How does digital economy affect green total factor productivity? Evidence from China

Can the development of the digital economy reduce industrial solid waste pollution?

Constraining industrial solid waste emissions is essential to achieving net-zero carbon emissions. Exploring how to reduce industrial solid waste pollution in the Industry 4.0 era is of great importance. This study investigates the impact of digital economic development on industrial solid waste pollution and its underlying mechanisms using a two-way fixed-effects model, with panel data from 30 provinces in China from 2011 to 2022. The results reveal a non-linear relationship between digital economic development and industrial solid waste pollution, showing an inverted "U" curve, which aligns with the traditional Environmental Kuznets Curve. The estimated inflection point of inverted "U" curve is 0.653, while the existing level of digital economic development is much less than it, revealing the current stage of China's digital economy has yet to demonstrate a significant inhibiting effect on industrial solid waste pollution. Mechanism analysis indicates that the digital economy influences industrial solid waste pollution through regional factor allocation efficiency and technological progress. Additionally, further analysis shows that upgrading the industrial structure and developing green finance can expedite the inflection point, allowing the digital economy's pollution-reducing effects to manifest earlier. This research provides implications for digital economic development and industrial solid waste pollution reduction.

Impact of economic growth patterns on carbon quota allocation by industry in China: extensive or intensive

Economic growth is closely related to carbon emissions, and determining the appropriate emission reduction targets for various sectors under different economic models has always been a challenge. This paper utilizes an Energy-Economic-Environment CGE model to simulate two types of economic growth models: extensive and intensive. Four economic growth scenarios are defined, and initial carbon quota allocations for various sectors are obtained for China at two key points: the peak year (2029) and the post-peak year (2035). The ZSG-DEA model is applied, considering the principles of fairness and efficiency, to iterate carbon efficiency across 33 industries and obtain quota adjustment values. The results indicate that the innovation-driven scenario, representing intensive growth, achieves a win-win outcome compared to other scenarios by enhancing GDP and avoiding additional carbon reduction costs. The initial carbon emission efficiency in agriculture, chemicals, steel, electronics, water supply, and services all reached 1. Comparative analysis reveals that the sectors of electricity, chemicals, coal, and cement face higher emission reduction pressures, while agriculture and services experience relatively lower pressures.

Striving towards green total factor productivity: A bibliometric and systematic literature review for future research agenda

In response to escalating environmental challenges and the pressing need for sustainable energy solutions, policymakers are increasingly focusing on Green Total Factor Productivity (GTFP) as a vital metric for sustainable economic growth. The present study examines the role of GTFP in addressing both economic and environmental objectives by incorporating energy efficiency and pollution mitigation within productivity analysis. The study provides a comprehensive examination of GTFP, with emphasis on major determinants such as agglomeration, environmental regulation, industrial structure, and green finance. Our robust review approach allows us to report methodological and topical contributions through detailed documentation of research collaboration, co-citation analysis and thematic classifications. As environmental policymaking increasingly aim to integrate sustainable development goals, this study offers policymakers and researchers crucial insights into GTFP's capacity to harmonize productivity with environmental stewardship and underscores GTFP's essential role in fulfilling environmental commitments outlined in national and international sustainability frameworks.

Synergistic governance efficiency of industrial pollution and CO2 emissions under the digital economy

Using panel data for 284 Chinese cities, this study explores the nonlinear relationship between the digital economy and the synergistic governance efficiency of industrial pollution and CO2 emissions (SGEIPCE). The study also investigates the transmission mechanism of two-way knowledge flows within this relationship using the double fixed effect model and two-stage least square method. The results show that the digital economy has a significant U-shaped relationship on the SGEIPCE: the impact first decreases and then increases. When the level of digital economy exceeds infection point, the SGEIPCE increases. The marginal effect identified through the heterogeneity analysis indicates that Chinese cities with high innovative talent agglomeration and low industrial Internet level are the first to cross the inflection point of the U-shaped relationship, and the promoting effect of the digital economy on the SGEIPCE is greater in these two types of cites. Further, when the digital economy crosses the inflection point, it indirectly improves the SGEIPCE by increasing the level of knowledge absorption and knowledge overflow. Knowledge overflow is the most critical transmission mechanism by which China's digital economy affects SGEIPCE. These results provide empirical support and a decision-making basis for promoting the mutually beneficial cooperation between digital economy and industrial synergistic governance.

Research on the impact of the digital economy on carbon emissions based on the dual perspectives of carbon emission reduction and carbon efficiency

China's digital economy is currently thriving, with the "dual carbon" targets representing a significant pursuit of economic development. The role of the digital economy in achieving these targets warrants detailed discussion. Using urban panel data from China spanning 2011 to 2021, this paper empirically examines the impact of the digital economy on urban carbon emissions. The findings reveal several key points: Firstly, the digital economy significantly reduces urban carbon emissions and enhances efficiency, a conclusion that remains valid after a series of robustness checks. Secondly, there is a notable structural effect, with different dimensions of the digital economy exhibiting varying impacts on urban emission reduction and efficiency enhancement. Thirdly, green economic efficiency and green technological innovation are crucial mechanisms through which the digital economy facilitates urban carbon emission reduction and efficiency improvement, operating through green development and innovation channels. Fourthly, industrial structure upgrading is a key nonlinear factor reducing the digital economy's impact on carbon reduction, while the digital economy's effect on urban carbon efficiency shows a U-shaped pattern. Lastly, the impact of the digital economy on urban carbon emissions displays significant heterogeneity across cities of different locations, tiers, and characteristics.

Digital Economy and carbon emission efficiency in three major urban agglomerations of China: A U-shaped journey towards green development

Amidst the global consensus on green transformation and sustainable development, the digital economy has emerged as a pivotal catalyst for enhancing carbon emission efficiency. Analyzing panel data of 49 cities in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) from 2011 to 2022, this study explores the U-shaped journey of the digital economy towards green development. The rebound effect on energy consumption from early digital infrastructure investments delays the long-term benefits of digital applications in boosting carbon performance, and the thresholds of DE in BTH, YRD, and PRD regions are 0.158, 0.199, and 0.467, respectively. The efficient resource allocation offers an indirect means to enhance carbon performance in BTH and YRD, albeit with limited efficacy in PRD. With the upgrading of industrial structure, the digital economy in BTH and YRD can achieve higher carbon emission efficiency, and a shape-flip occurs when the upgrading index reaches 6.104 and 6.470, respectively. The interplay between industrial structure upgrading and the digital economy in PRD has yet to yield satisfactory emission reduction outcomes. The study emphasizes the potential necessity for tailored strategic planning that addresses the distinct regional differences among urban agglomerations in their pursuit of green development.

Can digital technology adoption promote environmental innovation in small and medium-sized enterprises (SMEs)? Evidence from China

Despite the widespread acknowledgment in both industry and academia of the substantial potential of digital technology for fostering innovation and sustainable development, there remains uncertainty surrounding whether integrating these technologies can improve environmental innovation in small and medium-sized enterprises (SMEs) due to the liability of smallness. This paper utilizes a panel dataset comprising 1036 Chinese manufacturing SMEs listed between 2011 and 2020 to investigate the influence of different digital technology adoption strategies-specifically, digital technology adoption breadth (DTAB) and digital technology adoption depth (DTAD)-on SMEs' environmental innovation. Additionally, we examine the moderating effects of government subsidies and industrial agglomeration on these relationships. The results reveal that (1) DTAB has a negative effect on SMEs' environmental innovation; (2) DTAD positively affects SMEs' environmental innovation; and (3) both government R&D subsidies and environmental subsidies can positively moderate the relationships among DTAB, DTAD, and environmental innovation within SMEs. These findings are extended and upheld after undergoing a series of further analyses, endogeneity analyses, and robustness tests. Our research suggests that SMEs are not as suited to the broad adoption of digital technologies as large firms; instead, they should focus on the deep application of specific digital technologies to promote environmental innovation.

Digital economy development and carbon emission intensity-mechanisms and evidence from 72 countries

This paper employs two-way fixed effects models, mediation models and spatial panel models to examine the impact of digital economy development on carbon emission intensity in 72 countries from 2013 to 2020 using TIMG index as the proxy variable of digital economic development. The results of this paper show that (1) there is an inverted U-shaped relationship between the development of the digital economy and the carbon emissions in various countries. The development of digital economy first has a positive effect on carbon emissions, and then, its impact turns negative after it reaches a designated inflection point. (2) The results of the mechanism analysis show that the development of the digital economy can reduce carbon emissions by promoting industrial upgrading, while it could have an inverted U-shaped nonlinear effect on carbon emissions through energy efficiency. (3) The development of a country's digital economy may have a significantly inverted U-shaped spatial spillover effect on neighboring countries. This paper provides reference for countries to formulate carbon emission reduction policies and promote the coordinated development of digital economy and environmental protection.

New quality productivity and environmental innovation: The hostile moderating roles of managerial empowerment and board centralization

As new quality productivity (NQP) emerges as a rising star of productivity that can effectively leverage technological innovation and sustainability, this study aims to explore the relationship between NQP and environmental innovation, with a particular focus on the roles of managerial empowerment and board centralization within the context of China A-share listed companies. Utilizing the entire sample of China A-share market from 2013 to 2022, the study analyses the effectiveness of various dimensions reflecting innovation engagement among Chinese listed companies. For measuring NQP, the entropy method is employed to calculate the weights. By controlling for industry and year effects, the study examines both the main and moderating effects of managerial empowerment and board centralization. Additionally, heterogeneity tests, robustness checks, and two-stage least squares (2SLS) estimation were conducted to address endogeneity concerns. The results demonstrate that NQP significantly enhances environmental innovation, with managerial empowerment supporting this positive effect and board centralization obstructing it. The positive effect of NQP is particularly evident in state-owned enterprises, while in heavily polluting industries, the anticipated positive moderating effect of top managers disappears due to strict regulatory environments. Furthermore, board centralization negatively moderates environmental innovation, especially in lightly polluting sectors where internal governance is more sensitive. The study underscores the importance for policymakers to tailor regulations that balance managerial empowerment and board centralization to enhance the transformation of NQP into environmental innovation. Future research is needed to further investigate different background settings and the mechanisms through which NQP influences sustainability.

The impact of data factor-driven industry on the green total factor productivity: evidence from the China

Data factors have become an essential factor of production in today's digital era, and provided renewed energy for China's green and high-quality development. This study analyses the impact of data factor-driven industries on green total factor productivity (GTFP) and the underlying mechanisms using panel data of 277 Chinese cities from 2008 to 2020. The results show that: First, the urban data factor-driven industry can enhance GTFP. Second, the data factor-driven industry can increase the input-output ratio and enhance GTFP by promoting AI technological innovation and AI technological entrepreneurship. Third, the heterogeneity analysis show that in regions with high levels of digital technological innovation, the market size of data factor-driven industries is larger and the effect of data factor-driven industries in enhancing GTFP is more significant. And in regions with low levels of savings, the data factor-driven industry has limited capital availability and is more efficient in using capital, which has a stronger effect on GTFP enhancement. This study provides valuable empirical evidence on the relationship between data factor-driven industries and urban GTFP, and important policy implications for fully leveraging the green economic effects of data factors, and promoting green and high-quality urban development.

How does the digital economy affect the green development of China's industry?

Digital economy is an important force to promote industrial green development. The purpose of this paper is to explore the impact of digital economy on China's industrial green development and its mechanism of action from 2011 to 2019, and further examines the spatial spillover effect of digital economy on industrial green development using the spatial Durbin model (SDM). The results show that the digital economy can significantly promote the improvement of IGTFP, and the development of the digital economy in the region can drive the green development of industry in the peripheral regions through the spatial spillover effect. Green technology innovation has a partial mediating role in the process of digital economy affecting IGTFP. Industries in central cities can gain greater green development from digital economy development relative to industries in peripheral cities. The above findings remain valid after a series of robustness tests.

Impact of digital transformation on green production: Evidence from China

In the global context of development transformation, digital transformation (DT) has emerged as a prevalent practice among international corporations, facilitating the simultaneous enhancement of economic growth. However, limited research on how digital transformation affects green production, especially at a micro level, poses risks by impeding the understanding of strategies for balancing economic growth and environmental sustainability. This study addresses a critical research gap by elucidating the influence of digitization on green total factor productivity (GTFP). We based our findings on a sample of 280 listed non-financial firms from 2007 to 2021 and computed core variables through text analysis and the super-SBM model. The data analysis using fixed effects models, correlation analysis, instrumental variable approach, and difference-in-differences method. The findings underscore the positive impact of DT on enhancing firms' green innovation, investment efficiency, and internal control, consequently significantly elevating the level of GTFP. Additionally, it was observed that normal DT contributes to the sustainable long-term improvement of a firm's GTFP, whereas excessive DT exhibits a positive impact on short-term GTFP. This study's insights into the positive impact of DT on GTFP serve to guide enterprises and policymakers in navigating a transition towards high-quality development, facilitating a balanced approach that fosters environmental conservation alongside economic growth in both emerging and global contexts.

A pathway to sustainable development in China: The impact of local higher education expenditure on green total factor productivity

With the global warming crisis looming, the question of how to advance green total factor productivity (GTFP) has become an important concern confronting many developing countries. Although existing studies have demonstrated that total human capital can improve GTFP, the research has neglected to consider the influence of local higher education expenditure (LHEE), and no research has examined how LHEE spatially affect GTFP. Therefore, based on spatial economics theory, this study explores the spatial autocorrelation of LHEE and GTFP in China's 30 provinces from 2004 to 2021, employing a spatial Durbin model to analyze the spillover effect and influence mechanism of LHEE on GTFP. The results reveal that LHEE and GTFP exhibit positive global spatial autocorrelation. LHEE primarily improves GTFP and its subcomponents through spillover effects. The positive spillover effects in the three regions of China are significantly higher than the direct effects, whereas the direct effects in the eastern and central regions are positive but insignificant. Furthermore, LHEE promotes GTFP by advancing green technological innovation. The findings provide valuable insights to help policymakers address sustainable development goal 4 and develop synergistic regional GTFP growth policies to establish sustainable societies worldwide.

Digital economy exhibits varying degrees of mitigation of air pollution in China: Total cities-economic subdivisions-urban agglomerations

Air pollution is a challenge for many cities. The digital economy enhances support for environmental pollution management, while the mechanisms and scaling heterogeneity remain unclear. This study explored the contribution of digital economy development to PM2.5 concentrations control in China and driving mechanisms in different economic subregions and urban agglomerations. Results show that the spillover transfer effect on air pollution mitigation far exceeded the direct effect at different scales. At the national scale, the air pollution mitigation effect of digital economy was mainly through empowering industrial structure optimization and green technology innovation, while it also affected economic subregions and urban agglomerations through varying scenario combinations of pathways with structural optimization, green production, resource allocation, and technology innovation. Research findings provide support for cross-regional joint management strategies of digital economy and air quality and designing regionally differentiated pollution control pathways in the digital economy dimension.

A study on the potential of digital economy in reducing agricultural carbon emissions

Agriculture is a significant source of carbon emissions, which have a substantial environmental impact. The digital economy plays a vital role in mitigating these emissions through innovative digital solutions. As a leading agricultural nation, China faces substantial pressure to reduce its agricultural carbon emissions(ACE). This paper aims to thoroughly examine the relationship between the growth of the rural digital economy and ACE. To achieve this, we utilize an extensive panel dataset covering China's provinces from 2011 to 2020, analyzing the dynamic and spatial effects of digital economy development on ACE. The key findings of this research are as follows: (1) The rapid expansion of the digital economy significantly reduces ACE. (2) The impact of digital economic development on lowering ACE varies spatially, with a clear progression from eastern to western regions. (3) The digital economy helps reduce ACE through three specific channels: fostering technological innovation, enhancing scale efficiency management, and providing agricultural financial incentives. Based on these findings, this study proposes policy recommendations to improve digital infrastructure, promote balanced regional development in the digital economy, and optimize the management of agricultural science and technology. These policy insights aim to transform agriculture and achieve the goal of reducing ACE, thereby contributing to broader environmental sustainability.

Does the digital economy improve comprehensive total factor productivity in China?

Total factor productivity is an important symbol of high-quality economic development. At present, the question of whether the digital economy can infuse fresh impetus into enhancing total factor productivity has emerged as a prominent concern in China. This paper constructs a new undesirable output to measure comprehensive total factor productivity (CTFP) with the slack-based measure (SBM) undesirable Malmquist-Luenberger index by using 2011-2020 Chinese provincial panel data. Then, this paper explores the impact of the digital economy (DIG) on CTFP with a fixed effects (FE) panel model and a mediating effect model. The results show that CTFP increases by an average of 3.9%, technical efficiency contributes -1.1%, and the contribution rate of technological progress is 5.0%. Technological progress is the main source of CTFP growth. The empirical findings show that the DIG has a positive and significant impact on CTFP. This paper conducts various robustness tests, and the results remain consistent with the previous conclusion. Moreover, mechanism tests suggest that the promoting effect of the DIG on CTFP can be attributed to three main effects: technological innovation, the factor endowment structure and the educational level. Furthermore, the results of heterogeneity analysis demonstrate that the promoting effect of the DIG on CTFP exists in China's eastern, central and western regions. The findings of this research can serve as a valuable reference for informing decision-making processes related to environmental governance and high-quality economic development in China.

Impact of digital technology innovation on carbon intensity: evidence from China's manufacturing A-share listed enterprises

Current studies do not provide a consensus on whether digital technology innovation can reduce enterprise carbon intensity despite the rise of the digital economy. This paper examines the role and influence pathway of digital technology innovation on enterprise carbon intensity using data from A-share listed enterprises in China's manufacturing industry from 2012 to 2021. The findings indicate that (1) digital technology innovation has been found to significantly reduce enterprise carbon intensity, as confirmed by numerous robustness and endogeneity tests. However, its inhibitory effect on carbon intensity shows a marginal decreasing trend. (2) In the heterogeneity analysis, it was found that digital technology innovation significantly reduces the carbon intensity of consuming coal, coke, kerosene, and diesel. From various perspectives, including enterprise, industry, and external environment, there are significant differences in the carbon reduction effects of digital technology innovation. (3) The analysis of impact paths reveals that digital technology innovation can affect enterprise carbon intensity through three paths: improving productivity, enhancing green innovation efficiency, and adjusting energy consumption. (4) Upon further analysis, it was discovered that the spillover effect of digital technology innovation is more pronounced in the industry cohort of enterprises. Additionally, digital technology innovation plays a positive role in enhancing enterprise ESG performance. The paper's findings offer empirical evidence and decision-making references for the government to develop reasonable policies for reducing carbon emissions, promoting green and low-carbon enterprise transformation, and actively and steadily achieving the goal of carbon peaking and carbon neutrality.

How does the development of the digital economy influence carbon productivity? The moderating effect of environmental regulation

Improving carbon productivity is of great significance to China's "30 · 60" carbon target, while the development of the digital economy is a driving force for green transformation. However, few studies discuss the relationship between the digital economy and carbon productivity. We investigate the influence of digital economic development on carbon productivity using panel data from 30 Chinese provinces from 2011 to 2020. Spatial econometric and moderating effects are considered. The results show that (i) digital economy has a positive direct and negative spatial spillover effect on carbon productivity, and this conclusion is still valid after the robustness test and endogeneity test; (ii) digital infrastructure has a greater impact on carbon productivity than digital industrialization and industrial digitalization; (iii) the mechanism analysis shows that environmental regulation negatively moderates the relationship between the digital economy and carbon productivity; (iv) heterogeneity analysis shows that the effect of the digital economy on carbon productivity is more obvious in the central region compared to the western region, while it is not significant in the eastern region. Overall, this paper not only provides a new analytical perspective for understanding the improvement of carbon productivity in the digital economy but also provides policy inspiration for promoting carbon peak and carbon neutrality goals.

Effects of carbon emission trading system on corporate green total factor productivity: Does environmental regulation play a role of green blessing?

Extant studies focus on the impact of environmental regulation on regional economic growth or environmental pollution, and a lot of research outcomes have been made. However, from the perspective of corporate green sustainable development, the question of whether carbon emission trading represents a "green blessing" remains unclear. To address this issue, we employ a staggered difference-in-differences model to investigate the effects and mechanisms of the carbon emissions trading pilot policy (CETPP) on the green total factor productivity (GTFP) of listed manufacturing companies in China. Our results demonstrate that: a) CETPP can effectively promote corporate GTFP, and the robustness of this result is verified through a series of checks; b) the mediating role of environmental, social, and governance (ESG) performance is critical in the relationship between CETPP and corporate GTFP, with environmental and governance performance serving as two key transmission channels; and c) CEO green experience and public environmental concern both play the moderating roles on the relationship between CETPP and GTFP; d) CETPP has a stronger positive impact on GTFP of private enterprises and enterprises in the maturity life cycle; and e) CETPP has a spatial spillover effect on GTFP, and the effect will decay as spatial distance increases. Our study offers both theoretical and practical implications for enterprises to achieve their green economic development objectives, so as to promote China's high-quality development.

Can digital economy compensate the effect of aging on total factor productivity?

In China, the number of senior citizens has grown, along with the burden of old age, and aging has hampered economic growth. The advent of the digital age has led to the emergence of the digital economy as a new engine for economic growth. This paper uses DEA-Malmquist index model to measure the total factor productivity growth rate of 31 provinces in China from 2011 to 2021, and uses the moderating effects model to empirically investigate the relationship between the digital economy, aging and total factor productivity, and to verify whether the development of the digital economy can mitigate the negative impact of aging on total factor productivity. The results show that aging inhibits total factor productivity growth, and the digital economy can promote total factor productivity growth. Digital economy can alleviate the negative impact of aging on total factor productivity growth, and has a moderating effect. Digital economy plays a moderating role by improving the level of human capital and facilitating technological progress. The regional heterogeneity analysis shows that the moderating effect of the digital economy exists in the eastern and western regions and the southern region, but not in the central region and the northern region. Furthermore, the digital economy has a moderating effect on both the high and low aging groups. The research in this paper not only helps to evaluate the productivity effects of the digital economy, but also has important implications for finding ways to mitigate the negative effects of aging.

Investigating the effects of ICT, education, and R&D on economic efficiency and technology heterogeneity: A cross-country analysis

This study explores the impact of information and communication technology (ICT), education, and research and development (R&D) on countries' economic efficiency and technology heterogeneity. A panel of 52 countries, classified into developed (31 sample countries) and developing (21 sample countries) during 2011-2019, were the data sources for the analysis. We obtained relative country-level economic efficiency and technology gap inefficiency estimates from a novel Bayesian data envelopment analysis (DEA) approach. Bias-corrected estimates yielded by this technique have proven to be valid. We then regressed the estimates on ICT, education, and R&D proxy variables using a two-step and an iterative generalized method of moments (GMM) for linear dynamic panel data. Our analysis mitigates possible feedback effects between the explanatory and response variables, as well as possible endogeneity. The novelty of this work goes beyond the use of a new data analysis technique, investigating the impact of the three factors mentioned above and the country classification on technology heterogeneity caused by differences in countries' market structures, regulatory frameworks, economic and knowledge ecosystems, and cultures. Based on this study's findings, fixed broadband subscriptions have the most significant effect on economic efficiency improvement, while R&D is the main driver for reducing technology gap inefficiency. Specifically, ICT-facilitated knowledge spillovers within and across country groups through R&D cooperation play a significant positive role in closing the technology gap. This finding is consistent with the catch-up theory.

Digitization and carbon emissions: how does the development of China's digital economy affect carbon intensity?

The digital economy and the pursuit of carbon peak and carbon neutrality have emerged as crucial focal points for China's future development. However, the intricate relationship between the digital economy and carbon intensity remains uncertain. Based on the construction of the digital economy evaluation index system, using panel data for 30 provinces in China from 2011 to 2019, this study estimates the impact of the digital economy development on carbon intensity by adopting the system-generalized method of moments (SYS-GMM) technique. The results show that the digital economy can effectively reduce the carbon intensity. This conclusion was supported by robustness tests. However, the carbon emission reduction effect of the digital economy exhibits heterogeneity with respect to the digital economy dimensions and regions. In addition to digital industrialization and industrial digitization reducing the carbon intensity, the digital economy development carrier has an inverted U-shaped nonlinear relationship with carbon intensity. Additionally, the digital economy has a more obvious inhibitory effect on carbon intensity in the eastern region. Most importantly, besides the mediating effects of technological progress and financial development, this paper finds that the digital economy can increase carbon intensity through human capital accumulation. These conclusions provide a certain scientific basis for the effective implementation of China's digital economy and carbon peak and carbon-neutral development strategy.

How does the digital economy affect the provincial "zero-waste city" construction? Evidence from China

The digital economy is playing a crucial effect in the field of environmental governance. Digital and intelligent management is an essential means to fully realize the "zero-waste city" construction. The present paper investigates the impact of digital economy on China's provincial "zero-waste city" construction. The results indicate that digital economy can contribute to "zero-waste city" construction. The digital economy has a positive nonlinear effect on the construction of "zero-waste city," but the marginal effect is diminishing. The digital economy can facilitate "zero-waste city" construction by improving industrial structure upgrading and green technology innovation. Heterogeneity analysis reveals that digital economy contributes to the construction of "zero-waste city" in the eastern and western regions and high-level environmental regulation regions, while this impact is insignificant in the central region and low-level environmental regulation regions. The digital economy exerts the most significant positive influence on waste resource recycling followed by waste final disposal and then waste reduction at the source. These findings underscore the effect of digital economy in fostering "zero-waste city" construction and promoting sustainable waste management. The present study provides new ideas for the "zero-waste city" construction in emerging developing countries such as China.

Digital economy and green total factor productivity in China

The development of information technology has created conducive conditions for the digital economy. The digital economy is regarded as a critical pathway for transforming traditional economic models. Green total factor productivity serves as an indicator for assessing the quality of economic development. During pivotal periods of economic transition, the digital economy and green total factor productivity have emerged as two prominent themes for achieving sustainable economic development. But the impact of digital economy on green total factor productivity is less discussed. Innovation environment refers to a confluence of conditions shaped by factors such as talent, funding, cultural atmosphere and government policies, all of which collectively support innovative activities within a region. The institutional environment encompasses the aggregate of economic, political, social, and legal rules. Currently, there is little discussion on bringing innovation environment and institutional environment into the impact of digital economy on green total factor productivity. To fill the research gap, this paper adopts the Slack based measure-Directional distance function model and Malmquist-Luenberger productivity index to measure green total factor productivity in each region based on the panel data collected from 30 provinces in China from 2004 to 2019. Generalized Method of Moments method is constructed to carry out an empirical study on the impact of digital economy on green total factor productivity. This paper constructs a panel threshold model with innovation environment and institutional environment as threshold variables. In further analysis, this paper employs panel quantile regression for the empirical analysis of the impact of the digital economy on green total factor productivity. Further analysis elucidates the evident disparities in the influence of the digital economy on green total factor productivity at various levels. The research results can provide a guide for discussing the green value of the digital economy and its role in fostering the development of a green economy.

Can greater openness improve green economy efficiency of countries along the Belt and Road Initiative?

Openness is the core concept of the Belt and Road initiative (BRI), which plays a significant role in promoting the sustainable economic development of countries along the BRI. This study uses the entropy method to measure openness based on six dimensions: trade, investment, finance, tourism, technology, and information. Simultaneously, a super-SBM model with undesired output is proposed to measure green economy efficiency (GEE). Using the panel data of 66 countries along the BRI from 2008 to 2019, we empirically examine the impact of openness on GEE. The results are as follows: (1) The openness level of countries along the BRI is generally increasing, but the relative differences between countries tend to widen. (2) Openness has a significant U-shaped nonlinear effect on GEE, and the conclusion is still valid after considering the robustness test; (3) The spatial econometric model shows that openness not only affects the GEE of the local country, but also has a spillover effect on neighboring countries. Therefore, we believe that BRI countries should strengthen policy communication, break down border barriers, actively promote the orderly flow and diffusion of openness elements, and pay attention to the quantity and quality of openness development, which is key to the high-quality construction of the BRI.

The Collision of digital and green: Digital transformation and green economic efficiency

Enhancing the green economy efficiency (GEE) is crucial for building a sustainable economy. How can the rapidly advancing digital transformation contribute to this process? The paper empirically examines the direct and spatial spillover effects of digital transformation on cities' GEE in China. This study utilizes the National E-commerce Pilot City (NEPC) policy as a quasi-natural experiment of regional digital transformation and employs the staggered difference-in-differences (DID) method with heterogeneous effects. The findings reveal that (i) implementing the NEPC policy significantly increases urban GEE by 2.6%, corresponding to a 16% increase in the mean of GEE. This effect is particularly pronounced in non-resource-based cities and cities with high Internet penetration. (ii) The mechanism test shows that the pilot policy positively affects GEE by promoting green structural transformation, enhancing green innovation, and strengthening public environmental concerns. (iii) The study highlights a positive spatial spillover effect of the NEPC policy on the GEE of nonpilot cities. (iv) The adoption of the NEPC plays a pivotal role in advancing energy use and carbon emission efficiency. This paper expands the existing knowledge on the green development effects of the digital economy while offering valuable policy insights for building an "Inclusive Green Economy".

The impact of digital economy on carbon total factor productivity: A spatial analysis of major urban agglomerations in China

Amid global climate imperatives and intensified economic competition, pivoting from China's conventional growth paradigms to innovative economic catalysts emerges as pivotal for its transformative agenda. Drawing on panel data from 141 principal urban conglomerates spanning 2011-2021, this investigation delves into the intricate nexus between the digital economy and carbon total factor productivity. Our empirical analysis unveils a U-shaped trajectory characterizing the digital economy - carbon total factor productivity interplay, accompanied by a congruent spatial spillover dynamic. While digital economy fortifies environmental governance mechanisms through amplified data and media channels, such regulatory frameworks, albeit efficacious in emission abatement, may inadvertently impede economic vitality, thus attenuating carbon total factor productivity. Progressing from digital economy's foundational phase to its comprehensive deployment, its reverberations on capital productivity manifest in a U-shaped curve, invigorating local carbon total factor productivity while potentially undermining adjacent regions. This digital economy - carbon total factor productivity interrelation is accentuated in advanced, non-resource-reliant metropolises with subdued innovation propensities. This discourse proffers nuanced policy implications for sculpting digital economy trajectories and bolstering carbon total factor productivity in a sustainable context.

The moderate level of digital transformation: from the perspective of green total factor productivity

In the context of accelerated development of the digital economy, whether enterprises can drive green total factor productivity (GTFP) through digital technology has become the key to promoting high-quality development of the economy and achieving the goal of "dual-carbon", However, the relationship between digital transformation and GTFP is still controversial in existing studies. Based on the data of 150 listed companies in China's A-share energy industry from 2011 to 2021, this study empirically analyzes the impact of digital transformation on GTFP using a fixed-effect model. The study shows an inverted U-shaped nonlinear effect of digital transformation on enterprises' GTFP, and the conclusion still holds after a series of robustness tests. Mechanism analysis shows that enterprise investment efficiency and labour allocation efficiency play a significant mediating role in the above inverted U-shaped relationship, in which the inverted U-shaped relationship between digital transformation and GTFP mainly stems from the influence of enterprise investment efficiency. Heterogeneity analysis finds that the inverted U-shaped relationship between digital transformation and GTFP of enterprises is more significant in large-scale enterprises, new energy enterprises and enterprises in central and western regions. The study's findings provide important insights for enterprises to promote digital transformation and realize the green and high-quality development of the energy industry.

The impact of digital economy on green total factor productivity considering the labor-technology-pollution factors

The digital economy provides new impetus for the high-quality development of manufacturing industry. Through the DEA-Malmquist model and panel regression model, this paper confirmed that there is a positive and significant relationship between the development of digital economy and the green total factor productivity (GTFP) of manufacturing industry. The research result is as follows: (1) the development of digital economy can enhance the overall GTFP of manufacturing industry. (2) The green technology progress brought by the development of digital economy is the main path to promote the GTFP of manufacturing industry. (3) The heterogeneity analysis shows that the impact of digital economy on GTFP of high pollution manufacturing industry is significantly positive, the impact of labor-intensive manufacturing industry is significantly negative, and the impact of technology intensive manufacturing industry is not obvious. The contributions of this study are as follow. In terms of theory, this study theoretically continues Solow's classical theory, demonstrating the scientific nature of digital technology progress in promoting GTFP growth. In empirical analysis, this study build a new digital economy development level evaluation index system based on the perspective of manufacturing industry. In addition, this study also add a labor-technology-pollution perspective for the development of relevant policies.

Digital economy impact on inclusive green growth: intermediary and spatial spillover effects in China

As a new economic form that has emerged from the technological and digital revolution, the digital economy has great benefits to the green development of the economy, protection of the ecological environment, and improvement in social well-being. This study examines whether the digital economy affects the inclusive green growth (IGG). Measurement index system for the digital economy and IGG from 2013 to 2020 in China was constructed and the entropy evaluation method and super-efficiency epsilon-based measure (Super-EBM) model was used to evaluate them. We examined the direct effect, mediation effect, and spatial spillover effect of the digital economy on IGG using the basic regression model, mediating effect model, and the spatial Durbin model. Our results revealed that the development of the digital economy has clear regional differences. The role of digital economy on IGG has positive direct effects and positive spatial spillover effects. The digital economy affects IGG through industrial structure upgrading, so industrial structure upgrading has a significant intermediary effect. By comparing the coefficients, we found that the spatial spillover effects are stronger than the direct effects. Absorbing the spillover of the digital economy in surrounding areas is particularly important for promoting IGG. Heterogeneity analysis revealed that the digital economy is better for IGG and releases more digital dividends in eastern China. Finally, the research conclusions of this paper provide reference for the Chinese government to formulate relevant policies to deepen the integration of digital information technology and IGG, and promote the coordinated development of regional digital economy and IGG.

Appraising the role of the digital economy in global decarbonization: A spatial non-linear perspective on globalization

In the context of globalization, the role of the digital economy in carbon emissions may generate spatial spill over effects. This study comprehensively applies a spatial model to understand the nexus between the digital economy and carbon emissions in 67 economies from 2010 to 2019. Specifically, this study contributes by introducing a spatial panel threshold model, which helps to present the new evidence regarding decarbonization process. Empirical findings exemplify that the digital economy remarkably reduces local carbon emissions, with the positive spatial spill over effects being salient. The spatial moderating effect model uncover that globalization positively affects the nexus between the digital economy and carbon emissions. Interestingly, the spatial panel threshold model designates that the digital economy's reduction effect on local carbon emissions will be tightened, whereas the positive spatial spill over effects turn negative only when globalization surpasses a threshold. Our model has the potential to explain some results that traditional models cannot reach.

Digital economy, green technology innovation, and productivity improvement of energy enterprises

This study aims to address the important question of whether the digital economy can be deeply integrated with the energy sector to break through the resource and environmental constraints and thus enhance the productivity of energy companies. Using a sample of Chinese energy-listed companies, we comprehensively investigate the impact of the digital economy on the productivity of energy firms using the OLS method, mediated effects model, instrumental variables method, and difference-in-differences model. Research shows that the development of digital economy can significantly improve the productivity of energy enterprises. This effect is more obvious in eastern cities, non-resource-based cities, state-owned enterprises, and enterprises with high cash holdings. Green technological innovation in alternative energy production, transportation, and administrative supervision and design is an important channel for improving productivity in the digital economy. Internet development and digital inclusive finance can also improve the productivity of energy enterprises. "National Big Data Pilot Zone" and "Broadband China" pilot cities can play a policy role in improving the productivity of energy enterprises. The findings provide important insights for promoting the integration of the digital revolution with the energy technology revolution and accelerating the green development and digital transformation of the energy sector.

What is affecting the improvement of green innovation efficiency in the old industrial base: evidence from Northeast China

Green innovation is an important driving force for high-quality development and is vital for reinvigorating the old industrial bases in Northeast China. As such, this study investigates the spatial-temporal evolution characteristics and factors influencing green innovation efficiency (GIE) in Northeast China from 2005 to 2020, using the super-efficient EBM-Malmquist model, kernel density estimation, and random forest model. The results show the following. (1) The "growth effect" of technological change is the main force driving GIE improvement; the "horizontal effect" of pure technical efficiency change has started to play an important role; and the club convergence characteristics of GIE in Northeast China have started to be optimized. (2) GIE in Northeast China shows significant spatial differentiation. The urban agglomeration of Mid-southern Liaoning and Harbin-Changchun has had high values for GIE, indicating that green innovation has a cyclic cumulative effect and the spatial pattern of green innovation needs to be further optimized. (3) The random forest model is more accurate and provides more trustworthy results compared with the traditional multiple linear regression model. The results of random forest model measurement illustrate that the number of digital economy enterprises, public finance expenditure, GDP per capita, and vegetation coverage play a positive role in promoting GIE. The proportion of the non-farm population and industrial agglomeration plays a negative role in GIE. In the same period, the contribution of the number of digital economy enterprises≥0.41, public expenditure ≥0.47, GDP per capita≥0.39, and vegetation coverage≥0.36 to GIE reach maximum values and then remain unchanged.

Unleashing the power of informatization: How does the "information benefiting people" policy affect green total factor productivity?

Information development is a necessary means for China to achieve technology force and an effective path toward sustainable development. Regarding the "information benefiting people" policy led by the Chinese government as a quasi-experiment of information technology, this study builds an analysis framework for the impact of informatization on green total factor productivity (GTFP). Based on panel data at the Chinese city level from 2006 to 2019, this study further empirically evaluates the mechanism path, heterogeneity, and spatial spillover effects between informatization and GTFP by using a difference-in-difference (DID) model, a mediating model, and a spatial DID model. The results show that (1) the information benefiting people policy contributes considerably to greater GTFP levels in the pilot cities; (2) the policy also promotes the rapid growth of GTFP by fostering the advancement of education, the share of the number of ICT employees, and green technology innovation; (3) the information benefiting people policy raises GTFP in the eastern cities, small cities, and non-old industrial based cities; and (4) the policies lead to a large rise in local GTFP levels, but a decline in GTFP in surrounding cities. This paper offers valuable reference suggestions for the Chinese government to implement informatization-policies to support green development.

The nonlinear effects of digital economy on the low-carbon green total factor productivity: Evidence from China

The production process has undergone significant changes due to the exponential expansion of digital economy, leading to implications for carbon emissions. This study aims to establish the digital economy (DE) index and measures low-carbon green total factor productivity (CTFP) in 30 Chinese provinces between 2011 and 2020. Utilizing the panel fixed-effects model and the spatial model, it examines the nonlinear effects of DE on CTFP and investigates its underlying mechanism. The results reveal the following findings: (1) CTFP has experienced a decline over the past decade, while DE has exhibited significant growth. (2) the contribution of DE to CTFP follows a U-shaped pattern, indicating that CTFP experiences a significant increase once DE reaches a specific turning point. (3) DE affects CTFP by influencing technological innovation progress. (4) The impact of DE on CTFP exhibits regional heterogeneity, with the eastern region experiencing a spatial spillover effect. These rigorous empirical findings provide valuable insights for national policymakers, emphasizing the importance of prioritizing the digital economy and technological innovation when formulating policies to facilitate sustainable economic growth and reduce carbon emissions.

The synergistic effect of digital economy and manufacturing structure upgrading on carbon emissions reduction: Evidence from China

Promoting the integration of the digital economy with the manufacturing-based real economy is beneficial to avoid the detachment of economic development from tangible industries. Whether the low-carbon transformation can be achieved in this integration process is also an important issue. So, taking China for instance, we theoretically analyze the impact mechanism of the integration of the digital economy with three major categories of manufacturing (labor-intensive, capital-intensive, and technology-intensive) on carbon emissions, and empirically test those effects based on 30 provinces in China from 2011 to 2019. The following conclusions are drawn: (1) The development of the digital economy can reduce carbon emissions. (2) The integration of the digital economy with different categories within the manufacturing industry causes different effects on carbon emissions reduction, shown as a structural upgrading type of carbon emissions reduction, i.e., the deeper integration between digital economy and technology-intensive manufacturing contributes to a multiplier effect in carbon emissions reduction. (3) The efficiency improvements benefited from the integration with the digital economy in technology-intensive manufacturing are the main reason for the structural upgrading type of carbon emissions reduction. Therefore, policy should aim at accelerating the integration of the digital economy with advanced manufacturing to realize comprehensive low-carbon transformation.

Spatio-temporal heterogeneity of the coupling between digital economy and green total factor productivity and its influencing factors in China

The synergy of the digital economy and green total factor productivity (TFP) is the foundation for achieving beneficial outcomes for both the economy and environment. This synergy is also the catalyst for high-quality development and sustainable economic growth in China. The study applied a modified Ellison-Glaeser (EG) index, super-efficiency slacks-based measure (SBM) with a Malmquist-Luenberger (ML) index, coupling coordination degree, and other models to explore the spatiotemporal heterogeneity of the coupling between the digital economy and green TFP from 2011 to 2020 and also analyzed the influencing factors of the coupling. The results show that the coupling between the digital economy and green TFP showed an overall upward trend from imbalance to synergy during the study period. The distribution of the synergistic coupling expanded from point-like to band-like, and there was a significant spreading pattern from the east to the center or west China. The number of cities in a transition state decreased significantly. Spatial jumps, a coupling linkage effect, and evolution in time were prominent. Additionally, the absolute difference among cities expanded. Although coupling in the west experienced the fastest growth rate, the coupling in the east and resource-based cities showed significant benefits. Coupling did not reach an ideal coordinated state, and a neutral interaction pattern remains to be formed. Industrial collaboration, industrial upgrading, government support, economic foundation, and spatial quality all positively impacted the coupling; technological innovation had a lagged effect; and environmental regulation has not reached its full potential. Further, the positive effects of government support and spatial quality performed better in the east and in non-resource-based cities. Due to the optimization of industrial structure, the coupling of the west and resource-based cities achieved better dividends; however, spatial quality needs further improvement. Therefore, the efficient coordination of China's digital economy and green TFP requires a scientific, reasonable, localized, and distinctive approach.

Can the digital economy development achieve the effect of pollution reduction? Evidence from Chinese Cities

As a new economic form, the digital economy is not only empowering new impetus to economic growth, but also reshaping specific business forms of economical operation. Therefore, we conducted an empirical test to verify the impact and mechanism of pollution reduction in the digital economy, based on the panel data of 280 prefecture-level cities in China from 2011 to 2019. The results show that, first the development of the digital economy indeed has the positive effect of realizing pollution reduction. The results of mediating effect test indicate the influence mechanism mainly rely on promoting the upgrading of industrial structure (structural effect) and upgrading the level of green technology innovation (technical effect). Second, the results of regional heterogeneity analysis show that the emission reduction effect of digital economy development on four pollutants is characterized by weakness in the east and strong in the west in regional distribution. Third, the development of digital economy has a threshold effect on the level of economic development to achieve its pollution reduction effect. Further identification of the threshold effect indicates that the higher the level of economic development, the better in emission reduction effect.

Towards inclusive green growth: does digital economy matter?

In this decade, China has been pursuing an inclusive green growth strategy. Concurrently, the digital economy, which relies on the Internet of Things, big data, and artificial intelligence, has experienced explosive growth in China. The digital economy's capacity to optimize resource allocation and reduce energy consumption potentially makes it a conducive channel towards sustainability. Using the panel data of 281 cities in China from 2011 to 2020, we theoretically and empirically explore the impact of the digital economy on inclusive green growth. Firstly, we theoretically analyze the potential impact of the digital economy on inclusive green growth using two hypotheses: accelerating green innovation and promoting the industrial upgrading effect. Subsequently, we measure the digital economy and inclusive green growth of Chinese cities using Entropy-TOPSIS and DEA approaches, respectively. Then, we apply traditional econometric estimation models and machine learning algorithms to our empirical analysis. The results show that China's high-powered digital economy significantly promotes inclusive green growth. Moreover, we analyze the internal mechanisms behind this impact. We find that innovation and industrial upgrading are two plausible channels that explain this effect. Additionally, we document a nonlinear feature of diminishing marginal effects between the digital economy and inclusive green growth. The heterogeneity analysis shows that the contribution weight of the digital economy to inclusive green growth is more remarkable in eastern region cities, large and medium-sized cities, and cities with high marketization. Overall, these findings shed more light on the digital economy-inclusive green growth nexus and provide new insights into understanding the real effects of the digital economy on sustainable development.

The impact of investor sentiment on firms' green total factor productivity-facilitator or inhibitor?

Investor sentiment does not only have negative impacts. It may also improve green total factor productivity by invigorating funds. This research constructs a new indicator at the firm level to measure the green total factor productivity of firms. We research the effect of investor sentiment on firms' green total factor productivity using a sample of Chinese heavy polluters listed on Shanghai and Shenzhen A-shares between 2015 and 2019. Through a series of tests, the mediating role of agency costs and financial situations is confirmed. It is discovered that the digitization of businesses facilitates the effect of investor sentiment on the green total factor productivity of businesses. And when managerial competence reaches a certain threshold, the impact of investor sentiment on green total factor productivity is amplified. Tests for heterogeneity reveal that high investor sentiment has a larger impact on green total factor productivity in firms with superior supervision.

Towards green economic recovery: how to improve green total factor productivity

Achieving green economic recovery is crucial to improving environmental quality and sustainable development. This study examines the influence of new digital infrastructure on green total factor productivity (GTFP) using panel data from 30 regions in China from 2008 to 2019. The results are as follows: (1) New digital infrastructure has a significant improvement effect on GTFP. After a series of robustness tests, the conclusion is still valid. (2) The improvement effect of new digital infrastructure on GTFP shows significant heterogeneity. In regions with high industrial agglomeration, high environmental regulation and strong government environmental preference, the improvement effect of new digital infrastructure on GTFP is more obvious. (3) New digital infrastructure improves GTFP through green technology innovation and factor allocation optimization. The government should strengthen the fiscal incentives for green technology development while increasing R&D investment in fiscal expenditure, thus promoting green economic recovery.

Can new energy demonstration city policy reduce carbon emissions? A quasi-natural experiment from China

Against achieving carbon peaking by 2030 and carbon neutrality by 2060 context in China, the new energy demonstration city policy (NEDCP) has a crucial function to perform in promoting resource utilization efficiency, building the green development policy system, and facilitating carbon emission reduction. However, existing research has rarely investigated the contribution of NEDCP on carbon reduction. To investigate the policy effect of NEDCP, the differences-in-differences (DID) model is introduced to quantify the influence of NEDCP on carbon reduction, taking a statistical sample of 285 Chinese cities over the period 2005-2017 on the basis of exploring the intrinsic mechanism of NEDCP on carbon emissions. The statistical results reveal that NEDCP significantly inhibits carbon emissions. NEDCP's dampening impact on carbon reduction is more pronounced in the eastern area but not in other areas. City size and resource endowment heterogeneity results suggest that NEDCP significantly inhibits the output of carbon emissions in non-resource-based and large cities but insignificantly in resource-based and small- and medium-sized cities. Finally, we conclude that policy-makers should not only broaden the scope of NEDCP implementation continuously but also design relevant policy combination tools following the basic characteristics of each city to provide institutional guarantees for achieving carbon emission reduction.

Does digital finance enhance industrial green total factor productivity? Theoretical mechanism and empirical test

The development and application of digital finance has brought profound changes to the real economy, and its impact on industrial green total factor productivity is worthy of attention and evaluation. The industrial green total factor productivity of each province in China is measured by using EBM-ML index with the provincial panel data collected from 2011 to 2020. The panel fixed effects model is used to estimate the impact of digital finance on industrial green total factor productivity. The intermediary effect model is constructed to analyze its conduction mechanisms. The heterogeneity of the impact of digital finance on industrial green total factor productivity is further explored. The results indicate that digital finance makes a significant contribution to the promotion of industrial green total factor productivity. Digital finance indirectly promotes the enhancement of industrial green total factor productivity by promoting technological innovation, driving industrial upgrading and stimulating entrepreneurial dynamism. The impact of digital finance on industrial green total factor productivity has obvious sub-dimension heterogeneity and regional heterogeneity. Based on the above conclusions, we also suggest policy recommendations such as unblocking the conduction channels of digital finance and implementing the differentiated digital finance development strategy. The highlight of this paper is that it takes digital finance as the entry point and shifts the research content to the real economy, broadening the research perspective of "digital finance".

Can artificial intelligence achieve carbon neutrality? Evidence from a quasi-natural experiment

Introduction

As the global climate crisis worsens, carbon neutrality has attracted the attention of various nations.

Methods

Based on panel data from 282 Chinese prefecture-level cities from 2008 to 2019, this research considers the execution of the artificial intelligence strategy as a quasi-natural experiment. It uses the difference-in-differences (DID) model to evaluate the effect of artificial intelligence construction on carbon emission reduction.

Results

The findings indicate that implementing the artificial intelligence strategy into practice can lower carbon emissions and advance carbon neutrality, and this conclusion still passes after various robustness tests. The mediating effects reveal that developing green technologies and upgrading the industrial structure are crucial mechanisms for achieving carbon neutrality. The implementation effect varies with time, geographical location, natural resource endowment, and city level.

Discussion

This article examines the influence of artificial intelligence on urban carbon neutrality at the city level, adding to the notion of urban carbon neutrality and providing research support for urban development transformation.

Can the digital economy improve green total factor productivity? An empirical study based on Chinese urban data

With the new generation of technological revolution, the digital economy has progressively become a key driver of global economic development. In this context, how to promote green economic growth and improve green total factor productivity (GTFP) with the help of the digital economy is an important issue that urgently needs empirical research. We adopted the panel data of 278 Chinese prefecture-level cities from 2011 to 2020 to test whether the digital economy improves the GTFP through the Gaussian Mixed Model (GMM) dynamic panel model. The moderating effect model has been used to explore the impact mechanism from the perspectives of industrial structure upgrade and environmental regulation. In addition, a grouping regression was applied to the sample cities to test the heterogeneous impact of the digital economy on the GTFP. Based upon the empirical findings, this work has the following conclusions. First, the digital economy plays a significant role in improving the GTFP. Second, an industrial structure upgrade has a positive moderating effect on the ability of the digital economy to enhance the GTFP. The environmental regulation, in contrast, has a negative moderating effect. Third, the digital economy exerts heterogeneous impacts on the GTFP across regions, but not at the city level.

Impact of Digital Transformation on Enterprise Carbon Intensity: The Moderating Role of Digital Information Resources

In the context of China's "digital power" strategy, the realization of a green and low-carbon shift in manufacturing has become a necessary condition to promote the economy, and the digital factor has increasingly become a new driving force. The text mining and IPCC methods were used to measure manufacturing enterprise digitalization and the level of enterprise carbon emission intensity from 2011 to 2021, respectively. This study then explored the impact of digitalization on manufacturing enterprise carbon emission intensity based on the least squares method model and instrumental variable method model. This research comes to three conclusions. (1) Digitalization can significantly reduce the enterprise carbon emission intensity of China's manufacturing industry, and the influence shows a "marginal increase." (2) Notably, a mechanism analysis indicates the intermediary effect sizes of four crucial intermediaries: green technology innovation > financing constraint > information asymmetry > energy use efficiency. Interestingly, digital information resources positively moderate the positive effect of digitalization on carbon emission intensity through three paths: financing constraints, green technology innovation, and information asymmetry. (3) The influence shows evident signs of heterogeneity-as environmental regulation, financial development, executive education, and R&D quality advance, the inhibiting effect of digitalization on enterprise carbon emission intensity becomes more pronounced. Finally, corresponding policy suggestions are proposed.

Does the Digital Economy Increase Green TFP in Cities?

COVID-19 accelerated the growth of the digital economy and digital transformation across the globe. Meanwhile, it also created a higher demand for productivity in the real economy. Hence, the correlation between the digital economy and green productivity is worth studying as COVID-19 prevention becomes the norm. The digital economy overcomes the limitations imposed by traditional factors of production on economic growth and empowers innovative R&D and resource allocation in all aspects. This study delved into the digital economy by focusing on its green value at different levels of development. The study gathered the green-productivity indices and the principal components of the digital economy for each prefecture-level city in China from 2011 to 2019 and meticulously portrayed their trends in spatial and temporal figures. Meanwhile, regression models were used to verify the mechanism through which digital-economy development influences the changes in green productivity. The results showed that: (1) a higher level of digital economy helps to increase urban green total-factor productivity (GTFP) and that the conclusions of this paper still held after potential endogeneity problems were solved through the instrumental-variables approach; (2) the digital economy will drive an increase in urban GTFP by upgrading firms' production technologies and that digital-economy development encourages green patent applications from firms; and (3) as the digital economy develops, it will also drive urban GTFP increases by removing polluting enterprises from the market and that the higher the level of digital-economy development, the greater the number and probability of polluting enterprises exiting the market. In view of this study's results, the government should increase the importance of the digital economy, strengthen the role of the digital economy in promoting urban green development, and provide more guidance on regional green development with the help of the digital economy.

Exploring the Mechanism of the Impact of Green Finance and Digital Economy on China's Green Total Factor Productivity

In the context of the "double cycle," promoting the development of a green economy is an important goal for China's high-quality economic development in the digital age. This paper uses data from 30 provinces (municipalities and autonomous regions) in China during the 2006-2019 period using the Compiled Green Finance Index (GF) and Digital Economy Index (DE). The interrelationship between green finance, digital economy and green total factor productivity (GTFP) is empirically tested by conducting multiple regressions on panel data from 2006-2019 to perform an empirical analysis. Based on this, further analysis was performed with the threshold model. This study found that green finance and digital economy can contribute well to green total factor productivity, but the combination of the two does not have a good effect on green total factor productivity. Further study found that the green finance and digital economy's contribution to green total factor productivity is mainly derived from technological progress. The regression results based on the panel threshold model show that the more underdeveloped the digital economy is in certain regions, the stronger the role of green finance in promoting efficiency improvement. Therefore, policymakers should formulate differentiated green financial policies according to the level of development of the digital economy and give play to the role of green finance and the digital economy in promoting green total factor productivity.

Impact of Artificial Intelligence on Regional Green Development under China's Environmental Decentralization System-Based on Spatial Durbin Model and Threshold Effect

Artificial intelligence (AI) is the core technology of digital economy, which leads the transition to a sustainable economic growth approach under the Chinese-style environmentally decentralized system. In this paper, we first measured the green total factor productivity (GTFP) of 30 Chinese provinces from 2011 to 2020 using the super-efficiency slacks-based measure (SBM) model, analyzed the mechanism of the effect of AI on GTFP under the environmental decentralization regime, and secondly, empirically investigated the spatial evolution characteristics and the constraining effect of the impact of AI on GTFP using the spatial Durbin model (SDM) and the threshold regression model. The findings reveal: a U shape of the correlation of AI with GTFP; environmental decentralization acts as a positive moderator linking AI and GTFP; the Moran index demonstrates the spatial correlation of GTFP; under the constraint of technological innovation and regional absorptive capacity as threshold variables, the effect of AI over GTFP is U-shaped. This paper provides a useful reference for China to accelerate the formation of a digital-driven green economy development model.