scholarly journals The Spatial Spillover Effect of Environmental Regulation and Technological Innovation on Industrial Carbon Productivity in China: A Two-Dimensional Structural Heterogeneity Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Xiaosong Ren ◽  
Xuting Wu ◽  
Yujia Liu ◽  
Sha Sun
Keyword(s):  
Environmental Regulation ◽  
Technological Innovation ◽  
Resource Dependence ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Structural Heterogeneity ◽  
Two Dimensional ◽  
Spatial Spillover ◽  
Industrial Carbon ◽  
Carbon Productivity

Environmental regulation and technological innovation are two crucial factors for improving industrial carbon productivity. However, prior research ignored the spatial spillover effects of these factors, and heterogeneity caused by industrialization level and resource dependence did not acquire attention either. Thus, we use the STIRPAT model and spatial panel Durbin model to study the spatial spillover effects of two independent variables. Then, a two-dimensional structural heterogeneity analysis is conducted according to the industrialization level and resource dependence. The results are as follows: improving environmental regulation and technological innovation is good for industrial carbon productivity. Simultaneously, there are obvious regional differences under two-dimensional structural heterogeneity. From the perspective of space, industrial carbon productivity has high spatial autocorrelation, and it can be enhanced through local environmental legislation, as well as technological innovation. Environmental regulation’s spatial spillover impact inhibits the improvement of industrial carbon productivity in surrounding provinces, resulting in a pollution haven effect. However, there is no evident regional spillover effect of technological innovation. Therefore, we provided new perspectives from spatial spillover and structural heterogeneity to optimize low-carbon policies.

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.

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 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 A Study on The Driving Factors and Spatial Spillover of Carbon Emission Intensity in The Yangtze River Economic Belt under Double Control Action

2019 ◽  
Vol 16 (22) ◽  
pp. 4452 ◽  
Author(s):  
Xuhui Ding ◽  
Zhongyao Cai ◽  
Qianqian Xiao ◽  
Suhui Gao
Keyword(s):  
Technological Innovation ◽  
Emission Intensity ◽  
Emission Reduction ◽  
Yangtze River ◽  
Carbon Emission ◽  
Spillover Effects ◽  
The Yangtze River ◽  
Low Carbon ◽  
Spatial Spillover ◽  
Carbon Emission Intensity

It is greatly important to promote low-carbon green transformations in China, for implementing the emission reduction commitments and global climate governance. However, understanding the spatial spillover effects of carbon emissions will help the government achieve this goal. This paper selects the carbon-emission intensity panel data of 11 provinces in the Yangtze River Economic Belt from 2004 to 2016. Then, this paper uses the Global Moran’s I to explore the spatial distribution characteristics and spatial correlation of carbon emission intensity. Furthermore, this paper constructs a spatial econometric model to empirically test the driving path and spillover effects of relevant factors. The results show that there is a significant positive correlation with the provincial carbon intensity in the Yangtze River Economic Belt, but this trend is weakening. The provinces of Jiangsu, Zhejiang, and Shanghai are High–High agglomerations, while the provinces of Yunnan and Guizhou are Low–Low agglomerations. Economic development, technological innovation, and foreign direct investion (FDI) have positive effects on the reduction of carbon emissions, while industrialization has a negative effect on it. There is also a significant positive spatial spillover effect of the industrialization level and technological innovation level. The spatial spillover effects of FDI and economic development on carbon emission intensity fail to pass a significance test. Therefore, it is necessary to promote cross-regional low-carbon development, accelerate the R&D of energy-saving and emission-reduction technologies, actively enhance the transformation and upgrade industrial structures, and optimize the opening up of the region and the patterns of industrial transfer.

scholarly journals Environmental Regulation, Resource Misallocation and Industrial Total Factor Productivity: A Spatial Empirical Study Based on China’s Provincial Panel Data

2021 ◽  
Vol 13 (4) ◽  
pp. 2390
Author(s):  
Xu Dong ◽  
Yali Yang ◽  
Xiaomeng Zhao ◽  
Yingjie Feng ◽  
Chenguang Liu
Keyword(s):  
Panel Data ◽  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Spillover Effect ◽  
Factor Productivity ◽  
Resource Reallocation ◽  
Spatial Spillover ◽  
Resource Misallocation ◽  
Capital Misallocation ◽  
Spatial Spillover Effect

A vast theoretical and empirical literature has been devoted to exploring the relationship between environmental regulation and total factor productivity (TFP), but no consensus has been reached and the reason may be attributed to the fact that the resource reallocation effect of environmental regulation is ignored. In this paper, we introduce resource misallocation in the process of discussing the impact of environmental regulation on TFP, taking China’s provincial industrial panel data from 1997 to 2017 as a sample, and the spatial econometric method is employed to investigate whether environmental regulation has a resource reallocation effect and affects TFP. The results indicate that there is a U-shaped relationship between environmental regulation and industrial TFP and a negative spatial spillover effect of environmental regulation on industrial TFP at the provincial level in China. Both capital misallocation and labor misallocation will lead to the loss of industrial TFP. Capital misallocation has a negative spatial spillover effect on industrial TFP, while labor misallocation is just the opposite. Environmental regulation can produce a positive resource reallocation effect, which in turn promotes the industrial TFP in the range of 28% to 33%, while capital misallocation and labor misallocation are only partial mediator.

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