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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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

Previous studies have considered the one-way relationship between sustainable innovation and industrial transformation or upgrading. This research further investigates the asymmetric relationship between sustainable innovation and industrial transformation or upgrading from long-term and short-term perspectives. We analyse 30 provinces in China from 2001 to 2020 using ordinary least squares and panel quantile regression models to explore the positive effect of sustainable innovation on industrial transformation and upgrading with spatiotemporal heterogeneity. The panel autoregressive distributed lag (ARDL) model and panel vector autoregression (PVAR) further survey the causal relationship between sustainable innovation and industrial transformation and upgrading. The findings reveal that sustainable innovation promoted advancing industrial structures over the long-term and short-term promotion of industrial structure rationalisation. Simultaneously, there are low mutual coordination and extension between sustainable innovation and industrial transformation and upgrading. For regions with high coordination between sustainable innovation and industrial transformation and upgrading, the interaction between sustainable innovation and the advanced industrial structure is more pronounced. The paper's results confirm the asymmetric relationship between sustainable innovation and industrial transformation and upgrading, and the findings have crucial significance for the sustainable development of China's economy. [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]

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]

The paper investigates how climate changes and socioeconomic transformations affected grassland productivity from 2000 to 2017 in counties in Inner Mongolia of China. The grassland productivity and climatic change variables included 162 readings (9 periods in the growing season × 18 years), while ten socioeconomic variables contained 18 yearly readings. The mismatch between the environmental observations and socioeconomic data compounds quantitative analysis of causal relations between them. We applied several time-series processing methods to generate five datasets. We fit them with conventional, dependent-lagged, and dynamic-lagged panel regression models to investigate which combinations augment causal relationships between grassland productivity, climate, and socioeconomic changes. The results confirmed that the conventional model with the original data failed to reveal causal relationships between these factors. The panel regression models with the original data tended to intensify the causal effects of climate factors on grassland productivity. The models with the transformed datasets disclosed more socioeconomic variables showing causal relationships with grassland productivity. The dependent-lagged model with the empirical mode decomposition transformed data produced the highest R-squared value and lowest prediction error. GDP, state fixed asset investment, highway construction, grain plantation, and livestock density were primary factors affecting grassland productivity. In brief, the integration of time-series data mining and time-lagged panel analysis effectively unveiled the causes of grassland deterioration under climate and socioeconomic changes. [Display omitted] • Augment causality hidden in env-socio-economic systems with data assimilation. • Assimilate temporal environmental and socioeconomic data into compatible time-series. • Experiment with four groups of computational data mining methods on data assimilation. • Compare combinations of data assimilation methods and lagged panel regression models. [ABSTRACT FROM AUTHOR]

This paper provides an in-depth understanding of the mechanisms of green finance on green innovation, focusing on their spatial and non-linear relationships. Using panel data of 30 provinces of China during the period of 2009–2017, a green finance index is constructed, and the spatial Durbin model and panel threshold model are used. The results reveal that: (1) Green finance and green innovation had significant positive autocorrelation, and the development of green finance in provinces of central and western China were still in the lower-level range. (2) The coefficients of the direct effect and indirect effect of green finance on green innovation were significantly positive, which indicated that green finance was conducive to enhancing green innovation in local and adjacent provinces during the research period. (3) Double threshold effects of green finance on green innovation were observed, which demonstrated that the driving effect of green finance was decreased with the raising of intensity of environmental regulation. The implication of these results is that government should make full use of the radiation and trickle-down functions of green finance and green innovation to narrow regional gaps in sustainable development while maintaining a moderate intensity of environmental regulation. • A green finance index of 30 provinces of China during the period of 2009 to 2017 was constructed on the basis of green credit, green securities, green insurance, and green investment. • The heterogeneity of region and time for green finance were analyzed employing the spatial exploratory analysis, which manifested that the spatial evolution of green finance in China presents a gradient decreasing pattern from east to west. • The impact of green finance on green innovation was explored by the spatial Durbin model, which proved that the direct effect and the spatial spillover effect were significantly positive. • Moderate intensity of environmental regulation helps green finance promote green innovation and this value should not exceed a maximum of 0.935. [ABSTRACT FROM AUTHOR]

Sustainable development emphasizes the sustainability of natural resources and the environment. Under the background of resource scarcity and environmental constraints, it is of great significance to explore the impacts of the ecological footprint on the resource-rich but unbalanced China's Yangtze River Economic Belt from two perspectives of flow capital occupation and stock capital occupation. This study uses a fixed-effect regression model to investigate the impacts of ecological footprint breadth and depth on sustainable development by the panel data of 108 prefecture-level cities in China's Yangtze River Economic Belt from 2006 to 2018. Further combining the panel threshold regression model results, we identify ecological footprint breadth and depth as having inverted N-shaped and inverted U-shaped relationships with sustainable development. Firstly, there is a double threshold effect between ecological footprint breadth and sustainable development. Then, there is a single threshold effect between ecological footprint depth and sustainable development. When ecological footprint breadth is within the threshold of (0.2802, 0.7997), it is conducive to sustainable development. When ecological footprint depth is less than 2.5404, it is conducive to sustainable development. Secondly, ecological footprint breadth improves sustainable development of the Yangtze River Economic Belt by rationalizing and advancing industrial structure. Ecological footprint depth achieves sustainable development through rationalizing industrial structure. Thirdly, the mechanism of the ecological footprint on sustainable development has regional heterogeneity. Finally, this paper proposes several policy implications for achieving China's sustainable development. [ABSTRACT FROM AUTHOR]

Financial agglomeration is a key way to promote the green transformation of the global economy and environmental governance. The existing literature mainly analyzed the impact of financial agglomeration on economic development, but rarely examines its comprehensive impact on economic growth and environmental governance considering spatial spillover effects. Based on the perspective of spatial spillover effects, this paper uses panel data of 285 cities above the prefecture-level in China to examine the impact and mechanism of financial agglomeration on green development. The results show that: (1) During the study period, financial agglomeration and green development in China are significantly different in directions of spatial distribution and expansion, but the spatial correlation between the two is relatively high. (2) Financial agglomeration can exert significant spatial spillover effects on green development. (3) Financial agglomeration has more obvious positive spatial spillover effects on green development of cities in the servitization stage or with high administrative level. (4) Industrial structure upgrading effect, labor upgrading effect and technological innovation effect are the main paths that financial agglomeration affects green development. The research results can provide a new perspective and approach to promote the green transformation of economy and sustainable development of the world. [ABSTRACT FROM AUTHOR]

Participation in international industrial transfer (IIT) provides a significant opportunity and a motivation to improve China's industrial land production efficiency (ILPE). This study aims to investigate the overall role, heterogeneous impact and indirect mechanism of IIT in improving Chinese ILPE. This paper uses the Directional Distance Functions - Data Envelope Analysis (DDF-DEA) model to measure ILPE, economic output efficiency, and pollution reduction efficiency, the Global Malmquist Luenberger (GML) index to decompose the growth of ILPE into "technical efficiency change (EC)" and "technological change (TC)". The panel data of Chinese provinces from 2003 to 2018 and the Fixed-Effect model is used to examine the impact of IIT on ILPE. The primary outcomes suggest that participation in IIT has generally improved the ILPE in China. This promotion effect is evident after 2010, and IIT has a significant impact on the improvement of ILPE in extensive and inefficient areas. Similarly, IIT promotes the economic output efficiency of industrial land from the perspective of expected output and reduces unexpected output. This impact helps in improving pollution reduction efficiency of industrial land. The technology spillover brought by IIT improves the Chinese ILPE from two channels, including promoting technological progress and improving technical efficiency. However, the technology spillover mainly promotes the ILPE in land use high-efficient areas by promoting technological progress. Likewise, the ILPE is promoted by improving technical efficiency from a regional perspective in extensive and inefficient areas. This study provides valuable insights for the improvement of ILPE to optimize land resources. [ABSTRACT FROM AUTHOR]

This study investigates the impact of the state-owned sector on industrial transformation and upgrading as well as its mechanisms. Using provincial panel data for China from 2001 to 2019, we found that SOEs have a positive influence on value-enhancing upgrading, while the effects on resource-saving and environment-friendly upgrading are inverted U-shaped. These results indicate that innovation partially mediates the relationship between SOEs and the three types of industrial upgrading. Employing Data Envelopment Analysis (DEA), we also measured the Malmquist index of SOEs and non-SOEs in China and empirically tested the spillover effects of SOEs. The empirical results reveal a significant innovation spillover effect of SOEs. SOEs are able to promote industrial transformation and upgrading with strong and far-reaching spillovers. • This paper defines three types of industrial upgrading. • State-owned enterprises (SOEs) have a positive impact on value-enhancing upgrading. • Innovation partially mediates the relationship between SOEs and industrial upgrading. • Our results reveal a significant innovation spillover effect of SOEs. [ABSTRACT FROM AUTHOR]

The development of China's highway infrastructure has led to a rapid increase in carbon dioxide (CO 2) emissions while facilitating social and economic development. This paper introduces highway mileage and CO 2 emissions into the traditional production density model, using agglomeration as a mediating variable, to theoretically discuss the path through which highway infrastructure influences CO 2 emissions. We then use the spatial Durbin model (SDM) to verify the explanatory power of the expanded production density model based on panel data of China's 278 cities from 2003 to 2016. Empirical results indicate that (1) there is an inverted U-shaped relationship between highway infrastructure and CO 2 emissions in both local and peripheral cities; (2) highway infrastructure affects local CO 2 emissions through the agglomeration pathway but impacts CO 2 emissions in peripheral cities mainly through the spatial spillover effect of highway infrastructure; and (3) the U-shaped impact of highway infrastructure on CO 2 emissions in western China is diametrically opposed to the results for the east, the central region and the total sample. Therefore, China needs to fully consider the environmental effects of agglomeration to formulate a global emission reduction strategy when building highway infrastructure. Moreover, strategies based on the different stages of highway infrastructure development should be enacted and should be part of a spatially synergistic joint emission reduction mechanism while considering the characteristics of regional development. • The study extends the production density model and verifies the explanatory power. • The spatial correlation between variables is tested by the spatial Durbin model. • Regional heterogeneity is discussed, and the reasons for this are analysed. • The results are corrected using GS2SLS with slope as an instrumental variable. • Related policy recommendations are made for low carbon development in China. [ABSTRACT FROM AUTHOR]

Linkages between air pollution and individual subjective well-being (SWB) are theorized as a key component of the United Nations Sustainable Development Goals. Using the China Family Panel Studies (CFPS) covering 12,668 residents who were interviewed for five consecutive times during 2010–2018, we find significant negative effects of air pollution on individual SWB via the change of the respondent's physical health level, physical exercise behavior and obesity risk. Specifically, a one standard deviation increase in county's annual average PM 2.5 concentrations, instrumented by thermal inversion, is associated with a 2.45 standard deviations decrease in individual SWB level. In particular, people who are male, young people, less educated group, urban resident and live in eastern or western China are more sensitive to air pollution. This paper provides new insights into the health costs of air pollution. [ABSTRACT FROM AUTHOR]

The implementation of environmental regulation needs to consider not only pollution control but also its impact on economic growth. Using the provincial panel data in China from 2000 to 2017, this paper constructs dynamic spatial panel models and employs system GMM approach to evaluate the nonlinear and spatial effects of environmental regulation on economic growth and CO 2 emissions, respectively. The results suggest that, first, environmental regulation presents a significant "N"-shaped effect on economic growth and an inverted "N" effect on CO 2 emissions at the national level and in the eastern and central regions; while the effects are both"N"-shaped in the western region. Second, environmental regulation presents significant spatial effects on economic growth and CO 2 emissions. The enhancement of regional environmental regulation helps the economic growth and CO 2 emissions reduction in neighboring provinces at the national level and in the eastern and central regions, however, the spatial effects are opposite in the western provinces, proving the co-exists of "race to the top" and "race to the bottom" strategies of environmental regulation competition among China's regions. Third, the effects of environmental regulation on economic growth and CO 2 emissions are affected by FDI, and the moderating effect of FDI is regional heterogenous. • Building a dynamic spatial panel model based on the spatial spillover theory. • Proving an "N"-type effect of environmental regulation on economic growth. • The effect of environmental regulation on CO 2 emissions is regionally different. • Environmental regulation affects the role of FDI on economy and CO 2 emissions. • The spatial spillover effects of environmental regulation are proved. [ABSTRACT FROM AUTHOR]

The 2030 Agenda for Sustainable Development stipulates 17 Sustainable Development Goals (SDGs). The implementation of this agenda will mobilize countries worldwide to incorporate the SDGs into their national development strategies. The agenda does not specify how these goals are interconnected, thus limiting their implementation. In addition, air quality affects human life and plays a vital role in achieving these SDGs. Clarifying the interconnections between SDGs related to air pollution and other SDGs will accelerate the implementation of air protection and SDGs while simultaneously promoting policy coherence. In this paper, we use the latest calculation of the SDGs in China to construct national and provincial panel data to investigate the trade-offs and synergies among Chinese air pollution-related SDGs. The findings are as follows. First, most air pollution-related SDGs have synergetic relationships, except for SDG12, which has a trade-off relationship with other air pollution-related SDGs. Second, the synergies between air pollution-related SDGs and other SDGs far outweigh the trade-offs. Third, rapidly developing areas are more likely to experience a trade-off between economic development and air pollution problems. Fourth, geographic advantages in reducing air pollution, such as being adjacent to the sea, may weaken the synergies among air pollution-related SDGs and their synergies with other SDGs. These findings indicate that most air-pollution-related SDGs and interactions between air-pollution-related SDGs and other SDGs have substantial synergy; that is, measures aimed at one goal are conducive to the advancement of other goals. However, SDG12 reflects a trade-off relationship between economic development, environmental protection, and resource utilization. [ABSTRACT FROM AUTHOR]

Green development is a common goal pursued globally for carbon neutrality, and whether environmental regulatory system drives it in pollution-intensive industries (PIIs) is puzzled. Using provincial panel data of Chinese PIIs during 2005–2017, this paper applied entropy method to integrate existing environmental regulatory system into three types of environmental regulations, and then explored non-linear effects of them on green total factor productivity (GTFP). Several conclusions are generated. The annual growth rate of GTFP is 10.61% and it presents industrial differences. Technical change is the driving factor, while technical efficiency shows inhibiting effect. The effect of command-and-control environmental regulation on GTFP is a significant inverted U-shape curve, which is currently the primary driving role in green development, but it is too strict and increasingly less effective. Both market incentive and voluntary environmental regulations appear as positive U-shape curves, and their proper enhancement is breakthrough for future green development. Besides, market incentive environmental regulation is more effective in PIIs with relatively low pollution, while voluntary environmental regulation is sensitive to PIIs with relatively serious pollution. The Chinese government should allow environmental regulatory system more marketability and voluntariness, and production characteristics and pollution density of targeted industries should be considered. • The green development grows rapidly but shows technical inefficiency. • Command-and-control environmental regulation drives green development effectively. • Market incentive and voluntary environmental regulations can be enhanced properly. • Market incentive environmental regulation is sensitive to slight-polluted industries. • Voluntary environmental regulation works in heavy-polluted industries. [ABSTRACT FROM AUTHOR]

In response to climate change, carbon emission reduction has become an important goal worldwide. Forests are the largest carbon pool in terrestrial ecosystems with a high carbon density and a fast carbon accumulation rate, and play a key role in the global carbon cycle. In this paper, the dynamic change and influence factors of forest carbon sequestration efficiency was analysis using the Data Envelopment Analysis Malmquist method in province level of China. The results showed that Heilongjiang, Yunnan, Tibet, Sichuan, and Inner Mongolia had the highest carbon sequestration, while northern China, eastern China, and southwestern China had the highest carbon sequestration efficiency. Furthermore, the factors of gross domestic product (GDP) per capita, urbanization, and the length of the highway network had significant positive impacts on the carbon sequestration efficiencies, while the total imports and exports had a significant negative impact. Ecological afforestation, temperature, GDP per capita, urbanization, population, and total imports and exports had spillover effects. It is recommended that the northeastern, central-southern, and southwestern regions with high carbon sequestration efficiencies should be used as the main areas to enhance carbon sinks in the future, and the areas with low efficiencies should respect the laws of nature more. Provinces should take into account the characteristics of the science and technology needs of forest areas and should provide forestry technology extension services. The results of this study are of great significance to improving the efficiency of financial investments, forest quality, and carbon sinks. • Forest transition has shifted from increased forest land cover to increased forest ecosystem services; •Factors affecting the level of forest carbon sequestration productive efficiency are Natural conditions--bio-physical; urbanization rate; economic and demographic conditions; degree of openness •Northeast, Central South, and Southwest of China with high carbon sequestration efficiency can be used as the main areas; •This result would be conducive to carry out the ecological construction of suitable forests. [ABSTRACT FROM AUTHOR]

Given the degradation of the environment, balancing economic development with environmental protection is key to a green China. Therefore, it is of great significance to study the impacts of different environmental policies on China's pollution-intensive industries (PIIs). We look at the main types of environmental policies tools of China in areas of legal, economic and informal regulations, and select typical policies of each type for research. Based on the theoretical model about how environmental regulations affect the transfer decision of polluting enterprises, quantitative empirical tests are conducted in this paper to study the influences of environmental regulations on the transfer of PIIs by using provincial panel data from 2003 to 2016. It is found that: (1) All three types of environmental regulations have significant yet heterogeneous impacts on the transfer of PIIs. (2) With an emphasis on the nonlinear impact of environmental regulations on PIIs' transfer, we find that all the three types of environmental regulations exert inverted-N shaped nonlinear influences. The findings indicate that regions with ultra-stringent or excessively loose regulations are not attractive to polluting industries. However, appropriate environmental regulations stimulate enterprises to innovate, enhance market competitiveness, and increase production. (3) Between regions, spatially heterogeneous influences on PII's transfer are also found. Currently, levels of all types of environmental regulations are relatively low in China, which induce an initial negative correlation between policies and polluting enterprises. As a result, governments should continue to improve environmental regulations to promote a state of positive correlation, realizing a win-win result for environmental protection and economic development. ● Environmental regulations (ERs) affect pollution-intensive industries' (PIIs). ● The impact of ERs on PIIs' transfer is nonlinearly inverted-N shape. ● Multiple ERs have heterogeneous impacts on PIIs' transfer. ● Spatially heterogeneous influences of ERs on PIIs' transfer exist. ● Currently, the levels of all types of ERs are relatively low in China. [ABSTRACT FROM AUTHOR]

Conventional finance has many deficiencies in promoting green technology innovation (GTI) and energy-environmental performance (EEP). The emerging digital finance is filling the gaps left by conventional finance with the support of information technology. Using panel data from 2011 to 2017, the paper explores the impact of digital finance on energy-environmental performance in China. The results show that digital finance significantly improves China's energy-environmental performance, which remains robust after a series of tests. Green technology innovation is the transmission path through which digital finance affects energy-environmental performance. The impact mechanism test proves that digital finance affects pure technical efficiency rather than scale efficiency. Furthermore, we also find that digital finance has a greater stimulus effect on energy-environmental performance where credit and capital markets are more immature. Financial supervision and environmental regulation from the Chinese government can reinforce the role of digital finance in promoting energy-environmental performance. Our study suggests that China should accelerate digitization in the financial markets, particularly in pursuit of its energy-saving and emission-reduction effects. • Digital finance can improve energy-environmental performance significantly. • The green technology innovation is the primary mechanism for the improvement of energy-environmental performance. • Instrumental variable, Semiparametric, DID models are employed to exclude endogeneity. • Credit and capital markets, financial and environmental supervision can reinforce the role of digital finance. [ABSTRACT FROM AUTHOR]

Emerging industrialized countries are confronted with the fundamental reality of an increasingly uncertain and unstable economic policy environment. In case of China this paper examined how the transformation of inclusive green growth, from a "beggar-thy-neighbor" approach to a "neighbor-friendly" approach, can be realized. From the perspective of a "pollution paradise", this study regarded haze pollution as a mediator to examine the driving mechanism underlying the influence of economic policy uncertainty on inclusive green growth. Moreover, media attention was introduced as a moderator to explore the institutional scenario that drives inclusive green growth in China. This study used panel data from 30 provinces for the period 2006–2016, and employed the Spatial Durbin model for empirical testing. The findings showed that the influence of EPU on inclusive green growth was multi-dimensional, and this included the direct "policy-economic" effect, the partial intermediary effect of a beggar-thy-neighbor model which was reflected by haze pollution, and the moderating effect of a neighbor-friendly approach via media attention. Furthermore, the results revealed an inverted-U-shaped relationship between haze pollution and inclusive green growth. Finally, media attention can effectively regulate the negative impact of economic policy uncertainty and haze pollution on inclusive green growth, and realize the transformation of inclusive green growth from a beggar-thy-neighbor policy to a neighbor-friendly policy. This study presents a new perspective for understanding the economic consequences of economic policy uncertainty and provides an empirical framework that guide local governments about climate governance. • Examine how the transformation of inclusive green growth can be realized. • Haze pollution and media attention were introduced as a mediator and a moderator, respectively. • The influence of EPU on inclusive green growth was multi-dimensional. • There was an inverted-U-shaped relationship between haze pollution and inclusive green growth. [ABSTRACT FROM AUTHOR]

This paper aims to examine the causal relations between economic growth, electricity consumption, and urbanization indicators. Heterogeneous panel data techniques are performed to help shed light on the importance of the heterogeneity among three economic regions within China from 2000 to 2017. Our results show that the three indicators are all stationary and cointegrated after the first difference. Heterogeneity of the Granger causality is found between these three variables varies across the eastern, central, and western economic regions in China. In the long run, the eastern region presents a similar trend as the national level that long-run Granger causality of the three variables is found. Conversely, there is a unidirectional long-run causal relationship from economic growth to electricity consumption in the central region, while there is a bi-directional long-run causal relationship between economic growth and electricity consumption in the western region in China. Our empirical findings highlight the "urbanization ladder" effect which implies that as development, urbanization factor in the eastern region may play a promotion role in the tri-variate system when the urbanization reaches a higher level, while it may lack the influence in the central and western regions of China. From a regional perspective, it is further indicated that the improvement of urbanization can be practical measures in the central and western parts of China in the long run. • Economic growth, electricity consumption, and urbanization are cointegrated in eastern, central, and western China. • Granger causalities between the three variables vary across the three economic regions in China. • Urbanization does not have a causal effect on economic growth & electricity consumption in central-western China. • It is essential to accelerate the urbanization process in the central-western areas in China in the long run. [ABSTRACT FROM AUTHOR]

This study provides insights into the spatial relationships among logistics agglomeration, technological progress, and air pollution in the sub-regions. From the perspective of new economic geography, the positive environmental externality of logistics agglomeration should outstrip its negative externality as the result of technological spillover. However, significant impacts of technological progress on the environment have not been identified in the logistics agglomeration sub-regions of many developing countries currently grappling with various environmental problems. This paper applies spatial econometrics and extended STIRPAT model to explore the roles the logistics agglomeration (LA) and technological progress (T) play in air pollution (I) using panel data from sub-regions of Chongqing in China between 2009 and 2019. The main conclusions are as follows. (1) In a global context, logistics agglomeration is a meaningful way to reduce air pollution under the interaction effect of technological progress. (2) In a sub-regional context: first, the suppressive effect of logistics agglomeration on air pollution gradually rebounds with the increase in agglomeration degree; secondly, the rebound effect of technological innovation is also evident in air pollution, and the rebound area gradually spreads from the metropolitan area to the peripheral sub-regions; finally, the interaction effect of logistics agglomeration and technological progress has a noteworthy suppression effect on air pollution, especially after the occurrence of the rebound effect of the logistics agglomeration and technological progress. In this regard, local governments should suppress the negative externalities of agglomeration with the interaction effects of technological progress while strengthening logistics agglomeration. [ABSTRACT FROM AUTHOR]

Promoting environmental regulation and the reduction of carbon emissions is of great significance for sustainable development. China plans to achieve the following two major goals by 2030: to experience the peak of carbon dioxide emissions, and to be at the forefront of innovative countries in the world. The realization of these goals not only depends on the environmental regulation policy regarding carbon emissions, but also on the development imbalance among Chinese provinces. The Porter hypothesis theory holds that environmental regulation can produce the Porter effect and promote enterprise innovation; but few studies focused on the causal relationship between environmental regulation and the regional Porter effect. Under this framework, this paper uses propensity score matching - difference in difference (PSM-DID) to construct a quasi-experiment on China's carbon emissions trading pilot policy. Dynamic panel data models are used to double test whether environmental regulation can stimulate the regional Porter effect. The empirical results show that: (1) Under the premise of multiple robustness tests (whether quasi-experimental or dynamic panel data models), no evidence was found in support that environmental regulation can stimulate the regional Porter effect. (2) The reason why the regional Porter effect does not been stimulated is that the pollution heaven effect, induced by the carbon emissions trading pilot policy, counteracts the Porter effect to a certain extent. (3) There is no non-linear relationship between environmental regulation and the regional Porter effect. (4) The analysis of spatial heterogeneity shows that environmental regulation cannot stimulate the Porter effect in the eastern, central, and western regions of China. This suggests that it is very important to establish appropriate provincial environmental regulation objectives and to conduct appropriate environmental regulation in combination with local resource endowments. This study provides quantitative evidence toward an in-depth understanding of the relationship between environmental regulation and the regional Porter effect as represented by the pilot policy of carbon emissions trading. A certain degree of reference is provided for the practice of environmental regulation in other developing countries. • Environmental regulation cannot stimulate the regional Porter effect. • The pollution heaven effect explains why regional Porter effect is not stimulated. • No nonlinearity exists between environmental regulation and regional Porter effect. • Environmental regulation cannot stimulate the Porter effect in all Chinese regions. • The government should appropriately strengthen environmental regulation. [ABSTRACT FROM AUTHOR]

To achieve sustainable economic development, many developing countries have continuously tightened their environmental regulations; for example, the Chinese government revised some policies to protect the environment, such as the Environmental Protection Law, and levied environmental taxes. Will these regulatory tools affect the growth of the industrial economy? What are the differences in the influence of various types of environmental regulations? Based on city-level panel data from China, this paper applied a difference-in-difference (DID) model and a bootstrap panel Granger causality test to investigate the relationship between two types of environmental regulations (command-and-control environmental regulation and market-Based incentive environmental regulation) and industrial growth. The results show that (1) Command-and-control environmental regulation (CAC) has a significant inhibitory effect on industrial growth. (2) In most regions, there is no significant Granger causality between market-based incentive environmental regulation (MBI) and industrial growth. (3) Compared with command-and-control environmental regulation, market-based incentive environmental regulation allows more flexibility for enterprises, which is more beneficial for technological innovation. Meanwhile, market-based incentive environmental regulation does little to suppress industrial growth. • Environmental regulation are subdivided into the MBI(Market-Based Incentive) and the CAC(Command and Control). • We reflect the influence of the CAC environmental regulation on overall industrial performance to the industrial growth. • It investigates the relationship between the two types of environmental regulations and industrial growth respectively. [ABSTRACT FROM AUTHOR]