the impact of environmental regulation on the development of renewable energy in 30 provinces (autonomous regions and municipalities directly under the Central Government) in China from 2007 to 2020. The results show that (1) both environmental regulation and renewable energy development have positive spatial autocorrelation and form relatively similar spatial agglomeration areas, specifically showing the characteristics of "high-high" agglomeration in resource-rich areas and "low-low" agglomeration in resource-scarce areas. (2) Environmental regulation significantly promotes the development of local renewable energy and has a significant spatial spillover effect on the development of renewable energy in neighboring provinces. (3) The moderating effect results show that renewable energy installed capacity and electricity demand play an inverse moderating role between environmental regulation and renewable energy development. (4) From the perspective of different regions, the impact of environmental regulation on the development of renewable energy is heterogeneous. Based on the research conclusions, this paper finally provides corresponding policy suggestions from three aspects: regional cooperation, technical support, and differentiation.

How do local government fiscal revenue targets affect green technology innovation in China?

ABSTRACT The process of economic development in China cannot be separated from the ‘shadow’ of government target intervention. Under the Chinese system of fiscal decentralization, constraints created by local government fiscal revenue targets (CCFRTs) will have a series of influence on development economically and socially. Based on the fiscal revenue target data revealed in the government work reports of 281 prefecture-level cities in China from 2006 to 2019, this paper explores the influence of CCFRTs on green technology innovation (GTI). The findings are as follows: first, CCFRTs significantly inhibits GTI. Second, Spatial Durbin model analysis shows that CCFRTs has significant negative spatial spillover effect on GTI. Third, CCFRTs can affect GTI through the optimization of industrial structure, the level of human capital, and the degree of opening-up, technological progress and economic growth. Fourth, CCFRTs has an obvious threshold effect on GTI. Finally, the influence of CCFRTs on GTI has regional heterogeneity in central, eastern and western China. In the western and central regions, CCFRTs significantly restrains GTI significantly, while in the eastern region, CCFRTs significantly promotes GTI.

Examining the Factors Influencing Agricultural Surface Source Pollution in the Yangtze River Economic Zone from the Perspectives of Government, Enterprise, and Agriculture

In this study, for the period between 2006 and 2021, we used the spatial Durbin model and dynamic Generalized Method of Moments to analyze the spatial and temporal characteristics and contributory factors of agricultural surface source pollution in 11 provinces and cities within China’s Yangtze River Economic Belt from the perspectives of governments, enterprises, and farmers. In addition, we also investigated the threshold characteristics of the distortion of the factor market for agricultural surface source pollution under different levels of environmental regulation. Our results revealed a positive spatial correlation between agricultural surface pollution in the Yangtze River Economic Belt which was significant at the 1% level. Furthermore, we established that government environmental regulation, input factor market distortion, and labor transfer have significant effects on agricultural surface pollution, among which factor market distortion has a significant spatial spillover effect in this economic zone, and environmental regulation has a significant single-threshold effect, with a threshold value of 0.1405. Based on these findings, we propose practical steps for the mitigation of agricultural surface pollution from the perspectives of governments, enterprises, and farmers which could be adopted to support countryside revitalization.

The spatial spillover effects of establishing free trade pilot zones on FDI: Empirical evidence from China

The establishment of free trade pilot zones (FTZs) in China has constituted a pivotal endeavor to enhance global collaboration, foster economic restructuring and transformation, and attract foreign direct investment (FDI). These objectives are pursued through a series of strategies, including implementing a negative list system, reducing the threshold for FDI, and enhancing the FDI service framework. Based on panel data from 47 cities between 2005 and 2018, this research employs a spatial difference-in-differences model to empirically examine the spatial spillover effects of establishing FTZs concerning FDI. The findings reveal the substantial positive impact of FTZs on fostering FDI within respective domains. Conversely, an adverse spillover effect is observed on FDI in neighboring vicinities. Coastal FTZs have a negative spillover effect on FDI in surrounding areas, whereas inland FTZs have minimal impact on FDI in surrounding areas. The first and third batches of FTZs have had negative spillover effects on FDI in surrounding areas, while the second batch of FTZs has had no significant spatial spillover effect on FDI. Based on the empirical conclusions, this study proposes policy recommendations to broaden the scope of FTZs, refine the spatial spillover mechanism, and foster the diversified development of FTZs. These measures are envisaged to optimize the efficacy of the FTZ strategy to advance FDI objectives.

Digital economy and inclusive green growth: The moderating effect of government environmental regulation.

As digital economy flourishes, there have been fundamental changes in the patterns of economic development, social structure, and ecological environment, which are the key elements of inclusive green growth (IGG). However, whether digital economy can effectively contribute to IGG requires further investigation. This paper evaluates the direct and spatial spillover effect of digital economy on IGG of 280 cities in China during 2011-2019 using Spatial Durbin Model (SDM). It further explores how government environmental regulation (GER) moderates this facilitating effect. The empirical results show that digital economy significantly reinforces IGG while GER weakens the benefits of digital economy to IGG. There is a significant spatial spillover effect of digital economy on IGG in neighboring regions; specifically, IGG in peripheral cities is more significantly encouraged by digital economy than in central cities. In addition, digital development demonstrates the most significant impact on IGG in central regions of China, followed by the eastern regions, with western regions lagging behind. This paper contributes theoretically and empirically to promote digital economy selectively for IGG in different regions and provides a guideline for policymakers to achieve IGG through proper GER.

Financial agglomeration and regional green innovation efficiency from the perspective of spatial spillover

Starting from the theoretical mechanism of the impact of financial agglomeration on regional green innovation efficiency, and using panel data from 30 provinces in China from 2009 to 2017, this study calculates a financial agglomeration index and green innovation efficiency applying principal component analysis and the slacks-based measure (SBM) of super-efficiency. The study then constructs static and dynamic spatial Durbin models using two different spatial weight matrices to empirically test the spatial spillover effect of financial agglomeration on regional green innovation efficiency. The results reveal a significant positive spatial correlation between China's inter-provincial green innovation efficiency and financial agglomeration. Both static and dynamic models demonstrate that financial agglomeration has a significant spatial spillover effect on the green innovation efficiency of adjacent provinces, but the static model overestimates the impact of spatial spillover. In addition, human capital level, technology market activity, and environmental regulation all have significant positive impacts on the green innovation efficiency of provinces and adjacent provinces.

Has China achieved synergistic reduction of carbon emissions and air pollution? Evidence from 283 Chinese cities

Confronted with the dual pressures of carbon emissions and air pollution, examining their synergistic effects becomes increasingly paramount in China. This study verifies and quantifies the bidirectional synergistic effects between reductions in carbon emissions and air pollutants (SO2 and PM2.5) at the city level. We also analyzed the spatial spillover of this effect among cities, investigating the dynamic evolution, heterogeneity, and underlying mechanisms of both synergistic reduction and increase effects across different time scales. Key findings include: 1) Carbon emission mitigation causes greater synergistic reduction effect than pollution reduction; 2) Carbon emission reduction has a more significant synergistic effect on SO2 than PM2.5; 3) Synergistic effects vary across city types. Cities with higher resource endowments, lower administrative levels, smaller populations, and lower economic status show greater synergistic effects; 4) The synergistic effects demonstrate significant positive spatial spillovers across cities, with local reductions in carbon and sulfur emissions spurring sulfur emission reductions in neighboring regions; 5) Synergistic reduction effects between carbon and air pollutant emissions exhibit temporal delays, while their synergistic increase effects are pronounced in both short and long terms; 6) R&D investment mitigates synergistic increase effects, while the impact of energy efficiency on synergistic reduction effects shows an inverted U-curve relationship. Our findings offer valuable insights for policymakers seeking to simultaneously tackle climate change and environmental pollution more effectively.

Does the opening of high-speed rails improve urban carbon efficiency? Evidence from a spatial difference-in-difference method.

High carbon emission efficiency is an important guarantee for achieving the goals of "carbon peaking" by 2030 and "carbon neutrality" by 2060. Based on the panel data of prefecture-level cities from 2003 to 2018, the spatial difference-in-difference model is used to empirically test the spatial spillover effect of the opening of high-speed rail (HSR) on urban total factor carbon emission efficiency (TFCEE). The results show that the spatial correlation of TFCEE between regions is positive, and the opening of HSR has a significant positive spatial spillover effect on TFCEE. The conclusion is still valid after a series of robustness tests. We further employ a mediating effects model to verify that green technology innovation and labour resource mismatch are two important channels of influence for the opening of HSR to improve TFCEE. The heterogeneity analysis shows that the opening of HSR significantly promotes the higher development level and the provincial capital TFCEE.

Spatial Effect of Green Economic Efficiency in China From the Perspective of Informatization

Green economy has been paid more and more attention in the information age. Informatization plays an important role in the development of green economy by the transmission of industrial structure rationalization and upgrading. Because of the spatial mobility of information, it is necessary to study the spatial spillover effect of information on the efficiency of green economy. In this article, the non-radial directional distance function and the comprehensive index method are used to evaluate the efficiency of green economy and informatization respectively. On this basis, the spatial characteristics of the two are analyzed. Finally, the spatial econometric model is used to analyze the spatial impact of informatization on the efficiency of green economy. The authors find that: (i)The spatial distribution of the green economy efficiency and informatization are unbalanced; (ii) There is a significant spatial spillover effect in the efficiency of green economy; and (iii) The development of informatization plays an important impact on the efficiency of green economy.

The Impact of Urbanization on Food Security: A Case Study of Jiangsu Province

Food security has received extensive academic attention in recent years. However, research results analyzing cultivated land pressure from the perspective of urbanization are relatively few. This study used Jiangsu Province as the study area and analyzed the spatial pattern evolution of cultivated land pressure from 2005 to 2019 by constructing a formula for a cultivated land pressure index. The study used a spatial econometric approach to analyze the spatial relationship between urbanization and cultivated land pressure. Based on the spatial Durbin model, the impact of urbanization on the pressure on cultivated land is analyzed. According to the results, Jiangsu Province showed an obvious north–south divergence in the spatial distribution of the cultivated land pressure index, with the low-value areas of the cultivated land pressure index mainly distributed in northern and central Jiangsu, and the high-value areas mainly distributed in southern Jiangsu. The urbanization level and cultivated land pressure level in Jiangsu Province showed obvious spatial clustering characteristics, and there was a certain overlap between the high- and low-value clustering areas of the two, with significant positive spatial correlation features. The total urbanization had no significant effect on the cultivated land pressure. Population urbanization and industry urbanization showed a significant negative effect on cultivated land pressure in Jiangsu Province, while land urbanization showed a positive effect. Both population and land urbanization had a significant negative spatial spillover effect on cultivated land pressure. Plausible explanations of these results were provided and policy implications were drawn.

The Impact of Digital Economy Empowerment on Green Total Factor Productivity in Forestry

The digital economy is an important engine for promoting green economic development, and the integration of the digital and real economies can accelerate the transformation of the real economy. In order to explore the multifaceted influence of digital economy on forestry green total factor productivity and its specific presentation form, based on the panel data of 277 cities in China from 2013 to 2019, this paper first used the super SBM model to measure the level of forestry green total factor productivity and adopted the entropy method to measure the level of the digital economy in each region. Secondly, the influence and mechanism of the digital economy on green total factor productivity in forestry were explored by using fixed-effect and intermediate-effect models, and the heterogeneity of the digital economy on forestry green total factor productivity was analyzed based on different regional classification methods. Finally, the spatial spillover effect of the digital economy was explored in depth by the spatial Durbin model. The results are as follows: firstly, there is a significant inverted U-shaped relationship between the digital economy and forestry green total factor productivity, which first promotes and then inhibits. Secondly, the relationship between the digital economy and the level of urban green innovation shows a positive U-shaped relationship, first inhibiting and then promoting, and can have an indirect impact on forestry green total factor productivity by promoting the level of green innovation. Third, China is still on the left side of the inverted U-shaped relationship between the digital economy and forestry green total factor productivity, i.e., it is at a stage where the digital economy can significantly contribute to forestry green total factor productivity. Fourth, the effect of the digital economy on green total factor productivity in forestry is heterogeneous in the east, central, and west and is more pronounced in regions with faster economic development or rich natural resources. Fifth, the impact of the digital economy on forestry green total factor productivity has a significant positive spatial spillover effect.

Intellectual property system and urban green innovation: Evidence from China

AbstractGreen innovation (GI) can enable win‒win style economic and ecological benefits. Using China's pilot scheme for the construction of the intellectual property protection (IPP) system as an example, this paper empirically tests the impact of IPP system reform on the GI level and its spatial spillover effect. The results show that IPP system reform has significantly promoted urban GI, indicating that a progressive reform model characterized by experimentalist governance is applicable to innovation policy practices in developing countries. The dynamic effect analysis shows that IPP system reform can be applied to continuously promote urban GI. The mechanism analysis shows that such use of IPP system reform can improve the level of urban GI by promoting investment and talent agglomeration, confirming the viewpoint of the institutionalist school. The heterogeneity analysis shows that IPP system reform plays a stronger role in promoting GI in peripheral cities than in central cities, in cities with lower rather than higher scientific and educational levels and in cities with weaker rather than stronger GI capacity. Consistent with the theory of institutional diffusion, IPP system reform has a significant spatial spillover effect, promoting GI activities in surrounding cities while working to improve the local GI level. This paper affirms the effectiveness of the pilot regional innovation policy with Chinese characteristics, with important theoretical significance.

Spatial correlation network structure of port performance and its drivers: A case study of Chinese coastal ports

Coastal ports play a critical role as vital intersections connecting land and sea, and their level of spatial connectivity and integration serves as a crucial indicator of competitiveness. This study employs a gravity model to analyse the spatial network of port performance among 21 major coastal ports in China, investigating the overall characteristics of the network, centrality measures, network vulnerability, and spatial clustering features during the period from 2012 to 2021. The findings reveal a relatively stable spatial network structure of the coastal port performance, with closely intertwined connections between ports. Key ports such as Shanghai Port, Qingdao Port, Xiamen Port, and Guangzhou Port occupy central positions within the network, exerting a dominant influence. Port performance shows more obvious clustering characteristics in the correlation network, with strong intra-plate correlations and significant spatial spillover from the Southeast Coast, Yangtze River Delta, Pearl River Delta, and Southwest Coast. Furthermore, spatial distance, urbanization level, per capita GDP, and marketization level significantly impact the spatial correlation of port performance. The higher the similarity of economic development and marketization levels between ports, the stronger the spatial correlation and spillover of port performance. These research findings contribute to the establishment of collaborative mechanisms for the coordinated development of coastal ports and provide valuable insights for port management decision-making.

Siphon and radiation effects of ICT agglomeration on green total factor productivity: Evidence from a spatial Durbin model

Information and communication technology (ICT) agglomeration has a dual role in influencing economic growth and environmental recovery, and there is a significant spatial spillover effect. This paper will explore the spatial effects of ICT agglomeration on green total factor productivity (GTFP) through a spatial Durbin model (SDM) using balanced panel data for 282 cities in China from 2008 to 2019. Further, we explore the regional heterogeneity, impact paths, and the threshold effects between ICT agglomeration and GTFP. We obtained the following research findings: (1) ICT agglomeration affects GTFP through spatial spillover effects. Specifically, ICT agglomeration can significantly contribute to local GTFP, but negatively affects GTFP of surrounding cities. (2) ICT agglomeration has a significant contribution to local GTFP in eastern cities, while it only has a negative effect on GTFP in surrounding cities in central and western cities. (3) ICT agglomeration in large cities has a significant radiation effect, which can promote local and overall GTFP; ICT agglomeration in small cities has a significant siphon effect, which has a significant negative impact on both local and surrounding cities' GTFP. (4) ICT agglomeration can contribute to GTFP by promoting green technology innovation and science expenditure, and ICT agglomeration has a significant contribution effect on GTFP only when the economic growth level crosses the threshold. The results of this paper provide a valid reference for developing a green economy in China.

Temporal–Spatial Variations and Convergence Analysis of Land Use Eco-Efficiency in the Urban Agglomerations of the Yellow River Basin in China

Achieving synergistic development of efficient urban land use and the natural environment is crucial in promoting green urbanization. The assessment of land use eco-efficiency (LUEE) and its temporal–spatial changes provides an effective means of quantifying the relationship between the urban ecological environment and land use. Targeting 55 selected cities in the Yellow River Basin (YRB), in this study, we utilize the Super-EBM method to gauge the LUEE. We explore the temporal patterns and the spatial convergence of LUEE utilizing kernel density estimation and spatial econometric methods. Considering the resource and environmental costs of land use, we assumed the industrial pollutant emissions generated during urban land use as the undesired outputs and designed a framework for measuring the level of LUEE under double constraints, which theoretically revealed the formation process and spatial convergence mechanism of LUEE. The results show the following: (1) Throughout the sample period, the LUEE of the YRB urban agglomeration decreased from 0.158 in 2009 to 0.094 in 2020, indicating a decreasing spatial disparity in LUEE over time. Notably, the Lanxi urban cluster exhibited the largest gap in LUEE, whereas the Guanzhong Plain urban agglomeration displayed the smallest gap. The hyper-variable density exceeded the inter-group gap as the main factor leading to the difference in LUEE. (2) Although the LUEE of urban agglomerations has increased, there still exists a noticeable polarization phenomenon. (3) The LUEE of YRB demonstrates a pattern of conditional convergence and exerts a significant spatial spillover effect. Over time, the LUEE of YRB will tend towards an individual steady state. The findings have implications for strengthening linkage and synergy among cities in YRB, promoting factor integration across administrative regions, and formulating heterogeneous policies.

Assessing the role of digital economy agglomeration in energy conservation and emission reduction: Evidence from China

As an important economic phenomenon and development trend, it is meaningful to understand the impact of digital economy agglomeration (DIAGG) on energy conservation and emission reduction to achieve the dual carbon target in China. Using the panel data of 285 cities in China from 2011 to 2018, the study comprehensively investigates the influence mechanism, nonlinear effect, and spatial spillover effect of DIAGG on energy conservation and emission reduction by employing multiple econometric models. The results show that the DIAGG is beneficial to promote energy conservation and emission reduction by the mechanisms of the innovation effect, structural effect, and scale effect. However, the threshold model shows that DIAGG has a non-linear impact on energy conservation and emission reduction. When the DIAGG exceeds 0.083 and 1.194, respectively, the impact of DIAGG on emission reduction changes from inhibiting to promoting, while the marginal effect on energy conservation decreases. In addition, there is a significant positive spatial spillover effect of DIAGG on energy conservation and emission reduction, which inhibits energy conservation and emission reduction in surrounding cities. This spatial spillover effect decreases in the maturity period. This study provides policy insights for promoting energy conservation and emission reduction to achieve sustainable urban development.

The impact of industrial digital transformation on green development efficiency considering the threshold effect of regional collaborative innovation: Evidence from the Beijing-Tianjin-Hebei urban agglomeration in China

Promoting industrial digitalization and deepening regional collaborative innovation is essential for achieving urban green and sustainable development. This paper constructs a differential game model based on theoretical analysis and reveals the influence mechanism of industrial digitalization and regional collaborative innovation on urban green development efficiency (GDE). After that, this paper uses the entropy method, Super-SBM model, and improved gravity model to measure the level of industrial digitalization, urban GDE, and regional collaborative innovation, respectively. Then, this paper constructs the fixed-effects model, SDM model, moderating-effects model, and threshold model, then uses the panel data of the Beijing-Tianjin-Hebei (BTH) urban agglomeration during 2011–2020 for empirical testing. The results show that: (1) industrial digitalization significantly improves urban GDE. (2) Overall, 2011–2015 is the rapid development period of BTH industry digitalization, and 2015–2020 is its stable development period. However, there are apparent spatial differences and imbalances. (3) Industrial digitalization has a significant spatial spillover effect that can enhance local and surrounding cities' GDE. (4) Regional collaborative innovation can directly enhance urban GDE, and has a positive moderating effect on industrial digitalization to enhance urban GDE. (5) The regional collaborative innovation has two thresholds of 3.9851 and 6.6184. With the collaborative innovation level improving, the main effect intensity steadily increases.