Resource regulation and green innovation: Evidence from China's water rights trading policy.

Green innovation is the pivotal part connected with achieving urban sustainable development. Resource regulation, represented by water rights trading policy (WRTP), is playing an increasingly important role in supporting urban green innovation (UGI). Therefore, this paper uses the WRTP conducted in 2014 in China as a quasi-natural experiment to evaluate the net effect of resource regulation on green innovation by the identification methods of difference-in-differences (DID) model. The results show that: (1) WRTP promotes UGI significantly, and this finding holds after a series of robustness tests. (2)The influencing mechanisms are mainly by optimizing industrial structure and enhancing the efficiency of resource allocation and information exchange efficiency and the promoting function is moderated by urban competitiveness and population agglomeration. (3) The promotion effects are greater in cities with higher level of government intervention, environmental pollution, water using quantity and local economy.(4) WRTP has the spatial spillover effect on UGI. These findings provide insights into sustainable development of water resources, management of water trading market, urban green innovation and sustainable economic development.

Path to pollution and carbon reduction synergy from the perspective of the digital economy: Fresh evidence from 292 prefecture-level cities in China.

The digital economy is a crucial focus for realizing the transformation of old and new kinetic energy in China. It is widely integrated with various fields of the economy and society, constantly providing a new dynamic mechanism with synergetic control of environmental pollution and carbon emissions (SCEPCE). Based on panel data from 292 prefecture-level cities in China from 2011 to 2021, this study discusses the spatial effects and mechanisms of the digital economy on the coordinated control of pollutants and carbon emissions. The study found that: (1) The digital economy has direct and indirect influences on the coordinated control of pollutants and carbon emissions. The digital economy can drive reductions in pollutants and carbon dioxide emissions by upgrading industrial structures and transforming energy structures. (2) Green innovation plays an active regulatory role in the digital economy and structural optimization, particularly in the context of SCEPCE. This interference helps mitigate the impact of the digital economy on pollution and carbon emissions. (3) The digital economy has a significant spatial spillover effect on the coordinated control of pollutants and carbon emissions. (4) The influence mechanism of the digital economy on pollution reduction and carbon reduction synergy exhibits geographical heterogeneity, resource endowment heterogeneity. To enhance the synergy of pollution reduction and carbon reduction, it is essential to bolster support and optimise the digital economy at various levels. This includes reinforcing regional balance, considering spatial spillover effects, and enhancing the leading role of developed cities in the region.

Can carbon emission trading policy break China's urban carbon lock-in?

Greenhouse gas emissions from the use of fossil energy are the main drivers of global warming. China's dominant consumption of fossil energy necessitates adjustments in its energy consumption structure to break free from the carbon lock-in (CLI) phenomenon. Market-based environmental regulations, represented by the carbon trading market (CTM), play an important role in achieving the dual carbon goals of China. Using panel data of 270 prefecture-level cities in China from 2005 to 2020, this study applies a difference-in-difference model to identify the effect of CTM on urban CLI, analyze its transmission mechanism, and further examine the impact of urban characteristic heterogeneity on policy effects from multiple perspectives. Results show that the construction of CTM significantly reduces the degree of CLI of pilot cities; (2) CTM mainly affects urban CLI by promoting urban green technology innovation, industrial structure upgrading, and public green behavior; and (3) the inhibitory effect of CTM on CLI is more significant in cities with high carbon price, industrialization, and digital finance levels. The primary paths toward realizing carbon unlocking include optimizing the institutional design for CTM, enhancing the effective promotion and application of low-carbon technologies, cultivating the green awareness of the public, and increasing government investments in energy-saving and emission reduction techniques.

From bits to green: Unraveling the digital economy's influence on natural resource efficiency.

This study explores the impact of the digital economy (DE) on natural resource efficiency (NRE) across 275 Chinese cities between 2011 and 2021. Through a comprehensive empirical analysis, we find that the DE significantly positively affects NRE. A key moderating factor in this relationship is green technological innovation (GTI), focusing on the quality rather than the quantity of green technology. Our study also uncovers regional variations of moderating effect. Additionally, we identify several mechanisms through which the DE contributes to enhanced NRE, including the transformation of industrial structure and improvements in green total factor productivity. A detailed heterogeneity analysis shows that the DE's impact on NRE varies according to city-specific factors such as natural resource endowment, city size, environmental regulations, and administrative levels. These findings provide a more nuanced understanding of how the DE influences NRE at the urban level, contributing to the broader discourse on sustainable development in the digital age. Our research offers policy recommendations and potential pathways for cities to leverage the DE for greater natural resource efficiency.

Identifying and assessing the multiple effects of informal environmental regulation on carbon emissions in China.

Against the backdrop of the global carbon peak and carbon neutrality goals, the role of informal environmental regulation, epitomized by public engagement, is assuming an increasingly pivotal position within the realm of environmental management. By contrast, amidst the prevailing landscape dominated by formal environmental regulation (command-and-control and market-driven approaches), the environmental effects of informal environmental regulation on carbon emissions have received scant attention. Consequently, we examine the net, nonlinear, and mediation effects of informal environmental regulation on carbon emissions using panel data from 30 provinces in China, from 2003 to 2019. We find that informal environmental regulation has a significant effect on regional carbon emission reduction, especially in the eastern cities, pilot cities, and cities with long-term governor's tenure. Its U-shaped effect is confirmed by changes in environmental decentralization. The key points remain valid after the robustness test and the endogenous processing. The mechanism analysis shows that informal environmental regulation can reduce carbon emissions in the dual channels by improving industrial structure transition and renewable energy substitution. Therefore, this study assesses the management effectiveness of informal environmental regulation and determines the underlying mechanism between it and regional carbon emission reduction to provide a reference and an empirical basis for other countries regarding environmental improvement.

Coordination of industrial structure and eco-efficiency in ecologically fragile areas: A case study of the Loess Plateau, China.

The relationship between industrial structure (IS) and eco-efficiency (EE) is intricate with mutual influence and constraint. Exploring the coordinated relationship between IS and EE is beneficial to the sustainable development of ecologically fragile areas. This paper estimates and analyses the levels of EE and IS in 39 prefecture-level cities of the Loess Plateau, discussing the comprehensive and coordinated development levels between industrial structure rationalization (ISR) and EE, industrial structure advancement (ISA) and EE based on the coupling coordination degree model (CCDM). The results showed that the comprehensive development of the Loess Plateau has rough and imbalanced issues. The EE and IS are developing at a relatively low level, and the spatial distribution shows the development trend of high in the east and down in the west. The CCD of ISA and EE performs better than that of ISR and EE, but neither has reached the collaborative coupling state. The poor CCD score in the Loess Plateau is primarily attributable to its relatively backward degree of integrated EE and IS. The results are expected to provide decision-making support for EE improvement and industrial restructuring in the Loess Plateau and other ecologically fragile areas.

How does digital finance affect industrial structure upgrading? Evidence from Chinese prefecture-level cities.

Digital finance is playing an increasingly prominent role in economic development. This paper examines the impact of digital finance on industrial structure upgrading based on panel data from 289 Chinese prefecture-level cities from 2011 to 2020. The paper adopts fixed effects, mediating effects, and spatial econometric models and the findings are as follows. First, digital finance development significantly boosts industrial structure upgrading in Chinese cities. The evidence remains valid after various robustness tests. Second, digital finance and industrial structure upgrading exhibit positive spatial spillover effects. Third, digital finance indirectly affects industrial structure upgrading through innovation, entrepreneurship and the structure of household consumption channels. Fourth, the influence of digital finance is more significant in cities with more developed economies, less financialization and lower income inequality. Finally, among the sub-indicators of digital finance, the breadth of coverage plays the most significant role, inspiring policymakers and financial institutions to speed up the digitization infrastructure in backward areas.

Synergistic effect of energy and industrial structures on carbon emissions in China.

Energy structure and industrial structure are two crucial economic factors affecting carbon emissions. However, current research often examines them separately, neglecting the potential additional synergistic effect between them. Leveraging the coupling concept from physics, we objectively quantify these synergistic effect and investigate influencing factors on CO2 intensity from a novel perspective of the synergy by combining a coupling coordination model with econometric model of generalized method of moments (GMM) with a panel dataset from China spanning 2007 to 2019. Our estimates indicate that (1) synergy of energy and industrial structures significantly reduces carbon intensity, which is stable after a series of robust check. (2) the reduced effect of synergy can be enlarged by enhancing environmental regulation and green innovation. (3) the inhibiting effect of synergy is significant, mainly occurs in regions with abundant energy resource endowments. Correspondingly, we recommend several policy implications for China and other developing countries.

How does environmental regulation affect industrial structure upgrading? Evidence from prefecture-level cities in China.

This study examines whether and how environmental regulation affects industrial structure upgrading with a panel data of 270 cities between 2006 and 2019. We first adopt two indicators-rationalization and advancement-to quantify industrial structure upgrading and then use kernel density estimation as well as trend surface analysis to investigate these indicators' spatial-temporal pattern. With a spatial Durbin model, we find that environmental regulation has inverted U-shaped and U-shaped direct impacts on rationalization and advancement, and inverted U-shaped indirect impacts on both rationalization and advancement in neighboring regions. Moreover, our subsample tests demonstrate that environmental regulation has various impacts on industrial structure upgrading in different regions. Last, a mediating effect analysis shows that technological innovation is an important path for environmental regulation to promote advancement. Our study provides new evidence for the Porter hypothesis, and offers suggestions for the authorities to formulate and optimize environmental regulation intensity.

Can the marketization of urban land transfer improve energy efficiency?

Local government intervention in land resource allocation can lead to the misallocation of land resources and serious pollutant emissions. As an important market-oriented economic reform in China, the marketization of urban land transfer (MULT) might have the potential to contribute to improving resource allocation efficiency by curbing local government intervention. Therefore, this study aims to provide empirical evidence on the impact of MULT on energy efficiency. We improve the MULT evaluation method to test the mechanism through which MULT affects energy efficiency. The results show that, first, the proportion of land sold by allocation and listing methods, which is characterized by a low degree of marketization, has rapidly increased in recent years, lowering the overall level of MULT. Second, MULT has a direct and significant positive impact on improving energy efficiency. Third, the mechanism analysis indicates that MULT helps enhance energy efficiency by advancing industrial structure optimization and technological progress. Moreover, the heterogeneity analysis demonstrates that the impact of MULT on improving energy efficiency differs significantly in different reform stages and between central and peripheral cities. This study sheds light on the importance of land resource allocation in improving energy efficiency and thus has practical policy implications for promoting low-carbon energy transition in emerging countries.

Digital inclusive finance and consumption-based embodied carbon emissions: A dual perspective of consumption and industry upgrading.

Promoting the development of financial instruments can influence carbon emission reduction in the context of the carbon peaking and carbon neutrality goals. There are currently no theoretical mechanisms to explain whether and how digital inclusive finance, as a new type of financial service, influences residential consumption-based embodied carbon emissions. This study employs the mediation model, moderation model, and moderated mediation model to empirically evaluate the influence mechanism of digital inclusive finance on consumption-based embodied carbon emissions per capita in China from 2011 to 2019. The findings demonstrate that the development of digital inclusive finance increases residents' consumption-based embodied carbon emissions by upgrading consumption level and consumption structure, but that upgrading industrial structure does indeed have a significantly negative moderating effect in implications paths, causing consumption-based embodied carbon emissions to shift from positive to negative. This study, by focusing on the advancement of digital inclusive finance, offers policymakers suggestions for reducing consumption-based embodied carbon emissions from the standpoints of consumption upgrading and industrial structure upgrading, respectively.

The role of digitalization on green economic growth: Does industrial structure optimization and green innovation matter?

The digital economy has demonstrated strong resilience and great potential, under the interwoven influence of the global pandemic and severe environmental concerns across the world. Therefore, there is a need to focus on the value of green economic growth in the digital economy. This paper constructs an evaluation index system and adopts the SEEA (System of Environmental and Economic Accounting) method to measure the digitalization level (Digi) and green economy growth level (GEG) of China. The internal mechanism and linear relationship between digitalization and green economy growth are examined based on the panel data from 2013 to 2019. Moreover, this study explores the spatial spillover effect. The major study findings are as follows: (1) Digitalization and green economy growth represent a steady growth trend, and the former as a whole significantly promotes the latter, with a marginal effect of 1.648. (2) The mechanism analysis indicates the intermediary effects' size of three crucial intermediaries: green technology innovation > advanced industrial structure > the rationalization of industrial structure. (3) Both the "local effect" (0.556; 0.574) and "neighboring effect" (1.382; 1.415) of digitalization on green economy growth are positive under the two weight matrices and display "simultaneous resonance" characteristics based on the spatial perspective. (4) There exists obvious regional spatial heterogeneity and resource endowment heterogeneity. Finally, this study put forward corresponding policy implications, such as construction of new digital infrastructures and guiding green-energy consumption.

How does digital inclusive finance affect the ecological environment? Evidence from Chinese prefecture-level cities.

Digital inclusive finance (DIF) is playing an increasingly prominent role in green development. This study analyses the ecological effects generated by DIF and its mechanism of action from the perspectives of emission reduction (pollution emissions index; ERI) and efficiency gains (green total factor productivity; GTFP). Using panel data from 285 cities in China from 2011 to 2020, we empirically test the effects of DIF on ERI and GTFP. The results reveal a significant dual ecological effect of DIF in terms of ERI and GTFP, but there are differences in the various dimensions of DIF. Influenced by national policies, DIF produced more substantial ecological effects after 2015, which are more pronounced in developed eastern regions. Human capital significantly enhances the ecological effects of DIF, and human capital and industrial structure are critical paths for DIF to reduce ERI and increase GTFP. This study provides policy insights for governments to leverage digital finance tools to advance sustainable development.

The impact of industrial structure adjustment on the spatial industrial linkage of carbon emission: From the perspective of climate change mitigation.

Industrial structure adjustment is an effective way to reduce carbon emissions. When adjusting the industrial structure, changes in the input and output of industrial sectors in one region may cause changes in industrial sectors of other regions, resulting in inter-regional industrial linkages. What is the impact of industrial structure adjustment on the linkages, and how does it impact climate change? The modified gravity model combines the influence and inductive coefficients to build the carbon emission industrial spatial linkage network (ISL) using social network analysis (SNA) in this work with the data of China's 2008-2019 provincial carbon emissions. The impact of industrial structure adjustment on carbon emission industrial spatial linkage network and its effect on climate change mitigation are explored with the help of the STIRPAT model and quality assurance procedure (QAP). The results of this study are as follows: (1) The provincial carbon emissions under industrial spatial linkages show significant network characteristics, the network density increased from 0.1437 in 2008 to 0.323 in 2019. (2) There is a significant spatial spillover effect in the industrial spatial linkage network (2019) centered on Shandong and Jiangsu. The provinces can be divided into 4 blocks, which play different roles in the network. (3) The industrial structure upgrading can significantly promote the carbon emission industrial linkage network and mitigate climate change. (4) The industrial structure rationalization can promote the development of the network and mitigate climate change in the early and late development stages of carbon emissions industrial linkage. In addition, it is necessary for the government to pay more attention to the development level of the carbon emission spatial industrial linkage network when implementing industrial structure adjustment in response to climate change.

Accurate multi-objective prediction of CO2 emission performance indexes and industrial structure optimization using multihead attention-based convolutional neural network.

The establishment of specific targets for the global carbon peaking and neutrality raises urgent requirements for prediction of CO2 emission performance indexes (CEPIs) and industrial structure optimization. However, accurate multi-objective prediction of CEPIs is still a knotty problem. In the present study, multihead attention-based convolutional neural network (MHA-CNN) model was proposed for accurate prediction of 4 CEPIs and further provided the rational suggestions for further industrial structure optimization. The proposed MHA-CNN model introduces deep learning mechanism with efficient resolution strategies for training model overfitting, feature extraction, and self-supervised learning to acquire the adaptability for CEPIs. Multihead attention (MHA) mechanism plays important roles in influence weight interpretation of variables to facilitate the prediction performance of CNN on CEPIs. The MHA-CNN model presented its overwhelmingly superior performance to CNN model and long short-term memory (LSTM) model, two frequently-used models, in multi-objective prediction of CEPIs using 8 influence variables, which highlighted advantages of MHA module in multi-dimensional feature extraction. Additionally, contributions of influence variables to CEPIs based on MHA analyses presented relatively high consistency with the geographical distribution analyses, indicating the excellent capacity of the MHA module in variable weights identification and contribution dissection. Based on the more accurate prediction results by MHA-CNN than those by CNN and LSTM model, the increase in the tertiary industry and the decreases in the first and secondary industries are conducive to improvement of total-factor carbon emission efficiency and further enhancement of effective energy utilization in regions with inefficient carbon emissions. This study provides insights towards the critical roles of the proposed MHA-CNN model in accurate multi-objective prediction of CEPIs and further industrial structure optimization for improvement of total-factor carbon emission efficiency.

The impact of the COVID-19 pandemic on global trade-embodied carbon emissions.

We evaluate the response of global supply chains to carbon emissions through compiling multi-regional input-output (MRIO) models for import and export shocks in 14 countries/territories dominated by the COVID-19 crisis. Instead of traditional production-based inventories, we achieve CO2 emissions inventories based on intermediate inputs and final consumption to analyze the connected environmental impacts. In addition, we adopt the available data up to date to construct inventories of carbon emissions involved in imports and exports from different sectors. The results show that global carbon emissions could be decreased by 6.01% during the COVID-19, while export carbon emissions remained basically unchanged. As a result, imported carbon emissions fell by 5.2%, with the energy products sector most affected by the pandemic. Transport sector witnessed 18.42% carbon emission reduction. The impact of developing countries with a large proportion of resource-based industries is comparatively higher than that of developed countries with the technological advantage. International trade plays a crucial role in the choice of supply chain partners to control carbon emissions. Building a sustainable supply chain and reducing the "trade carbon deficit" between countries/regions requires the coordination of all departments of each country/region to promote the trade of energy-saving products, environmental protection services and environmental services.

How does the ecological compensation mechanism adjust the industrial structure? Evidence from China.

The ecological compensation (EC) mechanism is an innovative institutional arrangement which can effectively realize the coordinated development of social-economic growth and ecological protection. The current research on the evaluation of the implementation effect of EC mechanism mainly focuses on its environmental performance, how the EC mechanism guides the economically underdeveloped areas in the upper reaches of the basin to embark on the road of high-quality economic development, especially the mechanism of how EC triggers the optimization and upgrading of industrial structure, it is a topic worthy of in-depth discussion. This study takes China's first cross-provincial horizontal EC mechanism pilot (Xin'an River Basin EC) as the research object and regards it as a quasi-natural experiment. This paper selects the annual panel data of the 11 cities involved from 2009 to 2019 and builds a DID model to study the mechanism of EC affecting industrial structure adjustment systematically. The results show that the EC mechanism mainly promotes the adjustment of the industrial structure in the pilot area through two paths, this is achieved by triggering the transfer of backward or highly polluting industries and promoting the upgrading of the industrial structure. At the same time, technological innovation plays a part intermediary role in the impact of EC to promote the upgrading of industrial structure. Further analysis found that the larger the funds of compensation input, the higher the assessment intensity, the better the effects are. Finally, this study puts forward relevant policy recommendations to further release the potential of the horizontal EC for the reference of decision-makers.

Modeling economic losses and greenhouse gas emissions reduction during the COVID-19 pandemic: Past, present, and future scenarios for Italy.

Unprecedented nationwide lockdowns were adopted because of the COVID-19 pandemic. Understanding the socioeconomic impact of the past and future restrictions while assessing the resilience of a local economy emerged as a worldwide necessity. To predict the economic and environmental effects of the lockdowns, we propose a methodology based on the well-established input-output inoperability model, using Italy as a case study. By reconstructing the 2020 restrictions, we analyzed the economic losses and greenhouse gas emissions reductions, identifying the most economically impacted sectors because of the restrictions and the sectoral interdependencies and those avoiding most air emissions. We constructed four partial-lockdown scenarios by minimizing the economic losses for increasing restrictions to highlight the model's utility as a tool for policymaking. By revealing the most interconnected and, thus, crucial sectors, the simulated scenarios showcase how the restrictions can be selected to avoid sudden and unpredicted economic damage.

Vertical financial disparity, energy prices and emission reduction: Empirical insights from Pakistan.

The economic and environmental aspects of energy production have become important due to the increasing complexity energy sector and envoirnmental pollution, warranting to test the connection between financial imbalances, energy prices and carbon emission. The study aims to test the impact of vertical fiscal imbalances (VFI) on energy prices and carbon emission trends by considering the dual-perspectives of environmental regulation and industrial structure. The empirical outcomes indicated that vertical fiscal imbalances limited the environmental quality of Pakistan. Furthermore, VFI also caused environmental degradation by affecting industrial structure. VFI inhibits the intensity of environmental regulation, promotes the upgrade of industrial structures, both of which cause additional carbon emissions. The study suggest to energy ministries and energy regulation offices to revisit the machinism of energy prices determination and revised machanisim should provide a user-friendly assessment to understand the actual costs associated with the rising concern of environmental pollution. By this, envoirnmental protection maximization and optimal energy conservation is expacted to increase. Based on empirical findings, the study extends the suggestion that vertical fiscal imbalances should be considered an active indicator by the key policy makers and other stakeholders for energy prices determination and environmental quality upgradation.

Does ecological compensation have a spillover effect on industrial structure upgrading? Evidence from China based on a multi-stage dynamic DID approach.

China's rapid economic development has led to increasingly serious environmental problems, such as the deterioration of its ecology in important river basins. Adjusting the industrial structure through the mechanism of ecological compensation (EC) is a key measure for solving this economic and environmental dilemma. Early research on the impact of ecological compensation mechanisms has mainly focused on evaluating their performance in terms of the ecological environment, with little empirical evidence. Therefore, it is necessary to explore the economic effects of ecological compensation mechanisms in order to achieve sustainable economic and environmental development. Based on panel data from the Xin'an River Basin in China from 2009 to 2018, a multistage dynamic difference-in-differences (DID) model was constructed to systematically study the impact of the ecological compensation mechanism on the upgrading of the industrial structure. The research results show that due to the implementation of the policy, the industrial structure in pilot ecological compensation areas tends to be rational and advanced. The ecological compensation policy has dynamic effects on the upgrading of the industrial structure during the different stages of its implementation. This study is conducive to further enriching the relevant theories and practices underlying the study of ecological compensation mechanisms. At the same time, this paper provides operational suggestions for ecological protection, the adjustment of the industrial structure, and the formulation of relevant macroeconomic policies.