Impact of environmental regulation on green total factor productivity: a new perspective of green technological innovation.

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.

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.

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.

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

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.

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 impact of local government attention on green total factor productivity: An empirical study based on System GMM dynamic panel model

Does green innovation induce green total factor productivity? Novel findings from Chinese city level data

Digital finance provides a premises guarantee for green technology innovation, and effective environmental regulation helps to achieve green and sustainable development. This article selects Chinese urban panel data from 2011 to 2019 to explore the impact mechanism of the influence of digital finance and environmental regulation on the innovation capacity of green science and technology. It is found that extensive financing channels and the strong information-matching ability of digital finance have a significant promoting effect on local green science and technology innovation. Moreover, government environmental regulation not only facilitates the development of green technology innovation locally and in nearby regions, but also strengthens the utility of digital finance in driving green science and technology innovation. Further research found that the influence of digital finance and environmental regulation on the ability of green science and technology innovation has regional heterogeneity, and only digital finance in Central China can promote green science and technology innovation in both local and adjacent areas. Therefore, the government should continue to promote the development of digital finance, optimize environmental regulations by increasing environmental protection subsidies and creating a green innovation environment, and further stimulate willingness to innovate green technologies. At the same time, it is also important to note the coordinated development and governance with neighboring regional governments.

Environmental regulation and green total factor productivity in China: A perspective of Porter’s and Compliance Hypothesis

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

This study employs a staggered Difference-in-Differences (DID) model, based on the scenario of firms being included in China’s green manufacturing lists, to examine the impact of the voluntary environmental regulation on firms’ green and low-carbon technological innovation. Our results reveal that inclusion in the green manufacturing lists significantly accelerates firms’ green and low-carbon technological innovation. Mechanism analyses suggest that this positive effect is primarily driven by enhanced resource acquisition capability and increased environmental attention. Additionally, heterogeneity analyses indicate that the enhancing effect of the green manufacturing lists on firms’ green and low-carbon technological innovation is more pronounced when firms prioritize digital transformation and artificial intelligence, when local governments emphasize environmental protection, and when firms receive more market attention. Further, extensive tests show that firms’ inclusion in these lists also stimulates green and low-carbon technological innovation among other firms in the same industry or city. Lastly, the economic-consequence analysis demonstrates that being lists ultimately leads to improvements in firms’ green total factor productivity. These findings offer valuable insights for policymakers and regulators seeking to promote green transformation, providing empirical evidence of the effectiveness of voluntary environmental regulation in fostering sustainable development.

Green collaborative innovation critically drives green total factor productivity (GTFP), yet its network impact on GTFP remains unsolved. Based on the urban green collaborative innovation (UGCI) networks constructed by 2011–2021 joint application green patent data from 189 cities, this study applies social network analysis to calculate degree and degree centrality to represent cities’ network location. By utilising two-way fixed effects and quantile regression models, we find that cities’ locations within the UGCI network significantly influence GTFP, as evidenced by the network’s continual expansion alongside pronounced increases in green innovation, particularly in eastern, central and parts of northern China. Besides, central cities in UGCI network consistently enhance GTFP, validated through robustness tests. Heterogeneity analysis elucidates how geographic location and COVID-19 affect GTFP. Mediation analysis identifies energy dependency reduction as a critical pathway for GTFP enhancement. These findings advance strategies for optimising green co-innovation and sustainable development.