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The mechanism of the environmental regulations affecting carbon emissions is complex, and for many years it has been a hot research topic for researchers. However, few of the previous studies have focused on whether or not environmental regulations can potentially influence carbon emissions through technical efficiency. Therefore, the present study chose to investigate the mediation effects of the technical efficiencies between environmental regulations and carbon emissions using the provincial panel data of energy-intensive industries for the period ranging from 2005 to 2015. The results were as follows: (i) In regard to the entire group of energy-intensive industries, it was found that environmental regulations could not only potentially directly reduce carbon emissions, but also indirectly reduce carbon emissions through technical efficiency. In other words, technical efficiency had played a partial mediation role between the environmental regulations and the carbon emissions; (ii) It was observed that for the different subdivided energy-intensive industries, the different levels of technical efficiency had shown various mediation effects. For example, the mediation effects of technical efficiency in the petroleum processing and coking (PPC) industry; papermaking and paper products (PPP) industry, and raw chemical materials and chemical products (RCMCP) industry, were found to be similar to those of the whole energy-intensive industries. Furthermore, the "Porter Hypothesis" had been verified in the nonmetal mineral products (NMP) industry. However, there were no mediation effects observed in the smelting and pressing of ferrous metals (SPFM) and smelting and pressing of nonferrous metals (SPNM) industries; (iii) In this study, in accordance with the regression results of the double-threshold models, it was found that for the energy-intensive industries as a whole, the carbon emission reduction effects of environmental regulations had become stronger with the increases in technical efficiency. For the PPP and RCMCP industries, there was an inverted U-shaped relationship observed between environmental regulations and carbon emissions when the technical efficiency was taken as the threshold variable. Therefore, based on the research conclusions achieved in this study, some policy recommendations were put forward. • Environmental regulation reduces carbon emission of the energy intensive industries of China. • Technical efficiency plays a partial mediation effect between environmental regulation and carbon emission. • The mediation effects of technical efficiency differ in the subdivided energy-intensive industries. • The "Porter hypothesis" is verified in Nonmetal Mineral Products (NMP) industry. [ABSTRACT FROM AUTHOR]

Green finance can effectively support industrial upgrading and technology development, such as artificial intelligence (AI). In this paper, we attempt to pursue the possibility of a win-win situation for achieving an eco- and tech-friendly society. By asking where and how we could develop green finance and AI innovation simultaneously, this paper conducts an empirical investigation on the influence of green finance on the development of AI in China from 2011 to 2020. Based on the panel data from the 30 provinces, we introduce spatial measurement, policy effect, heterogeneity, and threshold analyses to present deeper insights into the impact of green finance on AI innovations. Indeed, green finance could promote the progress of AI innovation. China's green finance pilot policy is verified to promote the progress of local AI innovations. Furthermore, the spatial spillover effect and regional heterogeneity are observed as well. The promotion effect is most significant in the western area, where the green finance index is relatively low. Besides, the threshold analysis also considers how to increase the marginal effect of green finance in different areas. Finally, several policy recommendations are proposed, which contribute to providing specific directions for the policymakers to improve AI innovation and achieve sustainable development at the same time. [ABSTRACT FROM AUTHOR]

As China's economy continues to grow rapidly, the importance of green and sustainable development is increasingly prominent. In this context, enterprises have undergone significant changes in all aspects of the value creation process. Based on the data of Chinese a-share listed companies from 2011 to 2021, this paper links the digital transformation of enterprises with the green technology innovation of enterprises. The focuses on the relationship between the enterprises' digital transformation and the enterprises' green innovation and its Local-neighborhood effect. Research shows that the digital transformation of enterprises will promote the enterprise green technology innovation, and this relationship will have a Local-neighborhood effect in different regions, and this spatial spillover effect is mainly achieved through the transfer of high-tech industries between regions. The results of heterogeneity test show that the effect of green technology innovation is the strongest in Beijing-Tianjin-Hebei economic circle, and the weakest in Pearl River Delta economic circle. Based on the spatial econometric model, this paper provides empirical evidence for the government and the state to formulate the regional development strategy of enterprises' digital transformation and green innovation. • Spatial panel Durbin model reveals digital transformation's impact on green technology innovation and regional spillover. • The effect of digital transformation of enterprises on their own green technology innovation has a "local-neighborhood" effect. • The spatial spillover effect is mainly realized through the transfer of high-tech industries between regions. • The strongest green technology innovation effect is found in the Beijing-Tianjin-Hebei economic circle. [ABSTRACT FROM AUTHOR]

The widespread use of digital technology has driven a huge change in the way payments are made. Based on the micro-data of the China Family Panel Studies (CFPS), this paper explores the relationship between mobile payment and carbon emissions from the consumption side. With the exogenous impact of Alipay's "Collecting Five Blessings" campaign, this paper finds that mobile payment significantly increases household consumption carbon emissions, but the marginal effect is gradually decreasing. Mechanism analysis shows that mobile payment mainly realizes the above impact through promoting the increase of consumption expenditure and upgrading of consumption structure. Further analysis indicates that carbon reduction policies introduced by the Chinese government in the personal consumption sector can mitigate the carbon emissions growth associated with mobile payments. Still, there is a need to strengthen policy measures further to effectively address the issue of rising carbon emissions from household consumption. [ABSTRACT FROM AUTHOR]

This paper aims to study the significance of China's Industrial Structure Rationalization (ISR) in reducing carbon emissions. To this end, this study uses panel data from 30 Chinese province from 2000 to 2019 to measure the Industrial Structure Rationalization of each province by calculating the Thiel index, base on which a nonlinear autoregressive lagged distribution (NARDL-PMG) model is established to explore the impacts of industrial structure rationalization on carbon emissions. The results show that: (1) There still exist significant regional differences between Eastern and Central-Western regions in industrial structure as illustrated by the ISR index. The industrial structure in Eastern region is more rational; (2) In the long run, the carbon emission in China will drop when the industrial structure becomes more rational; (3) However, in the short run, the carbon emission in China will increase when the industrial structure becomes more rational. Besides the findings above, the major difference between this paper and the extant researches is that this paper pays attention to the relationship between industrial structure rationalization and environmental quality by investigating the asymmetric influences of industrial structure rationalization index's positive and negative shocks on carbon emission, which lays solid foundations for government aiming to set more detailed policies. • Focus on the impact of rationalization of industrial structure on CO2 emissions. • Focused on the linear relationship between industrial structure and carbon emissions. • Attempts to analyze three regional pairs from the East, Central and West regions. • Provide a reference for developing countries to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Under the background of high-quality development, the e-commerce industry needs to seek more comprehensive development, and the logistics industry should not only maintain higher efficiency, but also meet the requirements of green and low-carbon transportation. This study aims to investigate the link between the logistic density and the proportion of e-commerce transaction scale. There are few studies on how logistics density affects the development of e-commerce quantitatively. In order to solve this gap, this study establishes an impact model of high-quality growth of e-commerce, and based on Solow production model, constructs a calculation method of logistics density, and analyzes the impact mechanism of logistics density on the scale ratio of e-commerce transactions. Using the bidirectional fixed effect model, this paper makes an empirical analysis of the panel data of 31 provinces consisting of 248 observations and autonomous regions in China from 2014 to 2020. The results show that logistic density has a positive and significant impact on the growth of e-commerce, thus promoting the optimization of economic structure. The acceleration of logistics density decreases the expansion of the ecommerce. Finally, there are obvious regional differences between the development of e-commerce and logistics infrastructure in China. Finally, based on the empirical result, this paper puts forward recommendations for government and companies. [ABSTRACT FROM AUTHOR]

Based on the panel data of 30 provinces in China from 2006 to 2016, the Gaussian kernel density estimation was initially used to describe the characteristics of the inter-provincial differences in household energy consumption (HEC), a dynamic panel data model was established secondly to study the main factors affecting HEC, and finally the counterfactual decomposition method was used to calculate the contribution of each factor to the inter-provincial differences in HEC. The research results are shown as follows: First, the inter-provincial HEC in China shows a phenomenon of agglomeration and growth, and the HEC level of different regions presents difference and imbalance. Second, the logarithms of consumption habits, total population and residents' income have significant effects on the logarithm of HEC, the influence coefficients are 0.191, 0.073 and 0.745, respectively; HEC not only has significant inertia characteristics, but also has certain population size effect and wealth effect. Third, the logarithms of technological progress, urbanization and household energy price have significant effects on the logarithm of HEC, the influence coefficients are 0.864, 0.195 and −0.346, respectively; the HEC saved by technological transformation is not sufficient to offset the increase in HEC demand, urbanization can improve HEC significantly, but the household energy price significantly inhibits HEC. Finally, from the perspective of contribution, the total population, residents' income and urbanization contribute a lot to the inter-provincial differences, totaling 73.02%. The possible innovations of this paper are as follows: First, the contribution of the influencing factors to the difference of inter-provincial HEC is studied, which is rarely seen in the previous literature. Second, compared with traditional decomposition method, counterfactual decomposition method is more convenient for economic interpretation. Third, the divergent conclusions of scholars are pointed out in this paper, and the actual impact of influencing factors on HEC are clarified. Image 10086681 • The level of inter-provincial HEC shows difference and imbalance. • HEC has significant inertia characteristics, population size effect and wealth effect. • HEC saved by technology is not sufficient to offset the increase in HEC demand. • Total population, residents' income and urbanization contribute 73.02%. • The statistical analysis tool used in this paper is Stata15. [ABSTRACT FROM AUTHOR]

China facing the challenge of coordinated development of "ecology, economy, and well-being". Scholars have conducted some research on the relationship between enviromental regulation and employment, but there is less research on the role of clean technology innovation in the employment effect of environmental regulation, which is the purpose of this paper. Using the panel data of 22 industrial sectors in China, the paper uses the number of clean technology patents to measure the level of clean technology innovation, and examines the moderating effect of clean technology innovation in the employment effect of environmental regulations. The results show that: (1) With the gradual improvement of environmental regulation, the impact of environmental regulation on employment presents the characteristics of inhibition first and then promotion. (2) Clean technology innovation has a moderating effect on the employment effect of environmental regulation. It should encourage the green upgrading of traditional technologies, support the development and optimization of private enterprises in various industries, so as to promote enterprises to effectively reduce pollution emissions and create jobs through green technology upgrading at the initial stage. [Display omitted] [ABSTRACT FROM AUTHOR]

The role of digital technology in structural change of three major industries has been widely recognized, but its influence on the internal cleanliness change of the industry has not been confirmed. Based on panel data of 36 industrial sub-sectors in China from 2002 to 2020, this paper discusses the mechanism of digital technology driving the cleanliness of industrial structure from a heterogeneity perspective. The theoretical model indicates that variations in output growth across different industries can be attributed to total factor productivity (TFP) and factor distortions, and the heterogeneous contribution of digital technology to TFP and factor distortions leads to the change of industrial structure. The empirical results show that digital technology can not only promote innovation-driven development by increasing total factor productivity, but also help factor-driven development by reducing factor distortion. Heterogeneity tests show that digital technology contributes to the cleanliness of industrial structure, and polluting industries are mainly driven by factors, while cleaning industries are mainly driven by innovation. Therefore, it is necessary to correct the application direction of digital technology in time to better empower innovative development and clean production. [ABSTRACT FROM AUTHOR]

Smart energy plays an important role in alleviating energy poverty in China in the context of the new technological revolution and industrial change. This paper uses China's smart pilot policy as a quasi-natural experiment, employing China's provincial panel data from 2011 to 2022, measuring energy poverty indices based on a projection pursuit evaluation model, and conducting a quasi-natural experiment using a synthetic control method to assess the effect of smart energy on energy poverty and specific mechanisms of action. The study found that smart energy has a specific and significant impact on energy poverty, but the effect differs in different regions depending on the construction cycle and energy endowment. In the mechanism test, smart energy significantly alleviates energy poverty through the mechanisms of improving energy supply capacity, improving energy payment capacity, and improving energy cleanliness. The results of the study provide empirical references for regional solutions to energy poverty and the planning of smart energy construction. [ABSTRACT FROM AUTHOR]

The coordination of economic development and ecological conservation has emerged as a global trend for sustainable development. This paper utilizes the "Broadband China" policy as a quasi-natural experiment, employing panel data from 279 prefecture-level cities spanning from 2006 to 2019. By constructing a spatial difference-in-differences (SDID) model, it examines the impact of digital infrastructure (DI) on industrial ecology (IE). The study finds that DI enhances both local and neighboring IE, with a spatial attenuation boundary of 600 km for IE impacts on neighboring cities. DI primarily facilitates the transformation of IE by promoting green technology innovation and expediting factor mobility. Heterogeneity analysis conducted using a spatial difference-in-difference-in-differences (SDDD) model reveals that DI has a greater impact on IE in resource-based cities, highly marketized regions, small-scale cities, and eastern regions. This research provides a novel perspective for exploring the transformation of IE theoretically and offers practical insights for leveraging digitization to promote IE. [ABSTRACT FROM AUTHOR]

Digital technologies are a key driver of carbon peaking and carbon neutrality. However, as the physical foundation supporting digital technology, how digital infrastructure affects carbon emissions is unclear. Based on the panel data from 2008 to 2019, this paper examines the impact of the Broadband China Policy on carbon emissions by adopting a multi-period difference-in-differences (DID) method. The empirical findings indicate that, first, digital infrastructure development plays a significant role in reducing carbon emissions in China. Second, the Broadband China Policy significantly reduces carbon emissions especially in China's low-carbon emission regions, high-level digitization regions, and non-resource-cursed regions. Third, the implementation of the Broadband China Policy facilitates carbon emissions reduction through the promotion of green technology progress, optimization of industrial structures, green transformation of residents' lifestyles, and electrification of energy mix. Finally, the Broadband China Policy has a positive spatial spillover effect on the carbon intensity in the surrounding regions of pilot cities, but it has no significant effect on the total carbon emissions and per capita carbon emissions in the surrounding regions. The results provide important insights for digital infrastructure construction to achieve a win-win situation for economic development and emission reduction. • It explores the impact of Broadband China Policy on carbon emissions reduction. • Digital infrastructure development has positive impact on reducing carbon emissions. • The reduction effect is heterogeneous in regions with different characteristics. • Carbon emissions can be reduced at both industrial and individual levels. [ABSTRACT FROM AUTHOR]

Recent work has shown that serious environmental incidents may act as trigger events to produce stronger regulatory enforcement in China. After a major pollution incident, Chinese authorities often impose severe penalties on polluters as a means to prevent future incidents and appease the public. In this paper, we examine how this increased regulatory stringency might affect firms' environmental performance. We select Level I (extremely serious) and Level II (serious) environmental incidents from 2009 to 2019 as trigger events. Using city-level panel data on environmental violations, we find a significant deterrent effect of the incidents on violations: in the period following an incident, the number of violations falls roughly by 8%–11%. The effect is primarily driven by the incidents caused by illegal discharge of toxic pollutants. Other incidents, such as production safety accidents or traffic accidents, do not exert significant effects on environmental performance. [ABSTRACT FROM AUTHOR]

China's economic growth is accompanied by air pollution, which has harmed public health. Former scholars have explored the influencing factors of public health from different perspectives with different methods, among which family income and environmental pollution are two important factors. The paper explored the combined effects of economic level and air pollution on public health at the micro and macro level using the multivariate ordered Logit model and panel data regression model. A comparative analysis was also explored between China's eastern and western regions. The results demonstrated that: (1) Both at the micro and macro level, economic level was positively correlated with public health, while air pollution was negatively correlated with it. (2) The improvement of the economic level made public health more susceptible to air pollution at the micro level and at the macro level. (3) The higher the economic level, the lower the effect of economic growth in reducing the adverse effects of air pollution on public health. This paper proposed that sustainable economic growth should be pursued, the emissions of air pollutants should be reduced, regional development should be balanced and the development gap between China's eastern and western regions should be narrowed. [ABSTRACT FROM AUTHOR]

In contrast to the surge of attention to China's business registration reform per se , the environmental externalities of the reform have been somewhat neglected by mainstream academics. Adopting the difference-in-differences method alongside propensity-score matching, and utilizing the panel data of 283 cities in China from 2000 to 2013, this paper investigates the impacts of the deregulation reform on PM2.5 concentrations. The results indicate that the business registration reform has contributed to PM2.5 air pollution, with above-average impacts in central areas, but insignificant effects in western China. Furthermore, the treatment effects are stronger in cities with larger entry of small and medium enterprises and greater pressure to achieve targets for local GDP growth. Aiming to draw public attention to the problems arising from the reform, our study advocates necessary environmental regulations on business registration, which lends support to the theoretical view of "public interest" rather than "public choice". • Deregulation reform of business registration increases PM2.5 concentrations in China. • Treatment effects of deregulation reform on PM2.5 air pollution vary widely among regions. • More SME entries and higher targets for GDP growth are associated with stronger effects of deregulation reform on PM2.5. • PM2.5 air pollution should be considered during the deregulation reform in China and other developing economies. [ABSTRACT FROM AUTHOR]

The characteristics of high emissions and high energy consumption in metallurgical industry have brought great challenges to the green and low carbon transition in China. As a low-carbon economic instrument, carbon tax is generally considered to be an effective way to reduce CO 2 emissions through raising energy cost, but whether it will promote the green total factor productivity (GTFP) of China's metallurgical industry is still unanswered. Under this background, this paper uses provincial panel data over years 2000–2015 to investigate the impact of carbon taxation on GTFP of metallurgical industry from the perspective of inter-fuel and inter-factor substitution. The lock-in mechanism is also incorporated in the three-stage estimation model to better reflect the asymmetric price response of factors and fuels. The results reveal that the slow marketization process of energy price and the rigid demand for energy in China's metallurgical industry hinder the substitution effect of energy. The implementation of carbon tax has limited effect on energy-saving and CO 2 reduction in the metallurgical industry of China and levying a carbon tax has a negative effect on GTFP during the research period. Therefore, the government should not achieve CO 2 reduction targets at the expense of green economic growth. GTFP is suggested to be considered in future assessment criteria in the process of transforming to low-carbon economy. Image 1063 • We estimate the inter-fuel and inter-factor substitution in China's metallurgical industry. • The Sequential- Malmquist-Luenberger index is used to measure GTFP. • The impact of carbon tax on GTFP of China's metallurgical industry is measured. • The government should not reduce CO 2 emissions at the expense of green economic growth. [ABSTRACT FROM AUTHOR]

One of the critical challenges facing China is environmental pollution caused by insufficient use of clean energy. This paper empirically investigates the impact of rural labor mobility on household clean energy use using data from the China Family Panel Studies (CFPS). The results indicate that labor mobility significantly promotes the adoption of clean energy by rural households, with income effects and information channel effects serving as the underlying mechanisms. The study also finds that health risks, as an important consideration for household energy use choices, enhance this positive effect. Furthermore, heterogeneity analysis reveals that labor mobility has a greater impact on households with lower levels of education, lack of social security, and those located in central and western regions. Therefore, the government should take measures to increase the income of the rural migrant population and continuously widen the information channels for rural households to promote clean energy use. The findings of this study provide a new perspective and evidence for understanding household energy use behavior in China, offering valuable insights for policymakers aiming to expand the use of clean energy. • Labour mobility significantly contributes to clean energy use in rural households. • Income effects and information channel effects are the main mechanisms of action. • Health risks faced by households play a moderating role. • Heterogeneity in region, educational attainment, social security status will influence the effect of labour mobility. [ABSTRACT FROM AUTHOR]

Digital economy development (DED) empowers rural habitat (RH) improvement and promotes the construction of harmonious villages. Based on a panel data of 30 provinces in China from 2013 to 2019, this paper empirically tests the impact of DED on RH and its endogenous mechanism in multiple dimensions using panel fixed effects model and spatial Durbin model. The results show that DED significantly improves RH, which remains robust after a series of robustness tests and dealing with endogeneity issues. The mechanism analysis shows that DED helps to bring into play the rural resource allocation effect, the innovation and entrepreneurship effect, and the carbon emission reduction effect, and improves the RH through these three effects. Further study finds that the digital application divide and regional divide are the main barriers to digital technology enabling RH improvement, there is a spatial spillover effect of DED, which helps to promote the improvement of RH in neighboring areas. The results of the study can provide theoretical support and decision-making reference for the construction of digital villages and the balanced regional development of RH in China. • Indicator system of digital economy and rural habitat was constructed. • Digital economy development significantly boosts rural habitat. • Resource allocation, rural entrepreneurship, and carbon reduction are effective transmission mechanisms. • Digital application divide has a heterogeneity impact. • The spatial spillover effect of the digital economy is significant. [ABSTRACT FROM AUTHOR]

China is actively advancing the integration of digital and real industrial economies, fostering a mutually beneficial cycle that could potentially drive new momentum for eco-friendly industrial development. The empowering effect of digital-real integration on industrial green transformation (IGT) requires urgent exploration. Based on China's industrial sector panel data from 2010 to 2020, this paper empirically investigates the relationship between digital-real integration and IGT and delves into its internal mechanism to verify the above hypothesis. Meanwhile, it analyzes the heterogeneous effects of digital-real integration on IGT, considering variations in industrial technology levels and the sources of such integration. The results demonstrate a positive impact of digital-real integration on IGT in China. The green technology and scale effects play pivotal roles in unleashing the green benefits of digital-real integration in the industrial sector. Notably, the contribution of digital-real integration to IGT varies across industrial subsectors with distinct technology levels. There is heterogeneity in the enabling effect of digital-real integration from different sources on IGT, and the integration of digital services and the real industrial economy has yet to achieve the expected green benefits. Our findings provide new scientific evidence for managers and policymakers in developing countries like China to promote industrial digitization and sustainable growth. This work informs the future discussion on digital-real integration topics from a global context. [Display omitted] • The degree of digital-real integration in China's industrial sector is estimated. • Digital-real integration significantly promotes industrial green transformation. • Digital-real integration acts as a driver through green technology and scale effects. • Digital-real integration from different sources varies in green empowerment effects. [ABSTRACT FROM AUTHOR]

Despite ecotourism certification's efficacy as a potential environmental management tool for promoting sustainable development, the applicability of Western ecotourism certification patterns in China and the environmental effects of China's ecotourism certification remain unclear. Based on China's Prototype-zone of National Ecotourism Attractions (PNEA) certification, this paper aims to provide empirical evidence on the causal relationship between ecotourism and low-carbon sustainable development in relation to public environmental concerns. The multiperiod Difference-in-Differences (DID) model is set up to examine the supervision of PNEA certification on regional carbon emissions based on the panel data from 285 Chinese prefecture-level cities in 2011–2017. Results demonstrate that PNEA approval can reduce regional carbon emissions by 1.1% per capita, and this effect would increase over time. Heterogeneity analysis shows that the carbon emission reduction impact is significantly higher on midwestern cities, resource-dependent cities, and cities with net population inflow. Furthermore, the determinants of public environmental concerns, such as PNEA's functions of tourism economic development and environmental education, are crucial for low-carbon sustainable development. The findings quite clearly account for the contributions of ecotourism certification in promoting sustainable development and the benefits of effective policy instruments. • The PNEA certification implemented by China's central government is different from the Western ecotourism certifications. • The approval of China's unique ecotourism certification can reduce regional carbon emissions by 1.1% per capita. • The economic development function and environmental education function are key to promoting public environmental concerns. [ABSTRACT FROM AUTHOR]

Under the goal of "carbon peaking" and "carbon neutrality" in China, it is significant to explore whether green finance contributes to carbon emission reduction. Therefore, based on the panel data of 30 provinces in China from 2005 to 2020, this paper empirically examines the impact of green finance on carbon emissions and its mechanism using the FE model, GMM model, DID, and the mediating effect model. Results find that green finance can significantly promote carbon emissions reduction, and this promotion remains still after robustness tests. The heterogeneity analysis shows that green finance's carbon emission reduction effect is more significant in developed and western regions. Moreover, the results of policy intervention effects confirm that green finance reform and innovation pilot zones (GFRIs) for carbon emission reduction are more pronounced than in other regions. Finally, the mediating effects reveal that industrial structure and green innovation are the core transmission channels through which green finance influences carbon emission reduction. These findings offer meaningful implications for formulating reasonable carbon emission reduction plans and determining the future development direction of green finance. [ABSTRACT FROM AUTHOR]

China's development model of relying on heavy industry has brought huge environmental costs. Serious haze pollution has posed a threat to high-quality economic development and people's healthy life. Exploring the relationship between air pollution and industrial development and promoting the coordinated governance of economy and environment has become an important task in China's new era. Based on the satellite inversion PM2.5 concentrate data and micro industrial enterprise data in China's county-level areas, this paper uses the instrumental variable and two-stage least square (2SLS) method to test the impact of regional air pollution (RAP) on the regional industrial structure upgrading (RISU), and further reveals its impact mechanism. The results show that: (1) RAP has a negative impact on the RISU, and the introduction of instrumental variable and 2SLS method can overcome the endogenous problem of regression. (2) on average, for every 1% increase in PM2.5 concentration, the regional industrial structure height will decrease by 2%. (3) RAP hinders the RISU by affecting enterprises' fixed assets investment and innovation activities. And the sensitivity of innovation activities of state-owned enterprises to RAP is lower than that of other ownership enterprises. According to the research of this paper, some pertinent policies and suggestions are proposed to provide new decision-making basis for national policymakers. [ABSTRACT FROM AUTHOR]

Members of the public may express their desire for environmental improvements and achieve results through varying methods. To achieve change, such things as Google Index, the number of incoming letters, the number of visitors, the proposals of the National People's Congress and the motions of the Chinese People's Political Consultative Conference all play a role. However, studies which theoretically analyze the relationship between public appeals and environmental improvement are relatively scarce. For this reason, this paper uses provincial panel data from 2004 to 2014 to analyze the impact of public appeals on the performance of environmental governance. The results show that, the stronger the public appeals for environmental issues, the greater the government's control over the handling of environmental pollution. In areas with serious environmental pollution problems, including Shanxi and Hebei, the public voice is relatively strong. The impact of the Google index on environmental improvement in central China is stronger than in eastern and western China. By re-measuring the explanatory variables with the number of incoming letters, the number of visitors, the proposals of the National People's Congress and the motions of the Chinese People's Political Consultative Conference, we have discovered that the appeals of ordinary people can have the same impact on environmental improvement as those of social elites. • Relationship between public appeal and environmental performance in China is analyzed. • Environmental appeal in central China does not have a significant effect. • Ordinary people's online environment appeal exerts the same effect with social elites. [ABSTRACT FROM AUTHOR]

China has the largest electricity system in the world, which is undergoing a critical market reform. Based on the panel data in 2000 to 2016 of China, this paper tries to explain theinconsistency between electricity consumption and economic growth. For example, in 2015, GDP growth rate was close to 6.9% but with only 2.9% growth in electricity consumption. However, in 2018, a 6.6% growth in GDP required an 8.5% electricity growth. The results explain the reasons for inconsistency and identify the key factors. We find that the increase in inventory, fixed capital and industrial electricity consumption will narrow the gap when economy grows faster than electricity consumption, and widen the gap on the contrary. Heterogeneity exists among regions, the model and variables seem most convincing in explaining the situation in the western region, which is most similar to the full sample of China. Feedback effect is also observed between electricity consumption and economic growth in most parts of China by Granger test. The findings provides suggestions for the policy makers in making power planning, in an effort to avoid large power shortage or surplus. • Inventory, fixed capital and industrial electricity consumption will impact the deviation. • Impacts on deviation in western region are most similar to the full sample, and eastern region goes opposite. • Feedback effect is observed between electricity consumption and economic growth in most parts of China. [ABSTRACT FROM AUTHOR]

As the basic sector providing basic service and promoting economy development, the increment demand of transport sector has brought much more pressure on the environment. Beijing-Tianjin-Hebei region is the representative region of the advanced region of China and it is significant to analyze how to achieve the low-carbon transport development in Beijing-Tianjin-Hebei region, meanwhile provide reference of green development for other regions. Using the panel data from 1995 to 2016, the paper analyses the driving factor of carbon dioxide emissions from transport sector with two different analytical methods. The results of LMDI show that transportation energy intensity and economic effect is the main factor increasing the carbon dioxide emissions and the contributing factors to the carbon dioxide emissions reduction in the transport sector are the energy structure effect, the freight turnover of unit industrial output effect and the industrialization effect. In different subclasses divided by different threshold variables, industrialization has the positive impact while the coefficients vary, which indicates that appropriate development policies should be formulated in light of the development characteristics of different regions. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of urbanization on provincial energy efficiency in China. Using panel data of 30 Chinese provinces between 2003 and 2014, we adopt a stochastic frontier model to estimate energy efficiency in China, and apply a series of spatial panel data models to tackle spatial dependence of energy efficiency between provinces. Our results show that the overall impact of urbanization on energy efficiency is negative in China. These results are established after controlling for spatial correlation and other confounding factors, and are also robust to various model specifications. We also document that the impact of urbanization on provincial energy efficiency manifests through both a direct negative impact induced by the focal province's urbanization process, and an indirect positive spillover effect caused by urbanization in adjacent areas. [ABSTRACT FROM AUTHOR]

"Carbon Peaking and Carbon Neutrality" is one of the important tasks of China's current and future economic construction and development, but the carbon emission reduction effect of High-speed rail (HSR) has not yet been fully studied. In this paper, based on the panel data of 274 cities in China from 2003 to 2016, we take the opening of HSR in the cities as a "Quasi-natural Experiment", and construct the Multi-period Difference-in-Difference Model to explore whether the opening of HSR can reduce carbon emissions of cities along the route, and use the mediating effect model and moderating effect model to further analyze its internal mechanisms. We find that:①The opening of HSR can significantly reduce the carbon emissions of cities along the route, and the opening of HSR in a city will reduce the carbon emissions of the city by about 2.4% on average, and this carbon emission reduction effect usually manifests significantly in the first year after the opening of HSR, and increases year by year thereafter.②The mechanism test shows that the traffic substitution effect, the optimization of the industrial structure and the promotion of economic agglomeration have partial mediating effect on the influence between the opening of HSR and urban carbon emissions. In addition, the increase in the intensity of government environmental regulations can strengthen the effect of the opening of HSR on reducing urban carbon emissions.③The regional heterogeneity research shows that the opening of HSR has a more significant impact on the carbon emissions of cities in the eastern coastal region and western region of China. Moreover, in the western region, the reduction effect of the opening of HSR on carbon emissions is only reflected in the key cities rather than ordinary prefecture-level cities. This paper provides certain reference significance for promoting low-carbon and green economy and helping China to achieve the "Carbon Neutrality" climate action goal. [ABSTRACT FROM AUTHOR]

Reducing agricultural carbon emissions is an essential lever for mitigating climate change and promoting high-quality agricultural development. Environmental regulation in the form of resource agglomeration, represented by the high-standard farmland construction policy, plays a vital role in the emission reduction process. Using the panel data of 31 provinces in China from 2001 to 2019 and taking the high-standard farmland construction policy as a quasi-natural experiment, this paper constructs a continuous differences-in-differences (DID) model to explore the impact and mechanism of environmental regulation in the form of resource agglomeration (RAER) on agricultural carbon emission reduction. The results show that RAER significantly reduces agricultural carbon emissions by an average of 3.9%. This conclusion still holds after robustness tests such as endogenous tests, eliminating policy interference, and sample reprocessing. This abatement utility is mainly realized through the technique effect of promoting green technology innovation and the composition effect of optimizing crop cultivation structure. Based on the resource attribute characteristics, the agricultural carbon emission reduction effects of RAER are, in descending order, capital and facility. Further study found heterogeneity in four aspects of the effect of RAER on agricultural carbon emission reduction: regional, planted crops, carbon emission sources, and carbon emission intensity. Therefore, decision-makers should deepen environmental regulation reform through resource agglomeration, implement adapting to local conditions for the high-standard farmland construction policy, and promote policy innovation and system optimization of agricultural carbon emission reduction. [ABSTRACT FROM AUTHOR]

The total factor carbon emission performance has been largely used to investigate the effectiveness of climate policies and to support the design of carbon reduction strategies. Despite the important information that this indicator is providing in relation to historical and cross-country trends, no previous studies have been specifically devoted to analyze the persistent and the transient components of the total factor carbon emission performance. By disaggregating the time-variant and the time-invariant elements of the carbon dioxide emission changes, this paper adopts, for the first time, a new methodological approach to decompose the components of the total factor carbon emission performance indicator. Using panel data for selected 30 Chinese provinces for the time-period 1997–2017, this paper combines the environmental production technology, the Shephard distance function, and the stochastic frontier models to measure and investigate the spatio-temporal evolution of the total factor carbon emission performance and to evaluate the effectiveness of Chinese policies. By providing a better understanding of the total factor carbon dioxide emission performance, the proposed methodology is suitable to be replicated across regions, and provides an important opportunity for international comparisons and for the design of coordinated carbon reduction strategies. ⁃ An innovative approach is presented to decompose the persistent and transient TFCP ⁃ TFCP of China is affected by persistent inefficiency with regional disparities ⁃ The economic determinants of persistent and transient TFCP are investigated ⁃ Industrialisation, FDI, technology progress are key determinants of persistent TFCP [ABSTRACT FROM AUTHOR]

Based on the balanced panel data of 260 prefecture-level cities in China from 2005 to 2016, and the quasi-natural experiment of the Pollution Information Transparency Index (PITI) project implemented in 110 prefecture-level cities in 2009, this paper uses the spatial difference-in-differences (SDID) model and the spatial Dubin model (SDM) model to investigate the FDI attraction effect of environmental information disclosure (EID). The results show that EID will significantly promote the inflow of FDI in cities, and this effect will be stronger with the increasing disclosure extent. EID has a siphon effect on FDI, that is, a city that has a better EID will attract more FDI than its neighbors, further intensifying the competition effect of FDI among cities with similar geographical distance, levels of economic development, and Internet penetration. The attraction effect of EID on FDI is mainly present in polluting cities and non-resource-based cities, while the impact on clean and resource-based cities is not significant. • We analyze the attraction effect of environmental information disclosure on FDI. • The effect of PITI project is evaluated with spatial-DID and SDM methods. • Environmental information disclosure has a siphon effect on FDI among cities. • The FDI attraction effect of disclosure extent is heterogeneous in city characters. [ABSTRACT FROM AUTHOR]

The pilot program of low-carbon cities is of great significance for China's overall economic and social development. The construction of low-carbon cities contributes to adjusting the industrial structure, optimizing the energy structure and accelerating institutional reforms. Using the panel data of 285 prefecture-level cities during 2006–2015, this paper takes the pilot program of low-carbon cities as a quasi-natural experiment to detect the impact of the pilot program on industrial structure upgrading and its possible mechanism. The results reveal that the construction of low-carbon cities displays a positive impact on industrial structure supererogation while it has little effect on industrial structure rationalization. Ventilation coefficient is regarded as an instrumental variable to address endogenous problems. The conclusions are still tenable after a series of robustness tests. Mechanism analysis shows that the pilot program can bolster industrial structure supererogation via technological innovation and the reduction of the proportion of high-carbon industries. The regional heterogeneity analysis indicates that the influence of the pilot program on the industrial structure supererogation in the central and western areas is more positive than that in the eastern area, whereas the impact of the pilot program on the industrial structure rationalization is not significant in the three areas. The heterogeneity analysis of environmental law enforcement indicates that the pilot program can more obviously bump up the industrial structure supererogation in cities with strong law enforcement intensity. The impact on the industrial structure rationalization is not evident in cities with weak law enforcement intensity, but the industrial structure rationalization is significantly improved in cities with strong law enforcement intensity. This paper provides insights for realizing the integrated development of low-carbon cities and industrial structure upgrading. • The objective is to optimize the program of low-carbon and facilitate the upgrading of industrial structure. • Industrial structure supererogation and rationalization are considered. • We analyzed the impact mechanism. • The construction of low-carbon cities displays a positive effect on industrial structure supererogation. • The construction of low-carbon cities has little effect on industrial structure rationalization. [ABSTRACT FROM AUTHOR]

This paper provides a pioneering study of the interactive relationship between shadow economy and environmental pollution by applying the data of the 31 provinces in China from 2005 to 2015. Side effects of shadow economy including environment pollution have been proved by plenty of articles, yet still have not attracted enough public attentions. If the severe pollution will in turn further increase the size of the shadow economy, then the environmental situation in the present will lead to an even worse unhealthy economy growth path. This paper firstly adopts MIMIC (Multiple Indicators Multiple Causes) method to calculate the size of shadow economy, then uses the Generalized Method of Moments (GMM) specification to analyze the interplay between shadow economy and pollution in association with environmental regulation, economic growth, foreign direct investment and educational level. The results show that shadow economy and pollution do have a positive interaction between each other, statistically significant at 1% level. Also, both pollution and shadow economy have a U-shaped non-linear relationship with environmental regulation, but an inverse U-shaped non-linear relationship with economic growth. Finally, foreign direct investment (FDI) and education level have positive linear impacts on both pollution and shadow economy, too. But the effect from FDI is weak and less significant. Image 1 • The percentage of shadow economy on GDP is calculated based on MIMIC model. • The possible interaction relationship between shadow economy and pollution is explored. • Environmental regulation and economic growth have non-linear effect on both shadow economy and pollution. • FDI and education level have linear effect on both shadow economy and pollution. [ABSTRACT FROM AUTHOR]

The impact of technical change on economic growth is closely related to the structure of input factors, and guiding technical change towards energy-saving can achieve the dual goals of economic growth and energy conservation. Based on the provincial panel data of 2006–2016, this paper first uses the slacks-based measure model and the bootstrap data envelopment analysis (bootstrap-DEA) to calculate the biased technical change (BTC) index and its factor bias of China's iron and steel industry (ISI). Next, the influencing factors of BTC are examined using panel regression analysis. The results corrected by bootstrap-DEA show that the level of ISI's BTC in China is 1.0110, with a contribution rate of 20.75% to green total factor productivity. Moreover, China's ISI experienced a labor-saving, energy-saving, and capital-using technical change during 2006–2016. In two-factor comparisons, technical change biased towards saving labor in labor-capital and labor-energy, and towards saving energy in energy-capital. The results of regression analysis show that improving energy efficiency, promoting urbanization, expanding production scale and optimizing industrial structure effectively promote BTC and improving energy efficiency is the primary pathway; however, excessive capital deepening has a significant negative correlation with BTC. Based on these results, this paper proposes policy recommendations for ISI's green development. • Biased technical change of iron and steel industry is increasingly significant. • Technical change biases towards labor-saving, energy-saving and capital-using. • An energy-saving technical change exists in the iron and steel industry of most provinces. • Energy efficiency can significantly promote the biased technical change. [ABSTRACT FROM AUTHOR]

Analyzing the influencing factors of environmental pollution is of utmost significance for formulating pollution control strategies. However, the extant research did not take into consideration the spatial effects, which may result in an insufficient understanding of the results. To explore the spatial agglomeration of environmental pollution, the externalities of economic units are integrated into environmental pollution research. Using a panel data from 2005 to 2017 of 30 Chinese provinces, this paper quantitatively analyzed the main driving factors affecting environmental pollution by utilizing the spatial Durbin model (SDM). To better test the marginal effects from the spatial dependence, the influence of each contributing factor is further decomposed. The main results are as follows: (1) The quartile maps of China's environmental pollution show obvious characteristics of spatial disparity and clustering. (2) Owing to the correlation and similarity between economic units, China's environmental pollution shows a steady spatial agglomeration effect among regions. (3) Analysis of the SDM indicates that per capita GDP, technology, urbanization, and population exert different influences on environmental pollution. Moreover, the impacts of urbanization and foreign direct investment on environmental pollution vary essentially among regions, and one change in the abovementioned variables will not only exert influence on environmental pollution in one region but also extend its spatial effects in neighboring regions through a spatial transmission mechanism. Also, an inverted U-shaped nexus is also supported for environmental pollution accordingly. According to the empirical results of this paper, several major policy implications are proposed. [ABSTRACT FROM AUTHOR]

The growth effect of collaborative agglomeration of manufacturing and producer service industries is receiving increasing attention from scholars. However, few studies have explored whether and how collaborative agglomeration of manufacturing and producer service industries affects green innovation. To bridge this gap, using the methods of the system generalized method of moments, the moderating effect, and the threshold effect, and employing the panel data of 30 provinces of China for 2003–2017, this paper studies the effect of industrial collaborative agglomeration on green innovation and how this influence fluctuates when marketization is included. The main findings are as follows: (1) During the sample period, industrial collaborative agglomeration generally had a blocking effect on China's green innovation. A 1% increase in industrial collaborative agglomeration indicated a 0.461% decrease in green innovation efficiency. (2) Marketization can be an essential and efficient factor to correct the negative impact of industrial collaborative agglomeration through a moderating effect. (3) With the improvement of marketization, industrial collaborative agglomeration exhibits a U-shaped effect on green innovation, with the turning point occurring when the marketization index is 6.21. (4) As of 2017, 21 provinces have successfully exceeded the threshold of marketization, indicating that the current industrial collaborative agglomeration has been able to effectively improve China's green innovation efficiency. However, the other nine provinces still trail behind them in marketization reforms, with industrial collaborative agglomeration continuing to negatively affect green innovation. (5) This paper concludes with recommendations to improve green innovation through industrial collaborative agglomeration and market reform. Image 1 • Our research model links marketization, green innovation and industrial collaborative agglomeration. • We explore whether and how industrial collaborative agglomeration affects the green innovation. • Marketization moderates and promotes industrial collaborative agglomeration's influence on green innovation. • As marketization deepens, industrial collaborative agglomeration's effect on green innovation shows a U-shaped curve. [ABSTRACT FROM AUTHOR]

Environmental regulation not only has a direct impact on environmental pollution, but also has an indirect impact on air pollution. This paper collects the panel data of 253 prefecture-level cities in China between 2004 and 2016. First, we used the Two-Stage Least Squares (2SLS) method to empirically analyze the direct and indirect effects of environmental regulation on environmental pollution. Second, this paper uses the panel threshold regression model to explore the non-linear effects of environmental regulation on environmental pollution. The results of our analysis indicate: (1) environmental regulation can directly alleviate environmental pollution. Additionally, technology innovation and industrial structure adjustment due to environmental regulation are also conducive to improving China's environmental situation. The direct effects of environmental regulation are greater than the indirect effects; (2) the influence of environmental regulation on environmental pollution has a single threshold characteristic; (3) we also found that some control variables can significantly impact environmental pollution. The innovation of this article is mainly to explore the direct and indirect effects of environmental regulation on environmental pollution. • The effect of environmental regulation on environmental pollution is studied. • The Two-Stage Least Squares (2SLS) method is used in this paper. • The panel threshold regression model is used to explore the non-linear effects. [ABSTRACT FROM AUTHOR]

This paper uses a panel data of 37 industrial sectors in China from 2003 to 2015, adopts the specification of a fixed effect model, and studies the influence of the coordinated development of inward and outward FDI on industrial pollution emissions. A negative correlation is found between the coordinated development level of inward and outward FDI and the industrial pollution emission level, indicating a pollution emission reduction effect associated with the coordinated development of inward and outward FDI. Furthermore, the moderation effect of global value chain position indicates that an industry can benefit from a stronger emission reduction effect associated with the coordinated development level of inward and outward FDI if it evolves to a higher position in the global value chain. In addition, the heterogeneity analysis indicates that industries with lower energy intensity, a lower ratio of state-owned enterprises, and with more green patents benefit from a more obvious effect on reducing industrial pollution emissions that is caused by the coordinated development of inward and outward FDI. [ABSTRACT FROM AUTHOR]

Prior studies have explored the relationship between public environmental concerns and air pollution, but the interaction effects and spatial factors under a systematic framework have been ignored. This paper investigates the interaction effect between public environmental concern and air pollution, moreover, a spatial panel simultaneous equation approach is employed to reduce the endogenous interference and the potential impact of spatial factors. Based on the balanced panel data of 269 prefecture-level cities in China from 2011 to 2017, we find that a 1% increase in public environmental concern will lead to a 0.049% decrease in PM 2.5 concentration, while a 1% increase in PM 2.5 concentration will lead to a 1.398% increase in public environmental concern. Meanwhile, there is a significantly spatial spillover effect of both public environmental concern and air pollution to the surrounding areas. Furthermore, our findings suggest that public environmental concern reduces air pollution by promoting government environmental regulation, and air pollution promotes public environmental concern by threatening the health of the residents. In addition, the results of heterogeneity analysis show that the interaction effect of public environment on air pollution significantly differs across regions with different heating characteristics and economic development levels. Practicable policies to promote favorable feedback on public environmental concern and air pollution are suggested. [ABSTRACT FROM AUTHOR]

Carbon footprint (CF) and inequality reductions were two of the most important sustainable development goals. However, there was a lack of understanding of the latest equality of carbon footprint across regions. Based on the multi-regional input-output table and the China Family Panel Studies survey data of 17 provinces, this paper examined the evolution of carbon footprint and inequality in China. The results showed a stark disparity between regions and a declined inequality in the last few years. Specifically, the CF per capita in northern provinces (Liaoning, Shanxi, Heilongjiang, Shandong and Shaanxi) exceeded the average level in 2017. From 2015 to 2017, the carbon inequality showed a downward trend, with a national CF-Gini coefficient decrease from 0.31 to 0.28. Meanwhile, the gap between CF per capita in urban areas and rural areas was declining, with a growth rate at 18% and 32% from 2015 to 2017, respectively. In addition, CF per capita from various consumption categories indicated that household equipment and daily necessities, residential, transportation and communication were the three most important sources, with a downward trend from 2015 to 2017. This study would provide policymakers with deep insights into policies to achieve just transition. [ABSTRACT FROM AUTHOR]

Based on China's provincial panel data from 2011 to 2019, this paper examines the complex impact of new energy industry agglomeration on green innovation efficiency from the perspective of spatial mismatch of research and development (R&D) resources. The super slack-based measured directional distance function (super-SBM-DDF) is applied to measure the green innovation efficiency, while the least square dummy variable model (LSDV) is implemented to evaluate the mismatch of R&D resources in the new energy industry. Based on the generalized method of moment (GMM), the moderating effect model, and the dynamic threshold model are employed to investigate the threshold effect of new energy industry agglomeration on green innovation efficiency and the moderating effect of spatial mismatch of R&D resources. We come to the following findings. First, the agglomeration of China's new energy industry exhibits a "west-east-central" gradient distribution. In the meantime, there is a widespread insufficient mismatch of R&D resources in the majority of regions. Second, the agglomeration of the new energy industry can significantly boost the efficiency of green innovation. Moderate agglomeration can have a marginally enhancing effect, whereas excessive agglomeration will obscure the green innovation effect of new energy industry agglomeration. Third, the relationship between the new energy industry agglomeration and green innovation efficiency is negatively moderated by the mismatch of R&D resources, while the moderating effect is amplified by the mismatch of innovation financial resources. Fourth, there are two inflection points in the positive impact of new energy industry agglomeration on green innovation efficiency when the innovation resource mismatch is assigned as the threshold variable. [Display omitted] • The relationship among industry agglomeration, R&D resources mismatch and green innovation efficiency is investigated. • The mismatch of R&D resources is calculated by LSDV. The green innovation efficiency is measured by super-SBM-DDF. • The new energy industry presents a gradient distribution of "west-east-central" and there is a mismatch of R&D resources. • R&D resources mismatch hinders the positive effect of new energy industry agglomeration on green innovation efficiency. • Dynamic threshold panel model reveals the nonlinear relationship between agglomeration and green innovation efficiency. [ABSTRACT FROM AUTHOR]

The Chinese government, like many others around the world, has set carbon targets that by the time of 2020, to achieve a 40–45% decrease in CO 2 emissions per GDP compared with that of 2005. In some parts of China, short-term economic needs have dominated urban planning, while in other areas—especially in recent years—emphasis has shifted to the quality of urban development. This paper contributes to the literature as placing emphasis on the quality of land use as well as detecting possible causal links between land urbanization quality (LUQ) and carbon emissions using panel data from at provincial level from 2004 to 2013. The results show that: There is bidirectional long-run causal relation between carbon emission and LUQ on the national scale, which implies that the two are jointly determined and that they simultaneously affect each other. As the case of recovery to the equilibrium, Eastern regions have the fastest speed, followed by the Central and the Western ranked at last. Further, what worth noting is LUQ contribute to reducing carbon emissions, indicating the ongoing industrial restructuring and green developments have come into force. Moreover, we deduce that the Central region has the highest potential for energy conservation. We further propose that emphasis should be placed on promoting the degree of LUQ and energy conservation in the implementation during the New-type Urbanization Plan (2014–2020). [ABSTRACT FROM AUTHOR]

Green technology is a crucial way to achieve energy conservation, emission reduction and economic growth. Most of the previous literature has studied the influence of green technology on carbon emission from the regional perspective. This paper discusses the direct role in terms of industry of seven green technologies under the International Patent Classification (IPC) Green Inventory classification standard on the reduction of carbon intensity and the indirect impact of technology vertical spillovers generated by transmission via the intermediate input products channel on carbon intensity. Based on empirical research that was conducted by adopting an improved regression on the population, affluence and technology (STIRPAT) model using the panel data of 17 categories of industries in China from 2000 to 2015, the indirect effect was more significant than the direct result, as every green technology innovation level and technology spillover capacity was increased by 1%, the carbon intensity reduced by 0.1303% and 0.1558%, respectively. Energy conservation technology played a direct role in the reduction of carbon intensity and achieved the best results, and its impact was 1.76 times that of waste management technology, which had the weakest effect. Transportation emission reduction technology played an indirect role in the reduction of carbon emission intensity and achieved the best results; its impact was 2.13 times the average value of all types of technology spillover effects. Finally, the paper analyzes seven types of green technology spillover capacities and the heterogeneity in the reduction of carbon intensity efficiency and provides some relevant policy suggestions. • The green technology has been examined from the industry perspective. • The green technology vertical spillovers can reduce the carbon intensity more significantly. • Distinguished seven types of green technology. • Discovered the key kinds of green technology. • Explored the heterogeneity of spillover capacity and their effects on carbon intensity. [ABSTRACT FROM AUTHOR]

In the early stages of China's economic development, the ecological and environmental problems left over from the extensive approach were gradually exposed. Urban environmental problems such as haze attack and water pollution not only related to residents' happiness, but also challenged urban economic structural transformation and sustainable development. Based on the panel data of 211 cities in China from 2007 to 2016, this paper uses the entropy weight method to construct the evaluation index of urban living environment, and empirically analyzes the impact of improving living environment on urban innovation. The results show that for each 1% improvement in the urban living environment, the urban innovation raises by 34.5835; there is an inverted-U relationship between the two. In the analysis of the transmission mechanism, each 1% increase in the concentration of high-quality innovative talents will raise the urban innovation by 4.6548; and each 1% increase in foreign direct investment (FDI) spillover effect will reduce the urban innovation by 0.6498. The results of the geographic weighted regression (GWR) model show that the urban living environment, high-quality innovative talents gathering, and FDI spillover effect have obvious spatial differences in urban innovation. In short, this paper provides innovative inspiration for governments and enterprises to balance ecological environmental protection and sustainable urban development. Image 1 • The improvement of urban living environment can significantly promote urban innovation. There is an inverted "U" relationship between the two. • The high-quality innovative talents gathering promotes urban innovation;FDI spillover effect cannot. • Spatial differences in the impact of the three on urban innovation. [ABSTRACT FROM AUTHOR]

Governments often turn to subsidies to boost enterprises' innovation activities, which gives subsidized enterprises room for allocating the subsidies among different innovation activities. Taking insights from institutional logic theory, this paper proposes that enterprises exhibit different subsidy-allocation behaviors between nongreen and green innovations and that the positive effect of subsidies on nongreen innovation is greater than that on green innovation due to the double-spillover problem that is pertinent to green innovation. Further, this paper argues that innovation intensity varies from privately-owned enterprises to local and central state-owned enterprises and that the underlying reason for this phenomenon is that enterprises with different ownership structures behave with different institutional logics, face different environmental and innovation pressures, and hold different innovative resource and capability endowments. We test these hypotheses by using longitudinal data (2010–2015) on 175 publicly-traded firms in the pharmaceutical industry in China. Overall, the results support most of the hypotheses. • The effects of governmental subsidies on green and nongreen innovations were examined. • The moderating role of ownership types between innovation subsidies and green/nongreen innovation was examined. • Five-year panel data from 175 publicly traded Chinese pharmaceutical firms were used to test the hypotheses. [ABSTRACT FROM AUTHOR]

Using balanced panel data of 285 prefecture-level cities in China from 2003 to 2013, this paper studies the impact of High-speed rail (HSR) on environmental pollution. The results by Difference-in-Difference (DID) method show that HSR significantly reduces environmental pollution by 7.35% in China. In addition, we use Propensity Score Matching and DID (PSM-DID) method, as well as the instrumental variable method to deal with the endogenous problem, and we find that the results remain robust. HSR will not automatically reduce environmental pollution, but through the technical effect, allocation effect and substitution effect, which are the main factors to reduce environmental pollution. In addition, we also make further robustness tests for the conclusions of this paper. Further analysis shows that in cities with larger city scale, higher level of economic development, more abundant human capital or stricter environmental supervision, the pollution reduction effect of HSR is more significant. This paper provides some policy implications for improving city environmental quality and building an environment-friendly society. [ABSTRACT FROM AUTHOR]

The role of financial agglomeration in China's green development has generated many fascinating debates for scholarly research, but few studies have considered environmental effects of financial agglomeration from the spatial spillover perspective. Taking both natural and socio-economic factors into accounts, this paper explores the interaction between financial agglomeration and green development using the panel data of 285 prefecture-level Chinese cities from 2003 to 2015. The results show that both financial agglomeration and green development have demonstrated a trend of spatial convergence. Secondly, financial agglomeration can promote the green development of both focal and surrounding cities. Thirdly, financial agglomeration is conducive to enhance regional green development level in Western China, while only Eastern and Central China witness significant spatial spillover effects. Fourthly, the direct effect of financial agglomeration on green development at the city level exists, whereas megacities and large cities witness a significantly adverse spatial spillover effect. This paper also presents policy recommendations. [ABSTRACT FROM AUTHOR]

For economic activities, energy is a necessary component of production. As the world's largest energy consumer and carbon emitter, China faces greater resource constraints and environmental pressure in the background of global climate change, improving energy efficiency is the inevitable path for long-term development. However, the energy efficiency in China at this stage is relatively low, thus improving energy efficiency is urgent. Based on the panel data from the database of Chinese industrial enterprises and the database of Chinese industrial enterprises' pollutant emissions between 2003 and 2012, this paper empirically conducts a thorough investigation on the nonlinear impact of spatial agglomeration and enterprises' energy efficiency, and further examine its heterogeneity and mechanisms. The results show that: (1) There is a significant U-shaped link between spatial agglomeration and enterprises' energy efficiency. (2) Based on agglomeration externalities, scale effect, learning effect, competition effect, and policy effect are the internal mechanisms through which spatial agglomeration impacts on enterprises' energy efficiency. (3) The effects of spatial agglomeration on enterprises' energy efficiency are influenced by technology level, energy consumption level, agglomeration patterns, and enterprise characteristics. Based on the empirical findings, we suggest that enterprises take full advantage of the benefits brought by spatial agglomeration, and that the government encourage the growth period of spatial agglomeration to become more profound, more synergetic, and more diverse. [ABSTRACT FROM AUTHOR]

While household conversion to clean cooking fuels is well documented, the peer influence of neighbors on rural households using clean cooking fuels has not been investigated. This study examines the influence of neighbors on rural households switching to cleaner cooking fuels. Based on data from the 2018 China Family Panel Studies, this paper uses a spatial econometric model to analyze the neighborhood effects in the process of adopting clean cooking fuels among rural households in China. The findings show that neighborhood effects influence the adoption of clean cooking fuels by rural households in the same village through social norms and social multiplier effects. Neighborhood effects also indirectly promote the adoption of clean cooking fuels by rural households through the Internet. There is heterogeneity in the neighborhood effects on the adoption of clean cooking fuels by rural households. Therefore, this study recommends related policies to facilitate the transition to clean cooking fuel in rural regions. • Neighborhood effects influence rural households' adoption of clean cooking fuels. • Social norms effects facilitate rural use of clean fuels for cooking. • Social multiplier effects accelerate rural use of clean fuels for cooking. • Internet's a bridge between neighbors' effects and rural use of clean cooking fuels. • There is heterogeneity of neighbors' effects on rural use of clean fuels for cooking. [ABSTRACT FROM AUTHOR]

For economic activities, energy is a necessary component of production. As the world's largest energy consumer and carbon emitter, China faces greater resource constraints and environmental pressure in the background of global climate change, improving energy efficiency is the inevitable path for long-term development. However, the energy efficiency in China at this stage is relatively low, thus improving energy efficiency is urgent. Based on the panel data from the database of Chinese industrial enterprises and the database of Chinese industrial enterprises' pollutant emissions between 2003 and 2012, this paper empirically conducts a thorough investigation on the nonlinear impact of spatial agglomeration and enterprises' energy efficiency, and further examine its heterogeneity and mechanisms. The results show that: (1) There is a significant U-shaped link between spatial agglomeration and enterprises' energy efficiency. (2) Based on agglomeration externalities, scale effect, learning effect, competition effect, and policy effect are the internal mechanisms through which spatial agglomeration impacts on enterprises' energy efficiency. (3) The effects of spatial agglomeration on enterprises' energy efficiency are influenced by technology level, energy consumption level, agglomeration patterns, and enterprise characteristics. Based on the empirical findings, we suggest that enterprises take full advantage of the benefits brought by spatial agglomeration, and that the government encourage the growth period of spatial agglomeration to become more profound, more synergetic, and more diverse. [ABSTRACT FROM AUTHOR]

While household conversion to clean cooking fuels is well documented, the peer influence of neighbors on rural households using clean cooking fuels has not been investigated. This study examines the influence of neighbors on rural households switching to cleaner cooking fuels. Based on data from the 2018 China Family Panel Studies, this paper uses a spatial econometric model to analyze the neighborhood effects in the process of adopting clean cooking fuels among rural households in China. The findings show that neighborhood effects influence the adoption of clean cooking fuels by rural households in the same village through social norms and social multiplier effects. Neighborhood effects also indirectly promote the adoption of clean cooking fuels by rural households through the Internet. There is heterogeneity in the neighborhood effects on the adoption of clean cooking fuels by rural households. Therefore, this study recommends related policies to facilitate the transition to clean cooking fuel in rural regions. • Neighborhood effects influence rural households' adoption of clean cooking fuels. • Social norms effects facilitate rural use of clean fuels for cooking. • Social multiplier effects accelerate rural use of clean fuels for cooking. • Internet's a bridge between neighbors' effects and rural use of clean cooking fuels. • There is heterogeneity of neighbors' effects on rural use of clean fuels for cooking. [ABSTRACT FROM AUTHOR]