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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]

• Urban green spaces have direct and indirect effects on improving residents' health. • The health benefits of urban green spaces exhibit regional heterogeneity. • Economic development weakens the health benefits of urban green spaces. • Environmental regulations can enhance the health benefits of urban green spaces. Urban green spaces have long been cherished as the "lungs of the city", it can not only improve air quality and enhance residents' health. The impact of urban green spaces on air pollution and residents' health has attracted great attention. In this paper, we select 31 provinces in China as research samples and use ArcGIS software to draw spatial distribution maps of urban green spaces, air pollution, and residents' health in China, characterizing their spatiotemporal changes in order to explore whether there is a correlation among the three. On this basis, this paper utilizes panel data of Chinese provincial-level from 2010 to 2020 and conducts empirical tests through a two-way fixed effect model and a threshold regression model. The research findings are as follows: (1) Urban green spaces not only bring environmental benefits, but also health benefits, and the health benefits are greater than the environmental benefits. (2) There is a health risk of air pollution in northern China, and the health benefits of urban green spaces are not significant. Conversely, there is no health risk of air pollution in southern China, and the health benefits of urban green spaces are significant. (3) Although environmental regulations can enhance the health benefits of urban green spaces, the role of environmental regulations in enhancing the health benefits of urban green spaces may be further weakened as the economy develops. [ABSTRACT FROM AUTHOR]

Energy plays a vital part in stimulating economic progress, and the shift towards a cleaner energy system is highly significant for ensuring the sustainable development of the economy. China's energy structure urgently needs to be transitioned. The fast advancement and implementation of artificial intelligence (AI) has provided a new and important tool for promoting the transition of energy structure. So, what is the relationship between the application of artificial intelligence and the transition of the energy structure? This research introduces artificial intelligence into the energy sector, focusing on the relationship between artificial intelligence and energy transition. Since nonlinear models are better able to study the complex effects and phase differences of artificial intelligence. Using China's provincial panel data spanning from 2006 to 2019, this study employs nonlinear modeling to explore the stage differences in the process of AI in facilitating energy structure transformation. This paper derives the following findings based on empirical research. First, there is a U-shaped relationship between artificial intelligence and the transition of energy structure. Specifically, before the inflection point, the initial application of artificial intelligence, artificial intelligence may adversely impact energy transition. When the inflection point is passed, AI will help facilitate the energy transition. Second, the U-shaped relationship between AI and energy transition is more pronounced in coastal and non-resource-based regions. Third, energy intensity, government investment in science and technology, and informatization will moderate the U-shaped relationship between artificial intelligence and energy transition, changing the steepness of the original U-shaped relationship and even reversing it. Hence, it is imperative to effectively utilize the technological benefits of artificial intelligence through the development patterns and distinctive features of different regions, thereby facilitating the smooth transition of the energy structure. [Display omitted] • The role of artificial intelligence in the energy transition process is studied. • Stage differences in the role of AI are analyzed. • The nonlinear relationship between AI and energy transition is investigated. • Provide insights into the factors affecting the relationship between AI and energy transition. • This research helps the government to advance the energy structure transition. [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 explores how green fiscal expenditure affects G reen T otal F actor E nergy E fficiency (GTFEE) from both non-spatial and spatial perspectives based on selected panel data of 254 cities in China. The results of the non-spatial panel model indicate that green fiscal expenditure has a significant positive impact on GTFEE. A comparative study of different econometric models shows that the main parts of the results are largely consistent, which indicates that the conclusions are robust. The spatial autocorrelation findings indicate a statistically significant presence of positive spatial spillover effects in the GTFEE of Chinese cities. Spatial Durbin Model (SDM) and Dynamic Spatial Durbin Model (DSDM) indicate that green fiscal expenditure has a similarly significant positive effect on GTFEE, which will increase over time. This paper considers different spatial weight matrices and changing measures to measure GTFEE, and the conclusions remain robust. Furthermore, industrial structure upgrading, and digital economy are vital in strengthening the relationship between local governments' green fiscal expenditure and GTFEE. According to heterogeneity analysis, green fiscal expenditure has a more significant effect on the GTFEE in mature resource-based cities and non-resource-based cities. • Influence factors of green total factor energy efficiency (GTFEE) is explored. • Green fiscal expenditure (GFE) has a significant positive impact on GTFEE. • Significant positive spatial spillover effects exist in the GTFEE of Chinese cities. • Industrial structure upgrading and digital economy are vital for GFE and GTFEE. [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]

• A composite index named GLCDES is developed to dynamically assess the level of Green Low-carbon Circular Development. • The combined-assignment VIKOR model based on game theory is developed to thoroughly estimate the construction level of GLCDES. • Southwest China's Green Low-carbon Circular Development Economic System construction level is examined from 2012 to 2021, showing how the long-side principle governs each region's value. • Selecting and strengthening the long side in combination with its reality is an effective way to improve the construction level of GLCDES. Emission peak and carbon neutrality are critical components of China's overall ecological civilization, and the establishment of a sound Green Low-carbon Circular Development Economic System (GLCDES) is a fundamental countermeasure for solving China's resource, environmental, and ecological problems. This paper used the new development concept as entry points to establish a comprehensive evaluation index system encompassing six subsystems: development dynamics, production and living systems, green benefits, low-carbon benefits, circularity benefits and socio-economic benefits. The combined-assignment VIKOR model, based on game theory, was used to thoroughly estimate the construction level of GLCDES by combining panel data from four southwestern provinces, including Chongqing, Sichuan, Guizhou and Yunnan, from 2012 to 2021. The study discovered that: the construction level of GLCDES in all four southwestern provinces increased over the past ten years, but the increase was not significant, the four development effectiveness indices, including green, low-carbon, circularity and socio-economic, were significantly improved, the development dynamics index was not significantly enhanced, and the index of production and living systems declined in fluctuation from year to year. The construction level of GLCDES between regions was very uneven and can be divided into two echelons, with the gap between Chongqing and Guizhou being particularly obvious. Regions can be categorized into three major categories based on the number of dominant subsystems. According to the above results, the total value of the dynamic comprehensive evaluation of each region is governed by the principle of the long side, which is an effective way to improve the construction level of GLCDES by selecting and strengthening the long side in combination with its reality. [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 factors influencing residents health have become complex and intertwined with the development of economy and society. Traditional research with a single factor on health will not provide an accurate picture of the situation. This paper collects data on economic, environmental and social factors to estimate their impact on regional health. Considering the data is multi-source and complex, this paper proposes a combined feature importance algorithm, which weighted the feature importance of RF, XGB and SOIL. The algorithm does not depend on the data and adaptively approximates the true results. The results show that economic factors have a significant and direct impact on health, environmental factors have a lag correlation with health level, and social factors have a more complicated effect on health. Finally, we provide policy suggestions for health on economic, environmental, and social development. [ABSTRACT FROM AUTHOR]

• The co-agglomeration accentuates haze pollution. • Co-agglomeration has obvious spatial effects on haze pollution. • The pollution effect of co-agglomeration is weakened with the improvement of the economic level. • Technological innovation has an inhibitory effect on the pollution effect of co-agglomeration. The issue of haze in the middle reaches of the Yangtze River urban agglomeration has significant implications for China. Concurrently, co-agglomeration and technological innovation are key factors influencing haze pollution. Using the panel data composed of PM2.5 concentration and other data from 27cities in the middle reaches of the Yangtze River urban agglomeration between 2010 and 2020, this paper empirically investigates the impact of co-agglomeration and technological innovation on haze pollution. From this rigorous analysis, several conclusions crystallize: (1)the co-agglomeration of productive services and manufacturing accentuates haze pollution, showcasing notable regional variances;(2)the haze pollution has a significant positive correlation with the co-agglomeration levels in local and neighboring regions;(3)the negative consequences of co-agglomeration on environments reduce as the agglomeration of productive services and economic development increases;(4)technological innovation significantly moderates the pollution effects of co-agglomeration. [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]

• Revisit the relationship between population and energy in the late stage of demographic dividend. • Consider the relationship between population and energy from the perspective of metabolism. • Measure metabolic efficiency by combining emergy analysis and the Index-DEA. • Explore the multi-scale response of metabolism to population quality. • Provide a reference for other developing countries with population and energy issues. China's population and carbon emissions will reach two peaks in 2030. Especially in the late stage of demographic dividend, it is necessary to revisit the relationship between population and energy. Metabolism is a critical perspective to help understand the population-energy relationship. This paper establishes a new paradigm for assessing the impact of population quality change on regional metabolism based on panel data from 2003 to 2019 in China. We measure the population quality index (PQI) using the Projection Pursuit method from four aspects and regional metabolic efficiency (RME) using emergy analysis and Index-DEA. Then, the Tobit model is used to explore the impact of population quality change on regional metabolism from a multi-scale perspective. The results show that the influence has some variability at different scales. From the total sample, the response of regional metabolism to population quality is significantly positive. For different PQI regions, the RME has a positive response to PQI in both, but this response is more obvious in advanced PQI regions. For regions in different locations, RME has positive response to PQI in both East and West, but there is no obvious response in the Central. These findings are closely related to global sustainable development. [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]

• The impact of economic growth pressure on energy efficiency improvement is discussed. • Economic growth pressure has hindered the improvement of energy efficiency. • Heterogeneity effects exist in individual dimension and temporal dimension. Economic growth target management has been a typical feature of Chinese governments at all levels for a long time in the past decades. Based on a panel data of 188 Chinese cities, this paper examines the impact of pressure brought by economic growth target on energy efficiency improvement. The results suggest that economic growth pressure has hindered the improvement of energy efficiency. For every unit of increase in economic growth pressure, the improvement indicator of energy efficiency will decrease by 3.3%. This finding is robust, after replacing explained variables and core explanatory variables, no substantial changes are found. Sub-sample regression confirms the existence of heterogeneity effects in individual dimension and temporal dimension. Finally, by summarizing existing studies, this paper finds that the investment imbalance effect, the hindrance effect on industrial structure upgrading, and the crowding-out effect on innovation are three important ways for economic growth pressure to restrain the improvement of energy efficiency. Our findings are helpful to understand the role of the government's economic growth target management in resource allocation and energy utilization and provide a certain practical reference for China to promote high-quality economic development. [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]

• Construct the green development performance system of industrial enterprises from the micro perspective. • Simulated the green development performance index of industrial enterprises with the functional data analysis method. • Analysis the regional difference of the index. • Verify the stability and reference value of the index. This paper constructs an enterprise green development performance system by integrating green development concept and enterprise performance measurement. Based on the panel data of 458 industrial listed enterprises in China from 2011 to 2018, this paper simulates the green development performance index of industrial enterprises by using the functional data analysis method and functional entropy weight method. There are four main conclusions. First, the change in the green development performance index of industrial enterprises is U-shaped, which shows an upward trend overall. Within a range of [0.006–0.05], the minimum value is 0.006, and considering the strength and trend of future policies there is no maximum value. The higher the value is, the higher the level of green development of industrial enterprises. Second, according to the weight and fitting curves, we can find that the importance and development level of social performance are at the highest, and the importance level basically floats around 0.5, far higher than the average level. The importance of economic performance and the development level of innovation performance are at the lowest respectively, and there is a big gap with the average level. Third, the shape and trend of the index generated by the average weight and the subjective weight of social performance are basically consistent with the index generated by the objective weight. This shows that the index is not sensitive to the weight and has certain robustness and representativeness. Finally, according to the location of enterprises, they were divided into three categories: middle, east and west. The boost Trap method was used to conduct FANOVA (Functional ANOVA) with the P value of 0.314. The results showed that the index did not differ significantly between regions at the significance level of 0.05. [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]

• System GMM model was applied to test the mechanism of environmental regulation on the pollution-intensive industry transfer. • The transfer shows a general trend from the east to the central and western in China. • The central and the western have become "pollution paradise" for pollution-intensive industries. The pollution associated has intensified the environmental pressure within industrial transfer between the central and the western region in China. It's the key issue that how to use environmental regulations to promote the orderly pollution-intensive industries transfer and the optimization of industrial structure to realize the construction of ecological civilization during the transformation and upgrading of economic. By constructing the index of environmental regulation and industry transfer, this paper analyzed the spatial-temporal change of pollution-intensive industry transfer. We collected panel data of 30 provinces in China from 2004 to 2016 and studied the spatial differences of pollution-intensive industry transfer from the perspective of environmental regulation. This paper studied the path and mechanism of environmental regulation on the pollution-intensive industry transfer theoretically and empirically with System Generalized Method of Moments (GMM) model. The conclusions are as follows: Firstly, the pollution-intensive industry transfer in China shows a general trend from the east to the central and western regions. Secondly, there are obvious differences in environmental regulation between different regions. Thirdly, there are some differences in the impact of environmental regulation on industrial transfer. Therefore, the central and western regions should coordinate economic development and environmental protection when undertaking industrial transfer from the east, to optimize and upgrade industrial structure, and promote long-term economic development. [ABSTRACT FROM AUTHOR]

With the deterioration of China's ecological environment, technological innovation (TI) has become an important method of green transformation and upgrading Chinese steel enterprises (CSEs) under the constraint of environmental regulation (ER). Based on environmental protection panel data of 86 CSEs from 2005 to 2014, this paper first analyzes the direct effects of heterogeneous environmental regulation (HER) on TI and then studies the indirect effects of HER on TI through factors such as enterprise size, human capital, enterprise profit margin and executive environmental awareness. Based on a high-dimensional fixed effects model, the results show that (1) command-control environmental regulation (CCER) and voluntary environmental regulation (VER) have direct and positive effects on the TI of CSEs, while market-incentive environmental regulation (MIER) does not; and (2) the indirect effect of human capital is positively regulated by CCER and VER and that of enterprise size is negatively regulated by MIER, while all of the types of HER regulate the negative indirect effect of profit margin and the positive indirect effect of executive environmental awareness. It is necessary that combined and unified policy tools be implemented in the iron and steel industry (ISI) nationwide to coordinate the effects of HER. • This paper analyzed the dual effect of HER on TI of 86 CSEs with a high-dimensional fixed effects model. • Only CCER had the direct and positive effect on TI, whileMIER did not. • CCER had the indirect effect on TI through human capital, enterprise profits, and executive environmental awareness. • MIER had the indirect effect on TI through enterprise size, enterprise profits, and executive environmental awareness. • The robustness test by SYS-GMM verified the above results. [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]

• This paper studies the competition effect of product recommendation networks. • Three network attributes, centrality, connection , and scale are measured. • Their impacts on market competition in a homogeneous product market are tested at the global-network level. • A panel data of 320,981 package tour products was used to estimate the model. • Empirical results confirm the effect of three attributes on market competition. Extant studies have focused on the sales benefits of product recommendation networks; however, the competition effects of such networks have been overlooked. Understanding the competition effects of product recommendation networks is important within an e-commerce platform because maintaining a proper level of competition is critical to the platform ecosystems. This research adopts a data-driven approach and social network analysis, elaborating upon three structural properties of recommendation networks – centrality, connection, and scale – and operationalizes them as e venness of distribution, clustering of structure, and network size at the global-network level. The competition effects of the three proposed network variables were tested based on a daily panel dataset of 320,981 package tour products from Tuniu.com , a top travel service platform in China featuring homogeneous products. Empirical results confirmed that the three proposed structural network properties increase market competition in recommendation networks of homogeneous products. This research contributes to our understanding of the impact of recommendation networks on market competition in the context of homogeneous product markets and offers practical implications of substition recommendation for platform governance. Platform operators can leverage product recommendation networks to alleviate market competition and encourage the entry of sellers with new, innovative products that contribute to the e-commerce platform ecosystems. [ABSTRACT FROM AUTHOR]

[Display omitted] • China's air pollution mainly presents a spatial pattern of high-high agglomeration and low-low agglomeration. • New-type urbanization significantly reduces local air pollution. • Industrial structure, technological innovation and energy structure are important transmission mechanisms. • The impact of new-type urbanization on air pollution has regional heterogeneity. To alleviate the ecological and environmental problems caused by rapid urban development, China has formulated and implemented the new-type urbanization strategy. However, there is insufficient empirical research on the specific relationship between new-type urbanization and air pollution. Therefore, based on the panel data of 30 provinces in China from 2005 to 2018, this paper constructs a comprehensive evaluation index system of new-type urbanization using the five dimensions of population, economy, space, society, and green. The spatial Durbin model and the spatial mediating model are used to discuss the spatial effect, transmission mechanism, and regional heterogeneity of new-type urbanization on air pollution. The results show that China's air pollution mainly presents a spatial pattern of high-high agglomeration and low-low agglomeration, and there are spatial fluctuations. The construction of new-type urbanization significantly reduces local air pollution, and the industrial structure optimization, technological innovation, and energy structure adjustment are considered as important transmission mechanisms. However, under the fiscal decentralization and political tournament system in China, the policy implementation deviation may weaken the emission reduction effect of new-type urbanization, which is not conducive to regional environmental governance. From the sub-regional level, the impact of new-type urbanization on air pollution has regional heterogeneity. A robustness test confirms the reliability of our research conclusions. This study also proposes some policy suggestions that the government can utilize in grasping the policy focus of new-type urbanization construction to discover effective ways of controlling air pollution. [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]

• To investigate the green technology selection effect of environmental information disclosure policy. • Using mediation effect model to study the transmission mechanism of environmental policy. • Using instrumental variable approach to control the endogenous problem of environmental policy. • To examine the different effects of environmental information disclosure on green technology in different cityes. Based on 230 prefecture-level city panel data from 2003 to 2019 in China, this paper uses environmental information announcement system as a quasi-natural experiment, and uses the two-stage least squares (2SLS) model with instrument variables (IVs) to test the green innovation effect of heterogeneous urban environmental information announcement. The results show that environmental information announcement can significantly stimulate green innovation, and the stimulating impact has a long duration time and heightens year by year. Under the constraints of different affluence degrees, administrative level, industrial dependence degree and the difficulty of profit acquisition, the effects of urban environmental information announcement have obvious differences. Generally, the higher the degree of urban affluence or administrative level, the more prominent the effect of green innovation of environmental information announcement is. The more dependent the city is on the polluting industry, or the easier it is to obtain profits from the polluting industry, the more difficult it is to change the direction of green innovation of environmental information announcement. Simultaneously, environmental information announcement mainly motivates the choice of green innovation by changing the difficulty of obtaining industry profits. [ABSTRACT FROM AUTHOR]

Although green growth has become the economic development strategy of many countries in the world, and studies have analyzed the influencing factors of green growth from multiple angles, there are few literatures devoted to the impact of fintech and green finance on green growth. From the perspective of fintech development, this paper tries to construct a comprehensive index to evaluate the green growth of regional economy based on the in-depth analysis of the influence mechanism of green finance on green growth. At the same time, China's provincial panel data from 2011 to 2018 are selected to test the impact of fintech innovation and green finance on green growth, and its mechanism. It turns out that fintech and green finance significantly promotes green economic growth. At the same time, the impact of fintech and green finance on green growth has obvious regional heterogeneity, that is, the impact in eastern China is significantly stronger than that in central and western China. Further research shows that fintech innovation mainly promotes green economic growth through green credit and green investment. Therefore, fintech innovation can promote green economic growth by improving the development level of green finance, which has great reference significance for most countries. [ABSTRACT FROM AUTHOR]