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This article explores the impact mechanism of different types of environmental regulations on corporate green technology innovation (GTI). The research focuses on analyzing three types of environmental regulations: command based environmental regulation (ER1), market-oriented environmental regulation (ER2), and voluntary environmental regulation (ER3), and how they affect corporate GTI. This study selected enterprise GTI as the dependent variable and measured it by the number of applications for green invention patents and green utility model patents. The independent variables are the three types of environmental regulations mentioned above. According to data from Chinese A-share listed companies. Using benchmark regression models to analyze the impact of different environmental regulations on GTI, and constructing a moderating effect model to study the role of corporate R&D investment and government support in the process of environmental regulations affecting GTI. The results indicate that (1) ER1, ER2, and ER3 can all promote enterprise GTI, and the three environmental regulatory methods have a better synergistic effect. (2) R&D investment has a positive correlation with the relationship between ER2 and GTI, and a negative correlation with ER 3 and ER 1. (3) There are differences in the GTI performance of enterprises in different regions, ownership nature, factor density, and industry types under the influence of environmental regulations. (4) The impact of environmental regulatory policies on corporate GTI is mainly short-term. This study provides a new perspective on how environmental regulations affect corporate GTI, especially in the context of developing countries like China. The research findings emphasize the role of different types of environmental regulations in incentivizing corporate GTI, while also pointing out factors that governments need to consider when formulating environmental policies, such as regional differences and corporate characteristics, which are of great significance for promoting green development of enterprises and achieving broader sustainable development goals. [ABSTRACT FROM AUTHOR]

Based on the two-stage innovation value chain model, incorporating environmental regulation policies and three-waste emissions into the research framework, constructing a green technology innovation efficiency evaluation index system from the perspectives of green inputs and outputs, and utilizing the super-efficiency SBM model and the Malmquist-Luenberger index model, assessing the effectiveness of green technological innovation in two aspects, namely, static, and dynamic, respectively. The results show that: the average value of green technical innovation efficiency of China's hightech industries is 0.5277, with significant differences between provinces, but the overall is constantly improving, showing an upward trend; the green technological innovation efficiency decreases from east to west, and the differences among the three major regions are not only embodied in spatial patterns, but also in the growth rate; during the period of investigation, the inefficient provinces are gradually decreasing, and the level of green technological innovation of China is constantly getting better; China's The average value of ML index of green technical innovation efficiency of high-tech industries in China is greater than 1, and the overall development trend is better; the increase of ML index in the eastern and central regions mainly relies on the positive influence of technological efficiency, while the decrease of ML index in the western part is affected by the recession of technological progress and technological efficiency, and the efficiency of technology research and development stage is generally higher than that of scientific and technical achievements transformation stage, and low efficiency of achievements transformation stage is mainly affected by the inhibiting effect of technological progress - inhibitory effect of technological advancement. [ABSTRACT FROM AUTHOR]

Green energy efficiency (GEE) is pivotal for sustainable economic growth, particularly in the context of China's ambitious environmental goals. This study assesses the impact of Green Financial Reform and Innovation Pilot Zones on GEE from 2005 to 2020, using the SBM-GML method and a Double Difference Model (DID). Findings indicate a significant improvement in GEE within these zones, driven by advancements in green innovation and environmental regulation. At the micro level, firms in pilot zones show enhanced Environmental, Social, and Governance (ESG) performance and experience fewer financial constraints. The effectiveness of green finance policies is more pronounced in resource-rich and financially efficient regions, suggesting that these initiatives can significantly contribute to sustainable development. Based on empirical evidence, we recommend expanding pilot zones, promoting green technological innovation, and developing tailored green finance policies to address regional ecological sensitivities. [ABSTRACT FROM AUTHOR]

The escalating demand for resources in urban and rural construction development raises the crucial question of achieving green development within limited resource constraints. This study delves into the interplay between environmental policy and green development in urban and rural construction. Utilizing the spatial Durbin model for analysis, findings reveal that investment-oriented environmental regulation significantly impacts green development and positive spillover effects in neighboring regions when considering spatial weight matrices. In contrast, cost-based environmental regulations positively affect green development when spatial interactions are disregarded. However, they exhibit negative effects at the spatial level, potentially leading to a "pollution relocation" phenomenon. Although the influence of R& D subsidy-based environmental regulations on green development is not significant, their impact becomes notable upon considering spatial interactions, potentially generating positive effects across regions through mechanisms such as technology diffusion and knowledge transfer. Furthermore, from an endogeneity perspective, the impact of environmental regulatory tools on green development exhibits a time lag effect. Moreover, investment-type regulation in the eastern regions significantly fosters green development, whereas cost-based regulation shows a suppressive effect; investment-type regulation in central regions has a positive spillover on neighboring areas; and R&D subsidies in western regions negatively impact local green development. Moreover, the quality of governmental institutions, market integration, and technological innovation are key factors influencing green development in China's urban and rural construction. This study reveals the direct and indirect effects of various environmental policy tools on green development in urban and rural areas. It emphasizes the importance of considering spatial interactions in implementing environmental policies, providing a theoretical foundation and practical guidance for optimizing environmental policies. [ABSTRACT FROM AUTHOR]

Rapid developments in environmental infrastructure have contributed to significant improvements in green total factor productivity, but further investigation is required to provide a detailed assessment to understand the policy mechanisms involved. This paper analyzes environmental progress in China through MMQR, CCEMG, and AMG as empirical strategies for 30 provinces in China. Our empirical results reveal that energy optimization through renewable energy is the most effective channel to improve green total factor productivity, though it is not the only available option. Since environmental regulations, infrastructure development, and green technology innovation also directly impact energy efficiency, adopting these within policy channels will positively impact environmental sustainability. Our empirical approach helps suggest novel environmental policy suggestions. In particular, policymakers must introduce structural changes within energy developments to foster renewable energy. Furthermore, China must increase environmental spending to upgrade its energy infrastructure further and solve ecological issues. These insights offer valuable policy guidance for decision-makers in China and globally, aiming to foster economic and environmental sustainability and achieve zero-carbon transition goals. • The current study analyses the role of green factor productivity in zero carbon transition. • We use 30 chinese provincial datasets from 2005 to 2020. • Energy transition is the most effective channel to improve green total factor productivity. [ABSTRACT FROM AUTHOR]

Green innovation (GI) is increasingly recognised as an effective strategy for tackling climate change, mitigating environmental issues, and promoting sustainable development. Using panel data of the Chinese listed firms from 2007 to 2019, this study adopts the difference-in-differences approach to assess the impact of the green finance policy (GFP) initiated by the Chinese government in 2012 on the green innovation performance of firms. The findings reveal that the GFP significantly boosts the green innovation performance of heavily polluting enterprises (HPEs). Notably, this effect is more pronounced in state-owned enterprises and firms with high dependence on external finance. Compared with penalty-based regulations, incentive-based and voluntary environmental regulations demonstrate more significant moderating effects on the relationship between the GFP and green innovation performance for HPEs. We also identify improved efficiency in the usage of green investments as a potential mechanism through which the GFP enhances the green innovation performance of HPEs. Further comparative analysis shows that green enterprises can achieve simultaneous improvement in both the quality and quantity of green innovation, whereas HPEs predominantly exhibit enhancements in innovation quantity. To maximise the GFP's positive effects, it is recommended to facilitate more targeted bank lending towards HPEs to support their structural transformation. Additionally, the coordinated deployment of diverse environmental policy instruments is advised to exploit their synergistic effects. • This paper confirms the positive relationship between Green Finance Policy (GFP) and the green innovation. • We develop a novel machine learning approach to enhance the accuracy of variable measurements. • Firms with different ownership structure and external finance reliance are impacted differently by the GFP. • Both incentive-based and voluntary environmental regulations have positive moderation effects. • GFP can improve the green innovation by enhancing the green investment efficiency. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of China's environmental regulations, with a focus on the green credit policy, on green innovation in pursuit of the "carbon peak and carbon neutrality" goal. Given the implementation of the 2012 Green Credit Guidelines, this paper employs the Difference-in-Difference Method (DID) and conducts a quasi-natural experiment to empirically examine the interactions among the central government, local governments, and high-pollution and high-emission enterprises by exploring the impact of green credit policies on green innovation of these enterprises. Relying on 4503 samples of 237 high-pollution and high-emission enterprises listed in the main board in China from 2003 to 2021, this study reveals that the green credit policy can improve green innovation of these enterprises. Specifically, this study explores the detailed mechanism through which the green credit policy enables these enterprises to increase their market concentration and then the monopoly profits, which in turn promotes their green innovative productivity. In addition, this paper also reveals how local governments' political and financial incentives may serve as positive and negative moderating factors, respectively, within the impact mechanism. This study has valuable implications for how to effectively formulate and implement environmental regulations by balancing the interests of the central government, local governments and enterprises. [ABSTRACT FROM AUTHOR]