Spillover Effects Of Environmental Regulation Research Articles

Does Environmental Regulation Have an Employment Dividend? Evidence from China

Environmental regulations not only benefit environmental improvement but may also have a potential employment dividend, which is important for sustainable economic development. Based on the provincial panel data of China from 1997 to 2019, the spatial Dubin model is used to analyze the spatial spillover effects of environmental regulation on employment. From the findings, there is a significant spatial agglomeration characteristic in the employment scale. The environmental regulation positively influences the local employment scale, while there is a negative spatial effect on employment in neighboring regions. With regards to the regional heterogeneity analysis, environmental regulation has a spatial negative correlation with employment in coastal areas and less polluted areas. Additionally, in inland areas and less polluted areas, environmental regulation has a significant positive impact on the employment scale. Meanwhile, market-based environmental regulation has the potential to expand the employment scale in local and neighboring areas, while command-and-control environmental regulation impacts negatively on employment in neighboring areas. This study found that environmental regulation has an employment dividend. These findings reveal the spatial dependence between environmental regulation and employment, which will help policy makers consider the environmental and employment effects of environmental regulation more comprehensively. Therefore, the government should formulate targeted policies under regional differences to promote high-quality employment and construct a multiple governance environmental regulatory system.

Does Environmental Regulation Promote the Infrastructure Investment Efficiency? Analysis Based on the Spatial Effects.

Infrastructure investment plays a key role in steady economic growth. Investment in infrastructure is gradually increasing; however, large-scale infrastructure investment is also associated with efficiency problems and environmental problems, which need to be carefully examined. The entropy weight method and the Super-SBM model are implemented to measure environmental regulation and infrastructure investment efficiency, respectively; and the spatial Durbin model is applied to analyze the influence mechanism and spatial effects of environmental regulation on infrastructure investment efficiency. The results show that spatial agglomeration characteristics exist in both environmental regulation and infrastructure investment efficiency. Besides, environmental regulation can promote infrastructure investment efficiency in general, but it develops an inverted U-shaped relationship as the intensity increases. Lastly, the spillover effects of environmental regulation on infrastructure investment efficiency present a U-shaped relationship. The conclusion is that both environmental regulation and infrastructure investment efficiency in China increased from 2008 to 2020. Besides, moderate environmental regulation is beneficial to infrastructure investment efficiency and restrains spatial spillover, but strict environmental regulation appears to be the opposite. This research expands the literature on environmental regulation and production efficiency and provides a reference basis for formulating effective policies to improve infrastructure investment efficiency from the perspective of the ecological environment.

The Impact and Spillover Effects of Environmental Regulation on GTFP

Have environmental regulations introduced by local governments in China promoted regional green development? This paper identifies the impact and spillover effect of environmental regulations on Green Total Factor Productivity by using provincial panel data over the period 2005-2018. We found that the intensity of ERs is positively correlated with regional GTFP growth and also benefits its neighbours. I have also identified green innovation and FDI transfer as two mechanisms of action leading to this phenomenon. Finally, the effects of environmental regulation also vary according to geographical location, the degree of dependence on polluting industries and the level of nationalisation.

Does Environmental Regulation Drive Economic Growth through Technological Innovation: Application of Nonlinear and Spatial Spillover Effect

Based on provincial dynamic panel data from 2010 to 2019, this paper constructs a panel threshold model and explores the nonlinear relationship between environmental regulation and economic growth through channels of technological innovation. In addition, a spatial panel Durbin model is constructed to test the spatial spillover effects of environmental regulation and technological innovation on economic growth. The results show that environmental regulation has a significant positive impact on economic growth through channels of technological innovation. The interaction between environmental regulation and technological innovation has a single threshold effect on economic growth. When the intensity of environmental regulation exceeds the critical value, environmental regulation will change from promoting economic growth to inhibiting economic growth through channels of technological innovation. Environmental regulation has negative spatial spillover effect on economic growth of neighboring regions, while technological innovation has positive spatial spillover effect on economic growth of neighboring regions.

The Spatial Spillover Effects of Environmental Regulation and Regional Energy Efficiency and Their Interactions under Local Government Competition in China

Under the pressure of serious environmental pollution and energy shortage, China needs to improve its energy efficiency to alleviate these problems. Environmental regulation is an important constraint on economic development, which has an impact on energy efficiency. Meanwhile, energy efficiency is a reference factor for adjusting environmental policies, which has an impact on environmental regulation. Therefore, the relationship between environmental regulation and energy efficiency needs to be further studied under a unified framework. Based on Chinese provincial panel data, we first use a stochastic frontier model to estimate the energy efficiency of China’s 30 provinces from 2004 to 2019, and then employ a spatial simultaneous equation model to study the spatial spillover effects of environmental regulation and energy efficiency and their interactions. The results show that: (1) Both energy efficiency and environmental regulation have significantly positive spatial spillover effects. Specifically, an overall increase of 1% in energy efficiency in the surrounding areas can promote an improvement in the local energy efficiency by about 1.0404%, and an overall increase of 1% in environmental regulation in the surrounding areas can lead to an increase of about 0.6075% in the local environmental regulation. (2) The impact of environmental regulation on energy efficiency is significantly positive; i.e., under the current situation in China, an increase of 1% in environmental regulation can promote local energy efficiency by about 0.2777%. (3) The impact of energy efficiency on environmental regulation is significantly positive; i.e., a 1% increase in energy efficiency may stimulate local governments to strengthen their environmental regulation by 1.5981%. Accordingly, some targeted policy suggestions are given.

Environmental Regulation, Outward Foreign Direct Investment, and Low-Carbon Innovation: An Empirical Study Based on Provincial Spatial Panel Data in China

The low-carbon transformation has turned out to be a challenging task faced by government agencies, enterprises, and society because of the global warming. Endorsing the expansion of the low-carbon revolution is considered as an essential measure for low-carbon alteration and advancement. Therefore, articulating realistic environmental control strategies intended to enhance the motivation level of low-carbon innovation, though outward foreign direct investment (OFDI) can produce direct and indirect influences on the growth of low-carbon innovation. According to the data of 30 provinces of China from 2004 to 2017, the relationship among environmental regulation, OFDI, and low-carbon innovation was analyzed using the spatial econometric model. Based on the analyzed data, the following conclusions were drawn. (i) From the national and regional perspectives, China’s low-carbon innovation takes understandable agglomeration features in the longitudinal dimension. In addition, environmental regulation plays a key role in promoting low-carbon innovation and regional heterogeneity. (ii) Environmental regulation might force enterprises outward foreign direct investment efficiently and increase the level of OFDI that will be capable of promoting low-carbon innovation. (iii) OFDI acts as an intermediary in the relationship between environmental regulation and low-carbon innovation, and this role has regional heterogeneity. (iv) There are significant spatial spillover effects of environmental regulation and OFDI on low-carbon innovation, environmental regulation on OFDI, and the intermediary effect of OFDI on environmental regulation and low-carbon innovation. This study supplements our understanding of the relationship between environmental regulation and OFDI, in addition to low-carbon innovation, which provides illumination for enterprise practice, as well as decision-makers.

Environmental regulation benefits for whom? Heterogeneous effects of the intensity of the environmental regulation on employment in China

As environmental pollution in China has deteriorated in the recent years, intensifying environmental regulation has become a necessity for the Chinese government. But the debate persists among the academic circles and the government over whether a double dividend, reducing pollution emission and boosting employment, of environmental regulations exists. This study differentiates, based on Cobb-Douglas production function, the variance between high- and low-skilled labour and constructs theoretical models to analyse heterogeneous effects of environmental regulation intensity on the employment of labour with varied skills. The model finds that implementing environmental regulation will generate ‘compliance cost effect’ and ‘innovation offset effect’. The compliance cost effect will promote the employment of high-skilled labour while suppressing that of the low-skilled labour. The innovation offset effect, however, will facilitate the employment for both high-skilled and low-skilled labour. Therefore, the employment of high-skilled labour will grow along with the intensification of environmental regulation while that of the low-skilled labour will decline first and then rebound, showcasing a U-shaped curve. The empirical research results based on the provincial dynamic panel data from 2004 to 2018 in China confirm the theoretical analysis. Moreover, we find spatial spillover effects of environmental regulation on employment, with high-skilled labour being more sensitive to changes in environmental regulation. One percentage point increase in environmental regulation in neighbouring regions will cause 0.072% employment decline in high-skilled labour while that of low-skilled labour will only decrease 0.033%. The conclusions of this study verify that dividend in employment growth for both high-skilled and low-skilled labour can be realised along with intensification of environmental regulation, which carries significant guiding implications for policy-making for environmental regulation in China.

Positive or negative externalities? Exploring the spatial spillover and industrial agglomeration threshold effects of environmental regulation on haze pollution in China

As one of the efficacious environmental governance instruments, environmental regulations usually have been adopted to control haze pollution in most developing countries. However, as proved in recent researches, the relationship between environmental regulation and haze pollution remains uncertain. This paper develops a conceptual model and attributes this phenomenon to two reasons: the spatial spillover effect and industrial agglomeration threshold effect of effective environmental regulation. Spatial durbin model (SDM), instrumental variable (IV) and panel threshold model are used to estimate these effects based on 277 cities data in China from 2012 to 2016. The results confirm the spatial spillover effects of environmental regulations and haze pollution, which could influence the pollutant reduction effect through positive and negative spatial spillover effects. It also validates the thresholds of industrial agglomeration of approximately 0.818 and 1.271. Nevertheless, only 1.271 represents the turning point of the environmental regulation effect changing and environmental regulations could significantly reduce haze, only if it exceeds this numerical value. Moreover, the results have regional heterogeneity regarding spillover effect and threshold effect as well. The environmental regulation intensity in central and western regions plays a “multi-stage promotion” role on haze pollution emission with the adjustment of industrial agglomeration threshold, while it turns out to be a “triple-stage downward” trend in eastern China. At last, we put forward differential policies suggestions according to their industrial agglomeration levels.

Spatial spillover effects of environmental regulations on air pollution: Evidence from urban agglomerations in China

Environmental regulations affects the environmental quality of not only local areas but also surrounding regions. It remains unknown whether the effect of environmental regulations on the surrounding regions is free riding or pollution shelter. Based on the data from 2006 to 2018, the spatial correlation of PM2.5 in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) urban agglomerations in China was examined in this study. In addition, the spatial spillover effects of environmental regulation on PM2.5 concentrations were explored while the socio-economic driving factors of the heterogeneity of pollution spillover were identified via SDM based STIRPAT framework. Results showed that the characteristics of PM2.5 concentrations spatial correlations varies from one urban agglomeration to another. This study revealed that the air pollution is affected by not only local environmental regulations, but also regulations implemented in surrounding cities. The PM2.5 concentration of BTH, YRD and PRD increased by 0.76, 0.147 and 0.109 for each unit increase in environmental regulation of surrounding cities, respectively. In fact, cities with loose regulation become the pollution shelters. The spatial spillover effects offset the improvement effects of local environmental regulations on the air quality. Furthermore, the comparison amongst three urban agglomerations showed that the spatial spillover effects of PM2.5 concentration in BTH and YRD are higher than that of PRD. This is attributed to differences in industrial structure, population density, economic development, FDI and geographical location. Therefore, the spatial spillover effects should be taken into consideration and joint regulation should be strengthened to address air pollution issues in urban aggregations.

Does Environmental Regulation Affect Natural Gas Consumption? Evidence from China with Spatial Insights

How environmental regulations affect natural gas consumption in China is an urgent issue that must be addressed to achieve the optimal allocation of natural gas resources. The nonspatial panel model and spatial Durbin model have been applied in this paper to explore the impact of environmental regulation on gas consumption and the influence mechanism of such regulation. The results show that there is a N-inverted curve between environmental regulation and gas consumption at the national level. Three main mechanisms (or paths) by which environmental regulation affects natural gas consumption are discovered: controlling the total amount of coal in the energy mix, reducing industrial coal consumption and adjusting energy market prices. The first and third paths positively and significantly affect gas consumption, while the second path negatively affects gas consumption. Second, the spillover effects of environmental regulation promote the growth of gas consumption and integration of the natural gas market at the national level. Considering the provincial level, however, some regions have high regulation-high gas consumption intensity (HH), while others have low regulation-low gas consumption intensity (LL). Based on the above conclusions, we give recommendations for improving energy regulations in different regions to promote the development of regional natural gas markets.

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

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.

Environmental Regulation and Industrial Structure Change in China: Integrating Spatial and Social Network Analysis

Social networking has become a crucial factor affecting regional economic activities. Employing the panel data of the Yangtze River Delta and the Pearl River Delta in China, we examine the influence of environmental regulation on industrial structure and the role that social networks play in the spillover effect. Using the social media data from the Weibo API and the geo-information of enterprises, we construct the Weibo network and the enterprise network, then we analyze the network structures by employing a social network analysis method. The empirical results find the evidence of the spillover effects of environmental regulation through the above two networks by using network linkages as weight matrices in spatial econometric regressions.

Spillover Effects of Environmental Regulation for Sea Turtle Protection in the Hawaii Longline Swordfish Fishery

AbstractThis study examines spillover effects resulting from US fishing regulations instituted to protect sea turtles. Sea turtles, along with US and foreign fisheries for swordfish co-occur on the high seas in the North and Central Pacific and that allows for “spillover effects.” When one fishery is required to curtail fishing activity to reduce incidental fishing mortality on sea turtle populations, the activity of other, unregulated fleets may change in ways that adversely affect the very species intended for protection. This study provides an empirical model that estimates these “spillover effects” on sea turtle bycatch resulting from production displacement between regulated US and less-regulated non-US fleets in the North and Central Pacific Ocean. The study demonstrates strong spillover effects, resulting in more sea turtle interaction due to increased foreign fleet activity when Hawaii swordfish production declines.

Regional Competition, Heterogeneous Factors and Pollution Intensity in China: A Spatial Econometric Analysis

Regional competition may play an important role in the balance of environmental protection and economic growth. However, it is a pending issue of whether the competition among Chinese local governments leads to a race to black development or green development. This paper aims to explore the strategic interactions in provincial development in terms of an environment-economic indicator, i.e., the pollution intensity in China from 2000 to 2013. We divide four predominant industrial pollutants into two groups according to whether the pollutant is regulated, and then test the strategic interactions among regions based on the spatial lag term by employing the spatial Durbin model. The results show that the heterogeneous factors, such as various pollutants and regional difference, may give rise to diversified competition strategies. We find that the “race to black development” hypothesis is not supported at the national level, and the “race to green development” hypothesis is established in the developed eastern regions only in terms of the regulated industrial pollutants. We also detect how pollution intensity is influenced by the direct and spatial spillover effects of environmental regulation and find that environmental legislation has been effective in reducing regulated pollutants’ pollution intensity, while the effects of environmental staff and investment are weak. Finally, some policy suggestions are discussed.