scholarly journals Research on the Impacts of Heterogeneous Environmental Regulations on Green Productivity in China: The Moderating Roles of Technical Change and Efficiency Change

2021 ◽  
Vol 18 (21) ◽  
pp. 11449
Author(s):  
Yanchao Feng ◽  
Yong Geng ◽  
Zhou Liang ◽  
Qiong Shen ◽  
Xiqiang Xia
Keyword(s):  
Technical Change ◽  
Environmental Regulations ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Efficiency Change ◽  
Spatial Spillover ◽  
Lag Effects ◽  
Green Productivity ◽  
Path Dependent ◽  
Dynamic Spatial Durbin Model

Due to the publicly owned resource attributes of the ecological environment, the treatment and governance of the environment should be guided by governments, which are mainly represented as environmental regulations. However, whether environmental regulations affect green productivity and what effects heterogeneous environmental regulations have on green productivity are still implicit. In addition, the moderating roles of technical change and efficiency change are ignored. To examine these issues, this study investigated the impacts of heterogeneous environmental regulations on green productivity and the moderating roles of technical change and efficiency change using the dynamic spatial Durbin model based on the panel data of 30 Chinese provinces from 2000 to 2018. The results show the following: compared with efficiency change, technical change has a stronger promotion effect on green productivity in China; considering the spatial spillover effects and the temporal lag effects of green productivity simultaneously, the negative path-dependent feature is not supported any longer, while the spatial spillover effect is still the power source for promoting green productivity in China; the moderating roles of technical change and efficiency change for the nexus between heterogeneous environmental regulations and green productivity in China are partly and conditionally supported at national and regional levels; the direct and indirect effects of heterogeneous environmental regulations on green productivity at the regional level have a feature of spatial heterogeneity. This study provides both theoretical and practical implications, in particular for China, to promote green productivity from the dual perspectives of space and time.

scholarly journals Empirical Study of the Spatial Spillover Effect of Transportation Infrastructure on Green Total Factor Productivity

2020 ◽  
Vol 13 (1) ◽  
pp. 326
Author(s):  
Xi Liang ◽  
Pingan Li
Keyword(s):  
Total Factor Productivity ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Transportation Infrastructure ◽  
Factor Productivity ◽  
Spatial Durbin Model ◽  
Spatial Spillover ◽  
Spatial Spillover Effects ◽  
Dynamic Spatial Durbin Model ◽  
Spatial Spillover Effect

Transportation infrastructure promotes the regional flow of production. The construction and use of transportation infrastructure have a crucial effect on climate change, the sustainable development of the economy, and Green Total Factor Productivity (GTFP). Based on the panel data of 30 provinces in China from 2005 to 2017, this study empirically analyses the spatial spillover effect of transportation infrastructure on the GTFP using the Malmquist–Luenberger (ML) index and the dynamic spatial Durbin model. We found that transportation infrastructure has direct and spatial spillover effects on the growth of GTFP; highway density and railway density have significant positive spatial spillover effects, and especially-obvious immediate and lagging spatial spillover effects in the short-term. We also note that the passenger density and freight density of transportation infrastructure account for a relatively small contribution to the regional GTFP. Considering environmental pollution, energy consumption, and the enriching of the traffic infrastructure index system, we used the dynamic spatial Durbin model to study the spatial spillover effects of transportation infrastructure on GTFP.

Effects of tourism development on economic growth: An empirical study of China based on both static and dynamic spatial Durbin models

2021 ◽  
pp. 135481662110211
Author(s):  
Honghong Liu ◽  
Ye Xiao ◽  
Bin Wang ◽  
Dianting Wu
Keyword(s):  
Economic Growth ◽  
Spillover Effect ◽  
Tourism Development ◽  
Spillover Effects ◽  
Policy Implications ◽  
Long Term Effects ◽  
Spatial Spillover ◽  
Domestic Tourism ◽  
Inbound Tourism ◽  
Spatial Spillover Effect

This study applies the dynamic spatial Durbin model (SDM) to explore the direct and spillover effects of tourism development on economic growth from the perspective of domestic and inbound tourism. The results are compared with those from the static SDM. The results support the tourism-led-economic-growth hypothesis in China. Specifically, domestic tourism and inbound tourism play a significant role in stimulating local economic growth. However, the spatial spillover effect is limited to domestic tourism, and the spatial spillover effect of inbound tourism is not significant. Furthermore, the long-term effects are much greater than the short-term impact for both domestic and inbound tourism. Plausible explanations of these results are provided and policy implications are drawn.

scholarly journals Spatial Spillover Effect and Influencing Factors of Information Flow in Urban Agglomerations—Case Study of China Based on Baidu Search Index

2021 ◽  
Vol 13 (14) ◽  
pp. 8032
Author(s):  
Chengzhuo Wu ◽  
Li Zhuo ◽  
Zhuo Chen ◽  
Haiyan Tao
Keyword(s):  
Influencing Factors ◽  
Information Flow ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Urban Agglomeration ◽  
Coordinated Development ◽  
Spatial Spillover ◽  
Urban Agglomerations ◽  
Search Index ◽  
Spatial Spillover Effect

Cities in an urban agglomeration closely interact with each other through various flows. Information flow, as one of the important forms of urban interactions, is now increasingly indispensable with the fast development of informatics technology. Thanks to its timely, convenient, and spatially unconstrained transmission ability, information flow has obvious spillover effects, which may strengthen urban interaction and further promote urban coordinated development. Therefore, it is crucial to quantify the spatial spillover effect and influencing factors of information flows, especially at the urban agglomeration scale. However, the academic research on this topic is insufficient. We, therefore, developed a spatial interaction model of information flow (SIM-IF) based on the Baidu Search Index and used it to analyze the spillover effects and influencing factors of information flow in the three major urban agglomerations in China, namely Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) in the period of 2014–2019. The results showed that the SIM-IF performed well in all three agglomerations. Quantitative analysis indicated that the BTH had the strongest spillover effect of information flow, followed by the YRD and the PRD. It was also found that the hierarchy of cities had the greatest impact on the spillover effects of information flow. This study may provide scientific basis for the information flow construction in urban agglomerations and benefit the coordinated development of cities.

scholarly journals The Spatial Spillover Effects of Environmental Regulation on China’s Industrial Green Growth Performance

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 267 ◽  
Author(s):  
Xiping Wang ◽  
Moyang Li
Keyword(s):  
Growth Performance ◽  
Environmental Regulation ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Green Growth ◽  
Frontier Analysis ◽  
Spatial Spillover ◽  
Spatial Spillover Effects

This study investigated the spatial spillover effects of environmental regulation (ER) on industrial green growth performance (IGGP) in China. Firstly, a parametric stochastic frontier analysis (SFA) was estimated to measure IGGP using the data of China’s 30 provincial industry sectors during 2000–2014. Then, considering the space–time characteristics in IGGP, the spatial spillover effects of three types of ER, namely, administrative environmental regulation (AER), market-based environmental regulation (MER), and voluntary environmental regulation (VER), on IGGP was examined by employing spatial Durbin model (SDM). The main findings are: (1) the IGGP is low but shows a trend of continuous improvement and there is a significant disparity and spatial autocorrelations amongst regions; (2) the spillover effects of the three types of ER are different, specifically, the spillover effects of AER are significant negative, while the effects of MER and VER are both significant positive. The difference between the latter two is that the positive spillover effect of MER on IGGP is so large to outperform the negative direct effect, while the effect of VER is very minor. Based on these findings, relevant policy suggestions are presented to balance industrial economic and environmental protection in order to promote IGGP.

scholarly journals The Spatial Interaction Effect of Environmental Regulation on Urban Innovation Capacity: Empirical Evidence from China

2021 ◽  
Vol 18 (9) ◽  
pp. 4470
Author(s):  
Ruomeng Zhou ◽  
Yunsheng Zhang ◽  
Xincai Gao
Keyword(s):  
Environmental Regulation ◽  
Industrial Development ◽  
Positive Impact ◽  
Spatial Interaction ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Spatial Spillover ◽  
Innovation Capacity ◽  
Spatial Spillover Effects ◽  
The Impact

This paper applies a spatial econometric model to measure the impact of environmental regulation on urban innovation capacity from a spatial interaction perspective by using panel data from 41 cities in the Yangtze River Delta urban agglomeration from 2009 to 2018. The study findings are as follows: first, environmental regulation has a significant positive impact on urban innovation capacity and a significant positive spatial spillover effect; second, innovation capacity has significant positive spatial dependence; third, city informatization level, government expenditures on science and technology, city economic scale, and industrial development level all positively affect the innovation capacity of neighboring cities and all have positive spatial spillover effects on the innovation capacity of neighboring cities; and finally, city expansion reduces the innovation capacity of a city and has negative spatial spillover effects on the innovation capacity of neighboring cities.

scholarly journals Applying the Super-EBM Model and Spatial Durbin Model to Examining Total Factor Ecological Efficiency From a Multi-Dimensional Perspective: Evidence From China

2021 ◽  
Author(s):  
Li Chengyu ◽  
Zhang Yongmei ◽  
Zhang Shiqiang ◽  
Wang Jianmei
Keyword(s):  
Distribution Pattern ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Evaluation Framework ◽  
Ecological Efficiency ◽  
Spatial Durbin Model ◽  
Spatial Spillover ◽  
Distance Model ◽  
Resource Exhaustion ◽  
Hybrid Distance

Abstract Ecological efficiency mainly emphasizes the importance of balancing the relationship between natural resources,energy,ecological environment and economic growth, which has aroused widespread concern in the world.China's rapid economic development has inevitably accompanied by serious resource exhaustion,environmental pollution and ecological deterioration in the past several decades,which has brought huge challenges to China's sustainable development.Therefore, establishing the evaluation framework of total-factor ecological efficiency (TFEE) and identifying its driving force has great significance for improving China's sustainable development capabilities.Firstly, a ecological efficiency evaluation framework is established based on the theory of total factor analysis.Secondly,establishing the Super-efficient hybrid distance model consider undesirable output,and measuring the total-factor ecological efficiency of nationwide,30 provinces and four regions during the period 2003–2017.Finally, the spatial effect of total-factor ecological efficiency and its driving factor are examined by using a Spatial Durbin model. The empirical results show that: (1)The efficiency measurement results show that the TFEE of China overall and regional showed different degrees of decline during the study period.There are significant differences among 30 provinces and four regions.Beijing,Tianjin,Shanghai are efficient,and the other provinces has not been effective.The TFEE of four region's are not achieve effective,and shows the distribution pattern of the eastern > northeast > central > western .(2)Moran’s I index show that the TFEE in nationwide has a positive spatial autocorrelation,and showing a strong spatial agglomeration.However,the spatial distribution pattern of TFEE in China was unstable and easy to change;Moran scatter plot indicates that china's provincial TFEE has not only spatial dependence characteristics, but also spatial differences in spatial correlation.(3)Most factors are bound up with TFEE in various degree, in which, TP,JJ and HC play a positive in TFEE ,and IS,CITY, and EI play a negative role in TFEE. Furthermore,ER show U type of relationship with TFEE.GDP and FDI cannot have a significant impact on TFEE at this stage.(4)The spatial Durbin model results show that TFEE has significant spatial spillover effect, and the improvement of the TFEE of province will increase the this TFEE of neighboring provinces.And spatial spillover effects of TP,IS,JJ,CITY,and HC are confirmed can significant impact the improvement of TFEE in neighboring provinces.

Ecological well-being performance and influencing factors in China: from the perspective of income inequality

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lijun Zhou ◽  
Zongqing Zhang
Keyword(s):  
Income Inequality ◽  
Influencing Factors ◽  
Spillover Effect ◽  
Well Being ◽  
Spillover Effects ◽  
Content Type ◽  
Spatial Spillover ◽  
Effective Decision ◽  
The Impact ◽  
Spatial Spillover Effect

PurposeChina's increasing income inequality might cause a series of problems, such as the slowdown of economic growth, social and economic tension, the decline of the ecological environment quality and the threat to citizens' health. Consequently, income inequality will inevitably affect the ecological well-being performance (EWP) level of China's provinces through the above aspects. Analyzing the impact of income inequality on EWP and its spatial spillover effects are conducive to improving the level of EWP in China. Therefore, the research purpose of this paper is to use China's provincial data from 2001 to 2017 to analyze the impact of income inequality on EWP and the spatial spillover effect based on the evaluation of the EWP value of each province.Design/methodology/approachAt first, this study utilizes the super efficiency slacks-based measure model (Super-SBM model) to calculate the EWP values of 30 provinces in China, which can evaluate and rank the effective decision units in the SBM model and make up for the defect that the effective decision units cannot be distinguished. Then this study applies the spatial Durbin model and Tobit regression model (SDM-Tobit model) to explore the impact of income inequality and other influencing factors on EWP and the spatial spillover effects in adjacent areas.FindingsFirstly, the average EWP in China fluctuated slightly and showed a downward trend from 2001 to 2017. In addition, the EWP values of the provinces in the western region are usually weaker than those in the eastern and central regions. Moreover, income inequality is negatively correlated with EWP, and the EWP has a spatial spillover effect, which means the EWP level in a region is affected by EWP values in the adjacent regions. Furthermore, the industrial structure and urbanization level are both negatively related to EWP, while technology level, investment openness, trade openness and education level are positively related to EWP.Originality/valueCompared with the existing research, the possible contribution of this research is that it takes income inequality as one of the important influencing factors of EWP and adopts the SDM-Tobit model to analyze the impact mechanism of income inequality on EWP from the perspective of time and space, providing new ideas for improving the EWP of various provinces in China.

scholarly journals Environmental Regulations on the Spatial Spillover of the Sustainable Development Capability of Chinese Clustered Ports

2021 ◽  
Vol 9 (3) ◽  
pp. 301
Author(s):  
Xinhua He ◽  
Wenjun Liu ◽  
Ruiqi Hu ◽  
Wenfa Hu
Keyword(s):  
Sustainable Development ◽  
Environmental Regulations ◽  
Spillover Effect ◽  
Data Envelopment Analysis Model ◽  
Analysis Model ◽  
The Sustainable Development ◽  
Spatial Spillover ◽  
Media Regulation ◽  
Public Media ◽  
Development Capability

For years, China has adopted environmental regulations in developing ports to improve their sustainability. Based on the data of Chinese ports from 2009 to 2018, this paper presents a data envelopment analysis model with subdividing input-output indicator weights and develops it further in two stages with the weight preference and the slacks-based measure, respectively. After assessing the sustainable development capability (SDC) of Chinese ports and their spatial correlation, it revealed that Chinese ports are clustered in several regions and their SDC has spilled over into their neighbors. Further study revealed the SDC is affected by environmental regulations in different ways: as a key measure among regulations to improve the SDC, voluntary regulation has a spatial spillover effect, but neither the mandatory regulation nor public media regulation can significantly improve the SDC. This suggests that the port authority should enact environmental regulations based on the port spatial difference and the port should expand its operation scale and market size and recruit more top talent, which is good for improving its productivity and reducing its carbon emissions.

scholarly journals Spatial Spillover Effect of Heterogeneous Environmental Regulation On Ecological Welfare Performance in China

2021 ◽  
Author(s):  
guo bing nan ◽  
tang li ◽  
jia ru ◽  
lin ji
Keyword(s):  
Spatial Distribution ◽  
Environmental Regulation ◽  
Regional Differences ◽  
Environmental Regulations ◽  
Spillover Effect ◽  
Voluntary Participation ◽  
Spatial Spillover ◽  
Different Types ◽  
The Impact ◽  
Spatial Spillover Effect

Abstract This paper constructs a theoretical model to deduce the mechanism of environmental regulation on ecological welfare performance, selects the panel data of 30 provinces in China from 2005 ~ 2019, uses the Super-SBM model to measure the ecological welfare performance of China, and the influence of heterogeneous environmental regulation on ecological welfare performance in China is empirically tested by spatial Durbin model. The results show: (1) there are regional differences in the ecological welfare performance of different provinces in China, which illustrates an unbalanced spatial distribution; (2) there is significant positive spatial correlation between market incentive, command -control and voluntary participation environmental regulation and ecological welfare performance; (3) The impact of different types of environmental regulations on the performance of ecological welfare in China is heterogeneous. Command-control and market incentive environmental regulations can improve the performance of ecological welfare, while voluntary participation environmental regulations have no significant impact on the performance of ecological welfare; (4) From the perspective of spatial spillover effect, command-control environmental regulation is not conducive to the ecological welfare performance of neighboring regions, while market incentive environmental regulation is conducive to the improvement of ecological welfare performance of adjacent areas. The spatial spillover effect of voluntary participation environmental regulation on ecological welfare performance in adjacent areas is not significant.

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