Does the transformation of resource-dependent cities promote the realization of the carbon-peaking goal? An analysis based on typical resource-dependent city clusters in China

Green total factor productivity (GTFP) is an essential indicator to measure economic and environmental efficiency. Moreover, formulating a reasonable environmental regulation system and promoting green technological innovation is a systematic way to improve GTFP. However, previous related studies lack to investigate the impact of environmental regulation on GTFP from the perspective of green technological innovation. For this purpose, this paper aims to examine the specific impact of environmental regulation on GTFP based on the perspective of green technology innovation, so as to provide some policy insights for the formulation of more effective implementation of environmental regulation, improve green technology innovation level, and achieve a win-win situation for both economic growth and environmental protection. Furthermore, epsilon-based measure (EBM), which includes both radial and non-radial distance functions, is used to measure the GTFP. The spatial autoregressive method is also employed to quantify the impact of environmental regulation on GTFP from the perspective of green technological innovation using panel data of 269 prefecture-level cities in China from 2004 to 2018. The main findings indicate that there is a significant spatial autocorrelation between environmental regulation and GTFP. Environmental regulation has a significant positive effect on GTFP. Environmental regulation in the local regions also significantly contributes to GTFP in neighboring regions. Besides, environmental regulation indirectly promotes GTFP by enhancing green technological innovation level. Regional heterogeneity results show that environmental regulation can not only directly promote GTFP but also indirectly significantly promote GTFP through green technological innovation in the eastern and central regions, but insignificant in the western region. Based on the above findings, we conclude that policymakers should not only develop differentiated environmental regulation standards and steadily improving the intensity and rationality of environmental regulation but also add green innovation funds supply, enhance green innovation factor allocation efficiency, and strengthen R&D talents, funds, and policies to green technology innovation, so as to drive GTFP improvement.

Compared to regions with lighter pollution, the areas heavily affected by pollution in China face more severe environmental problems due to rapid economic growth, which creates a greater urgency for government and corporate environmental requirements. This study innovatively applies mediation and threshold models to explore the potential correlation between green technology innovation, types of environmental regulation, and provincial-level green total factor productivity (GTFP). Additionally, it examines inter-regional differences, determines threshold effects, and introduces regional heterogeneity and mediator variables. The research findings demonstrate that progress in green technology innovation significantly impacts the improvement of provincial-level GTFP. Further mechanism analysis reveals the crucial role of environmental regulation in facilitating sustained enhancement of GTFP through green technology innovation. The promotion of GTFP is more pronounced in eastern and central provinces compared to western regions, and the positive influence of green technology innovation varies significantly among provinces. By investigating the regional differences of polluted areas and introducing mediating variables, this paper explores the environmental regulation mechanism, which has important guiding significance for formulating more effective environmental regulation policies, promoting green technology innovation, and improving GTFP.

Green technological innovation, green finance, and financial development and their role in green total factor productivity: Empirical insights from China

Environmental regulation is a crucial tool for government intervention in the field of green technology innovation. It can boost an enterprise’s competitiveness and encourage green technology innovation, both of which have a major effect on luring foreign investment. This paper first systematically elaborates on the relationship between environmental regulation, foreign direct investment (FDI), and green total factor productivity (GTFP) and then combines panel data from Chinese cities to empirically test these relationships using various methods, such as the mediation effect model, two-stage least squares, and difference-in-differences method. The study found that environmental regulation significantly boosts FDI and GTFP. FDI helps to improve GTFP, and environmental regulation can impact GTFP indirectly through FDI. The way that FDI and environmental regulations affect GTFP demonstrates regional variation. Large cities with high economic growth gain more from environmental regulation. FDI has a stronger promotion effect on GTFP in medium- and small-sized cities than in large-sized cities, and it does not significantly impact GTFP in cities with high levels of economic development or in the eastern region.

Improving green total factor productivity (GTFP) can promote high-quality economic development, while different forms of competition among local governments can affect GTFP. This paper uses panel data from 226 prefecture-level cities in China to measure GTFP using the super efficiency SBM model and GML index. Based on the angle of comprehensive competition, this paper constructs a panel fixed effect model and a panel threshold regression model to analyze the impact of local government economic competition and environmental competition on GTFP, and analyzes the threshold effect of environmental regulation on economic competition and environmental competition on GTFP. Based on the effect of competition transformation, a difference-in-difference model is constructed to analyze the impact of local government competition transformation on GTFP, and to test the mediating effect of reduction of pollution and carbon emissions. The results show that: First of all, the joint effect of local government economic competition and environmental competition has promoted the improvement of GTFP, but there are regional differences, with the promotion effect of southern cities, eastern cities, and first-, second-, and third-tier cities being more obvious. In addition, local government competition taking into account environmental competition can promote the improvement of GTFP. With the increase of environmental regulation intensity, the promotion effect of comprehensive competition increases first and then decreases. Finally, the transformation of local governments from economic competition to environmental competition can promote GTFP by reducing pollutant emissions intensity and carbon emission intensity, and reducing carbon emission intensity is the main path. According to the empirical results, the study suggests that the central government improve the competition mode of local governments, establish a performance evaluation mechanism that reflects green development, and balance the relationship between economic competition and environmental competition. Further we should improve the implementation norms and regulatory standards of institutional environmental regulations, adopt classified guidance and tailored environmental regulation policies, and gradually strengthen the coordinated governance of pollution reduction and carbon reduction.

Environmental pollution and resource waste in Chinese cities have become important obstacles to sustainable economic development, and it is urgent to change the mode of economic development and improve the quality of economic development. In response to this challenge, this study proposes environmental regulation as a solution and empirically tests the impact of environmental regulation on green total factor productivity. The empirical results show that environmental regulation can significantly improve urban green total factor productivity, the public environmental concern and green finance strengthen the positive effect of environmental regulation on urban green total factor productivity. The mechanism test shows that environmental regulation can improve urban green total factor productivity through green technological innovation and industrial structure upgrading. Heterogeneity analysis reveals that, compared to the resource-based cities, the positive effect of environmental regulation on urban green total factor productivity is more significant in the non-resource-based cities with relatively developed traditional finance and high levels of industrial modernisation. Compared to the central and western as well as the northeast regions of China, the positive effect of environmental regulation on urban green total factor productivity is more significant in the eastern region due to capital accumulation and technological constraints. The results of the study remain reliable after a series of endogeneity and robustness tests. These studies provide an important research basis for providing more targeted environmental regulation programmes and better improving green total factor productivity.

Green total factor productivity (GTFP), as an important indicator considering both economic development and environmental protection, has prompted countries around the world to actively explore ways to improve it in the context of the global transition to a green economy. The Low-Carbon City Policy (LCCP) implemented by the Chinese government, along with the National Big Data Comprehensive Pilot Zone Policy (NBDCPZ), which serve as key carriers of green regulation and digital innovation, respectively, play an important role in improving green total factor productivity (GTFP) and achieving high-quality economic development. This study aims to deeply explore whether there is a collaborative enabling effect of the Low-Carbon City Policy (LCCP) and the National Big Data Comprehensive Pilot Zone Policy (NBDCPZ) on green total factor productivity (GTFP) and to reveal the internal mechanism by which they improve GTFP through green technological innovation and industrial agglomeration. Specifically, based on the panel data of 269 prefecture-level cities in China from 2006 to 2022, a “dual-pilot” policy is constructed through LCCP and NBDCPZ, and a multi-period difference-in-differences model (DID) is used to evaluate the collaborative effect of the “dual-pilot” policy on GTFP. The results show that the “dual-pilot” policy has a significant collaborative effect on green total factor productivity (GTFP), and its enabling effect is more obvious than that of the “single-pilot” policy. These conclusions still hold after a series of endogeneity and robustness tests. Mechanism analysis shows that the “dual-pilot” policy can also improve green total factor productivity (GTFP) through green technological innovation and industrial agglomeration. Heterogeneity analysis reveals that the collaborative enabling effect of the “dual-pilot” policy is influenced by geographical location and population density. Specifically, the “dual-pilot” policy significantly promotes green total factor productivity (GTFP) in coastal cities and those with high population density. These research results provide a scientific basis for formulating green development policies in China and other countries, as well as a direction for subsequent research on the collaborative enabling effect of multiple policies.

Green technology innovation shoulders the dual task of green development and innovation leading. It is an inevitable choice for China to achieve the carbon peak and neutrality goal and promote high-quality economic development by effectively stimulating green innovation vitality and improving green innovation capacity. In this context, from the perspective of institutional quality, this study takes the anti-corruption campaign launched since the 18th National Congress of the Chinese Communist Party as a quasi-natural experiment, constructs an intensity difference-in-differences (DID) model, and tests the impact effect and mechanism of the anti-corruption campaign on regional green technology innovation. It is found that the anti-corruption campaign has significantly improved the level of regional green technology innovation. This conclusion still holds after a series of robustness tests such as parallel trend test, placebo test, and instrumental variable estimation. The results of mechanism analysis show that the anti-corruption campaign is helpful to increase foreign direct investment and change the government's fiscal expenditure bias, thus promoting the improvement of green technology innovation level. Heterogeneity analysis shows that the promotion effect of anti-corruption campaign on green technology innovation is more significant in eastern and southern regions. At the same time, the lower the degree of government intervention, the greater the protection of intellectual property rights, and the stronger the environmental governance, the greater the promoting effect of the anti-corruption campaign on green technology innovation. Further research shows that the improvement of the level of green technology innovation is conducive to the realization of the "dual control" goal of total and intensity of carbon emissions. This study proves the positive externality of anti-corruption campaign from the perspective of green technology innovation and provides new empirical evidence for the advantageous theory of anti-corruption.

This paper employs the SBM-DDF method to measure the index of green total-factor productivity (GTFP), based on the panel data of 279 prefecture-level cities in China from 2007 to 2019, and constructs a spatial Durbin model (SDM) and a threshold effect to empirically test the effects of dual environmental-regulations and green technological innovation on GTFP. The results are as follows: (1) the SDM supports a nonlinear contribution of dual environmental-regulations spillover to GTFP. The relationship between formal environmental-regulation and GTFP is an inverted U-shape, while a U-shaped nonlinear relationship is found between informal environmental regulation and GTFP. (2) Green technology innovation has a significant negative moderating effect on the process of dual environmental-regulations affecting GTFP in local regions, but a positive moderating effect on informal environmental regulation in neighboring regions. (3) There is a significant green technology innovation threshold effect of dual environmental-regulations affecting GTFP. Specifically, the promotion effect of dual environmental-regulations on GFFP gradually increases as the level of green technology innovation increases.

Amidst resource loss and environmental protection constraints, achieving green development necessitates enhancing green total factor productivity (GTFP) as a means of promoting rational and efficient resource allocation, thereby balancing economic growth and environmental preservation. Meanwhile, literature on the subject matter of GTFP from a sustainability viewpoint is minimal. As a result, this study employs the panel dataset from 30 provinces of China spanning the period 2005 to 2020 and utilizes the method of moments quantile regression (MMQR) developed by Machado and Santos Silva (2019) to analyze the heterogeneous role of green innovation, environmental regulations, and fiscal expenditure on GTFP. Moreover, the controlling variable for this study includes renewable energy and economic growth. Furthermore, this study investigates the heterogeneous combined impact of green innovation and fiscal expenditure (GTE*FSE) on GTFP. The findings of the MMQR reveal that green innovation has a positive impact on GTFP, while fiscal expenditure, environmental regulations, and renewable energy consumption have a negative impact. GTE*FSE has a positive and significant effect on GTFP, indicating that FSE can reinforce and increase the positive impact of GTE on GTFP in the long run. The study also reveals that economic growth has a mixed effect on GTFP, depending on the quantiles. Furthermore, environmental regulation has a significant and negative impact on GTFP, contradicting the Porter hypothesis. Likewise, the robustness of the findings is confirmed by the results of the fully modified OLS (FMOLS) and dynamic OLS (DOLS) estimations, which indicate a similar impact of the determinants on GTFP as observed in the MMQR analysis. This reinforces the validity of the findings and suggests that the observed relationships are robust to different estimation techniques. Furthermore, the findings of the Dumitrescu and Hurlin (D-H) panel causality test reveal significant bidirectional causality between renewable energy consumption and GTFP and fiscal expenditure and GTFP. Policy-makers need to channel a large chuck of their fiscal spending into green innovation so as to boost sustainability.

The enhancement of green total factor productivity of resource-based enterprises has a crucial impact on building an environmentally friendly society, promoting a circular economy, and guaranteeing the security of national resource supplies. This study takes the green transformation of resource-based enterprises as the main line, and then constructs the research framework. A random forest algorithm is used to discover the effects of different characteristics of green transformation on green total factor productivity. Further, using panel data-based qualitative comparative analysis and necessary condition analysis, it clarifies what kind of green transformation group path promotes green total factor productivity from the group perspective. This study shows that (1) environmental regulations, green cognition, and green investment are important factors in condition configuration and there exists a complex nonlinear relationship among them, indicating the need for further research from a configurational perspective; (2) green technological innovation, green investment, green development strategies, green governance level, green cognition, environmental subsidies, and environmental regulation are not necessary conditions for a high level of green total factor productivity; (3) there are three grouping paths for green total factor productivity improvement in resource-based enterprises; and (4) there are time and case differences in the explanatory strength of the three grouping paths. Finally, based on the results of this study, and in conjunction with China’s green transformation practice, countermeasures are proposed from both the enterprise and government perspectives.

Carbon emissions have become a global challenge that threatens human development. Governments have taken various measures to reduce carbon emissions, and green finance is an important and innovative way to realize carbon emission reductions. This paper uses data on a prefecture-level city in China to explore the impact of green finance on carbon emission intensity from both theoretical and empirical perspectives, and analyzes the mechanisms by which green finance affects carbon emission intensity. On this basis, this paper further analyzes the impact of green finance on carbon emission efficiency. In addition, this paper introduces variables related to the digital economy to perform a comprehensive examination of the moderating effect of digital economy development on the relationship between green finance and both carbon emission intensity and efficiency. The results indicate that green finance reduces carbon emission intensity and that green innovation, green total factor productivity and the transformation and upgrading of industry are important mediating mechanisms. Meanwhile, analysis shows that green finance improves carbon emission efficiency. This paper also finds that the digital economy significantly enhances the role of green finance in reducing carbon emission intensity and promoting carbon emission efficiency, and makes a positive contribution to promoting carbon emission reduction. The findings will contribute to strengthening the government’s capacity for environmental protection, developing green finance, and reducing carbon emissions.

Effect of green technology innovation on green total factor productivity in China: Evidence from spatial durbin model analysis

Confronted with challenges such as escalating demand, expanding energy consumption, and emissions, China’s manufacturing sector stands at a pivotal juncture on its path towards sustainable development. Against the backdrop of a new wave of technological revolution and industrial transformation, exploring how the digital economy can foster growth in green total factor productivity (GTFP), particularly amidst technological diversification, holds significant importance for realizing sustainable development objectives. This study employs the system generalized method of moments (System GMM), encompassing 30 provinces in China, to delve deeply into the notable and dynamic correlation between the development index of the digital economy and GTFP. The findings reveal that the advancement of the digital economy significantly influences GTFP, underscoring its direct and enduring impact on green productivity. Key mechanisms through which the digital economy promotes green productivity are identified, including resource optimization, green technological innovation, data-driven decision making, and the transformation of environmentally sustainable behaviors. By bridging gaps in existing literature, this study integrates economic and environmental perspectives, emphasizing the necessity for formulating digital innovation policies aligned with environmental objectives. It provides richer insights into the role of the digital economy in enhancing GTFP, accentuating the potential of digital technologies in driving green transformation. With its holistic approach, this study combines economic efficiency with environmental sustainability, offering crucial guidance for policymakers and industry stakeholders in crafting sustainable development strategies.

Do renewable energy, environmental regulations and green innovation matter for China's zero carbon transition: Evidence from green total factor productivity