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Improving the logistics industry's green total factor productivity (LGTFP) is a key source of power to achieve its high-quality development (HQD) in China. Technological innovation (TI) and environmental regulation (ER) policies are vital factors that affect the improvement of LGTFP. Although the impact of ERs or TI on LGTFP has been extensively researched, few studies have examined their combined effect. This study utilizes panel data from 30 Chinese provinces during 2006-2020 to estimate LGTFP using the Epsilon-based measure and global Malmquist-Luenberger index. Moreover, this study employs a dynamic spatial Durbin model to explore the influence of TI on LGTFP and its spatial spillovers, as well as the modulatory effect of ER in the relations between TI and LGTFP. The results show that (1) China's LGTFP displays positive spatial spillovers and is influenced by the preceding period's level. (2) In the short term, an improvement in TI levels had a positive effect on local LGTFP, but negative spillovers on neighboring districts. Nevertheless, in the long run, an improvement in TI levels had a notably negative influence on local LGTFP but positive spillovers on adjacent regions. (3) ER had an "inverted U-shaped" modulatory roles with spatial spillovers on the relations between TI and LGTFP in the long-term. These discoveries offer valuable insights into the coordinated development of TI systems and ER policies, enabling the formation of a policy system that aligns with the logistics industry's HQD in China. [ABSTRACT FROM AUTHOR]

Green economy is the core content of the high-quality economic development, and the digital economy is the new driving force to accelerate the realization of high-quality economic development. In this regard, this paper selects 248 resource-based cities in China from 2011 to 2019 as the research objects and uses the fixed effect model and mediation effect model to test the relationship between digital economy and regional green total factor productivity. We get the following conclusions: First, there is the nonlinear relationship between digital economy and regional green total factor productivity, and this relationship shows the inverted U-shape. Secondly, digital economy can influence regional green total factor productivity through the path transmission mechanism of regional technological innovation, industrial structure, and environmental regulation. Finally, the effect of digital economy on regional green total factor productivity is heterogeneous, especially in the eastern region and cities with high human capital level. Based on the digital economy, the findings of this paper provide theoretical basis and reference suggestions for promoting the green development of regional economy. The government should attach importance to regional green development, actively guide the digital economy to promote green development, accelerate the development of the digital economy, and achieve high-quality economic development finally. [ABSTRACT FROM AUTHOR]

As an ecological barrier to ensure the high-quality development of China's economy, the Yangtze River Economic Belt has attracted more and more attention from academic circles on how to promote the green development of the Yangtze River Economic Belt. This paper uses the SBM directional distance function and the Malmquist–Luenberger index to measure the green total factor productivity of 110 cities in the Yangtze River Economic Belt from 2006 to 2018, and then based on the panel threshold model to empirically explore the intensity of environmental regulations that induce trade openness and promote green total factor productivity. Studies have shown that: Firstly, trade openness has significantly inhibited the increase in green total factor productivity, but environmental regulations can play a positive regulatory role, that is increasing the intensity of environmental regulation can alleviate the adverse effects of trade openness, and it is mainly to improve the adverse effects by promoting the progress of green technology. Secondly, the results of the panel threshold model show that environmental regulations have a nonlinear regulatory effect on trade openness and green total factor productivity. When the intensity of environmental regulations crosses the second threshold, trade openness has a significant positive effect on the impact of green total factor productivity. Finally, the heterogeneity results show that in order to reverse the adverse impact of trade openness on green total factor productivity, the upper, middle and lower reaches of the Yangtze River Economic Belt should formulate relatively strict environmental regulations. [ABSTRACT FROM AUTHOR]

In the context of achieving the 'dual carbon' goals of peaking carbon emissions and carbon neutrality, meeting emission reduction targets while ensuring stable economic growth is the economic development model China is seeking now. Therefore, exploring the mechanism of environmental regulation in China's economic growth, especially on technological progress, will help to analyze the mechanism of environmental policy on sustainable economic development. In this article, we used the SBM model to measure the green total factor productivity in the subdivided industries of the manufacturing industry in China from 2003 to 2018, and decomposed technological progress to examine the factor preference characteristics of biased technological progress, and finally used a panel regression model to empirically test the mechanism of environmental regulations on green total factor productivity and technological progress and their decomposition terms. The results showed that: 1 Green total factor productivity in China's manufacturing industry was generally increasing year by year, and technological progress was the main source of its growth. Environmental regulation showed an inverted U shaped relationship with green total factor productivity and technological progress, and the intensity of regulation was currently on the left side of the inflection point, and the increase in environmental regulation intensity helped to promote the growth of green total factor productivity and technological progress in China's manufacturing industry. 2 From the internal influence mechanism of technological progress, the results of biased technological progress factor preferences showed that the characteristics of input-biased technological progress factor preferences changed with the stage of economic development, and output-biased technological progress was more biased toward CO2 output, but it showed an improving trend year by year. The effects of environmental regulations on input-biased technological progress, output-biased technological progress, and scale technological progress were all significant, and the increase in the intensity of environmental regulations helped to enhance input-biased technological progress and reduce output-biased technological progress so as to save the input of production factors and reduce CO2 output. 3 The degree of opening to the outside world, capital intensity, and government subsidies all had positive effects on green total factor productivity and technological progress, and strengthening these factors could help to improve the economic development of the manufacturing industry. The study found that current technological progress had a certain 'carbon lock-in' effect on carbon emissions, and environmental regulations were not effective in reducing coal use. By measuring the current situation of China's manufacturing economy and the effect of environmental regulations, this study provides theoretical support for promoting China's green and high-quality economic development. [ABSTRACT FROM AUTHOR]

The question of whether environmental regulation fosters technological innovation and green development, as a nuanced extension of the Porter hypothesis, constitutes a focal point in contemporary research. Despite this attention, the literature often omits a multifaceted evaluation framework for green development and fails to consider multiaspectual environmental regulation and technological innovation. This study develops a comprehensive model of green total factor productivity (GTFP), situating the Chinese economy within an economy–environment–health nexus. The extended Crépon–Dugeut–Mairesse model is employed to revisit the "strong", "weak", and "narrow" Porter hypotheses. The analysis reveals that formal environmental regulation exerts a crowding-out effect on research and development (R&D), whereas informal environmental regulation exhibits a facilitating effect, corroborating the narrow version of the Porter hypothesis. Both categories of regulation contribute to substantial innovation. Following the incorporation of R&D factors, heterogeneity in the "weak" Porter hypothesis emerges in the Chinese context, contingent upon specific types of environmental regulation and technological innovation. Environmental regulation positively influences GTFP, affirming the "strong" Porter hypothesis, primarily through the vector of technical progress change. A developmental trajectory to enhance GTFP is thus articulated: judicious environmental regulation leads to R&D, which in turn fosters innovation quality, subsequently affecting the technical progress change index and ultimately GTFP. Correspondingly, policy recommendations are delineated across three dimensions: judicious environmental regulation, targeted innovation support, and regional coordination. [Display omitted] • A GTFP evaluation framework within the economy–environment–health is constructed. • The "strong", "weak" and "narrow" Porter hypotheses are retested by the CDM model. • Multidimensional regulation, innovation, and productivity are investigated. • There are innovation-driven interactions and regional heterogeneity. • Reasonable regulation–R&D–innovation quality–GTC–GTFP is a key development path. [ABSTRACT FROM AUTHOR]

Environmental performance-based credit mechanisms are among the tools policymakers can use to influence the polluting firms' behavior. In this study, we use China's blacklisting system for environmental fraud as a quasi-natural experiment to analyze the pollution-reducing effect of environmental credit constraints (ECCs). We operationalize our approach using a sample of 287 Chinese cities for the period 2008–2018 and find that ECCs help reduce emission intensity—a result that is both statistically significant and robust. Furthermore, our analysis suggests that ECCs can motivate producers to increase investment in technological innovation and optimize their factor allocation structure to improve green total factor productivity, thereby helping reduce their environmental impact. We demonstrate that the ECC-based schemes could be particularly effective in helping reduce pollution in regions with high enterprise credit dependence and relatively heavy presence of the manufacturing industry. In addition, these pollution-reducing effects are significant in regions with relatively strict environmental regulation. Hence, we argue that environmental credit systems could help policymakers provide polluting companies with additional incentives to voluntarily cut their emission levels and thus offer opportunities for diversifying the strategies policymakers can use to mitigate adverse environmental impacts. [ABSTRACT FROM AUTHOR]

Green productivity plays an important role in China's industrial economy. By adopting the technique of Malmquist Luenberger index based on the non-radial directional distance function (NDDF), this paper evaluates the green total factor productivity (GTFP) of the 36 sub-industries in China's industrial field from 2005 to 2015. On this basis, this article further investigates the effects as well as impact mechanisms of environmental regulation (ER) on the industrial GTFP. The empirical analysis reveals that there is a significant positive correlation between ER and industrial green growth, with a one-standard-deviation rise in ER leading to an average 0.0683% GTFP increase. Through the decomposition procedure of Chinese industrial GTFP, we further prove that technological progress, compared to technical efficiency improvement, plays a more essential role in driving industrial green growth. Results of the intermediate effects model indicate that ER can promote the industrial GTFP through industrial structure upgrading. We also find that the effect of ER varies with the levels of per capita output, energy efficiency, and technology intensity. This study sheds new light on the effects of ER on industrial GTFP from perspectives of heterogeneous effects and impact mechanisms analysis. • Industrial GTFP was measured based on the NDDF along with GL productivity index. • Moderate environmental regulation contributes to industrial GTFP growth. • Industrial structure upgrading is one of the important influence mechanism. • Rigorous environmental regulation could harm less-developed industries. [ABSTRACT FROM AUTHOR]

• Green technology progress promotes the total factor productivity of enterprises. • Environmental regulation promotes the green technology progress of enterprises. • The improvement of unit labor productivity is an influencing mechanism. • The push of external pressure is an influencing mechanism. The implementation of Industry 4.0 has had an important impact on the value creation of the manufacturing industry, but there are few studies on its driving mechanisms and effect on total factor productivity. In this study, green technology progress is selected as an important representation of Industry 4.0, and samples of China's A-share resource-based enterprises from 2004 to 2018 are used to examine the relationship between environmental regulation, green technology progress, and total factor productivity to explore the role of social, environmental, and technological factors in manufacturing development. The findings show that green technology progress significantly promotes the total factor productivity of enterprises through the improvement of unit labor productivity and that environmental regulation "forces" the green technology progress of enterprises through external pressure. These conclusions remain valid after replacing the explained variables and measuring methods. The results of heterogeneity analysis show that when an enterprise has strong financial and human resource bases, the "forcing" effect of environmental regulation on green technology progress is more significant. [ABSTRACT FROM AUTHOR]