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 government supports and credits on Turkish agriculture

2019 ◽  
Vol 9 (4) ◽  
pp. 391-401 ◽  
Author(s):  
Ahmet Ali Koç ◽  
T. Edward Yu ◽  
Taylan Kıymaz ◽  
Bijay Prasad Sharma
Keyword(s):  
Spillover Effect ◽  
Value Added ◽  
Spillover Effects ◽  
Data Set ◽  
Agricultural Output ◽  
Content Type ◽  
Spatial Spillover ◽  
Percent Increase ◽  
Spatial Spillover Effects ◽  
The Impact

Purpose Domestic supports on Turkish agriculture have substantially increased over the past decade while empirical evaluation of their output impact is limited. Also, the existing literature often neglects potential spatial spillover effects of agricultural policies or subsidies. The purpose of this paper is to quantify the direct and spillover effects of Turkish agricultural domestic measures and agricultural credits use on the added agricultural value. Design/methodology/approach This study applied a spatial panel model incorporating spatial interactions among the dependent and explanatory variables to evaluate the impact of government support and credit on Turkish agricultural output. A provincial data set of agricultural output values, input factors and government subsidies from 2004 to 2014 was used to model the spatial spillover effects of government supports. Findings Results show that a one percent increase in agricultural credits in a given province leads to an average increase of 0.17 percent overall in agricultural value-added per hectare, including 0.05 percent from the direct effect and 0.12 percent from the spillover effect. Contrary to agricultural credits, a one percent increase in government supports in a province generates a mixed direct and spillover effects, resulting in an overall reduction of 0.13 percent in agricultural value-added per hectare in Turkey. Research limitations/implications This study could be extended by controlling for climate, biodiversity and investment factors to agricultural output in addition to input and policy factors if such data were available. Originality/value This study fills the gap in the literature by determining the total effect, including direct and spatial spillover effect, of domestic supports and credits on Turkish agricultural value. The findings provide crucial information to decision makers regarding the importance of incorporating spatial spillover effects in the design of agricultural policy.

Influence of environmental regulations on China’s tourism competitiveness

2019 ◽  
Vol 10 (3) ◽  
pp. 429-446
Author(s):  
Cong Peng ◽  
Peng Yuan
Keyword(s):  
Environmental Pollution ◽  
Environmental Regulation ◽  
Environmental Regulations ◽  
Tourism Development ◽  
Nonlinear Effects ◽  
Spillover Effects ◽  
Spatial Econometric ◽  
Content Type ◽  
Spatial Spillover ◽  
Spatial Spillover Effects

Purpose China intends to enhance its environmental regulations, which will affect many industries, because of the serious environmental pollution that the country faces. This study aims to investigate the influence of environmental regulations on China’s provincial tourism competitiveness. Design/methodology/approach A vertical-and-horizontal scatter degree method is used to construct provincial-level tourism competitiveness and environmental regulation indices in China. Thereafter, a spatial econometric model is established to empirically assess the influence of environmental regulations on China’s provincial tourism competitiveness and investigate the spatial spillover effects of environmental regulations. Findings Environmental regulations and China’s provincial tourism competitiveness exhibit a “U”-shaped relationship, mainly because of the indirect effects of environmental regulations (spatial spillover effects). The environmental regulation indices of the majority of the provinces have crossed the turning point. Thus, improving environmental regulations has a positive effect on tourism competitiveness. This effect mainly originates from the positive spatial spillover effects. Social implications Tourism development plays an important role in promoting economic growth. However, increasing environmental pollution may constrain the development of tourism. Therefore, the possible influence of environmental regulations on tourism development should be understood. Originality/value At present, no research has explored the influence of environmental regulations on China’s tourism competitiveness. The current study considers the nonlinear effects of environmental regulations and investigates their spatial spillover effects.

scholarly journals Spatial Spillover Effects of Economic Growth Based on High-Speed Railways in Northeast China

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Haoming Guan ◽  
Qiao Li
Keyword(s):  
Public Transportation ◽  
Northeast China ◽  
High Speed ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Economic Benefits ◽  
Dynamic Panel Data ◽  
Liaoning Province ◽  
Spatial Spillover ◽  
Spatial Spillover Effects

This paper examines the spatial spillover effects of public transportation infrastructure on regional economy in Northeast China, the “rust belt” region in China. The dataset consists of socioeconomic data from 47 cities in the area during the period of year 2005 through 2015. Accessibility is used as an explanatory variable to reflect the influence of infrastructure on economic development. In order to avoid the endogenous, queen contiguity matrix is used to define the spatial weight matrix. In the paper, the dynamic panel data model is also used to explore the effects of high-speed railways in the whole study area and attempted to confirm the spatial differences among Heilongjiang Province, Jilin Province, and Liaoning Province. The results show that the high-speed railways increase the cities’ connection in terms of accessibility, and a significant positive spillover effect exists after the construction of high-speed railways (HSR), indicating the extensive economic benefits of HSR construction, despite of the overall economic difficulty experienced by this region.

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 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.

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