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Environmental regulation policy and cleaner production technology innovation are the key links to achieve sustainable economic development. This paper tests the impact of Two Control Zone (TCZ) environmental regulation policy on cleaner production technology innovation and explains the heterogeneity effect between them from the perspective of regional pollution intensity and R&D investment scale.

This paper takes TCZ policy as an environmental regulation policy and collects the patent data related to coal desulfurization cleaner production technology innovation in prefecture-level cities from 1994 to 2002 in China. This paper also tests the relationship between TCZ environmental regulation policy and cleaner production technology innovation based on difference in difference (DID) model. Take regional R&D investment scale and pollution intensity as category variables and analyze the heterogeneity effect of TCZ environmental regulation policy on cleaner production technology innovation based on difference-in-difference-in-difference (DDD) model.

TCZ environmental regulation policy effectively promotes China's cleaner production technology innovation, but it is more conducive to cleaner production technology innovation in heavy pollution areas. With the increasing of R&D investment scale, the positive effect of TCZ environmental regulation policy on cleaner production technology innovation is stronger.

On the basis of this study, the authors should further explore the regulatory factors of the relationship between TCZ environmental regulation policy and cleaner production technology innovation and further expand the research object, so as to make the research conclusions more practical and instructive.

This paper tests the impact of TCZ environmental regulation policy on cleaner production technology innovation based on the prefecture city level data and DID model, and it handles the endogenous problem caused by the missing variables and provides the accurate conclusions. Moreover, this paper examines the heterogeneity effect of TCZ environmental regulation policy on cleaner production innovation from regional R&D investment scale and pollution intensity two hands and expands the existing theoretical research.

This paper aims to review how current policy instruments drive (or not) environmental innovation and, by doing so, to reinvestigate the relationship between innovation and regulation.

A comprehensive literature review on innovation and environmental regulation created a theoretical foundation of the paper. Using the grounded theory, a model was developed and evaluated using interviews. This is a timely topic as the new shape of recent environmental regulation appears to be fairly strict. A new model is presented to encapsulate highly dynamic interaction of environmental innovation and regulation to provide results that reflect on the present innovation behaviour and its implications.

The model highlights various diffusion pathways that are triggered by the main three drivers of innovation namely government (regulation), market (competition and cost) and technology which has the possibility of an autonomous diffusion.

The empirical data are limited to 13 qualitative experts' interviews within industry, consultancies and governmental departments.

The suggested model is particularly useful for policy makers to better understand the innovation dynamics and its diffusion pathways to design smarter regulations that incentivise rather than force organisations to comply with regulation.

The paper shows how regulation drives (or not) innovation and how various diffusion pathways can be used by external stakeholders to direct and promote innovation.

The purpose of this paper is to test the relationship between environmental regulations and green total factor productivity (GTFP) of China's logistics industry. The high-factor input, high-energy consumption, and high-pollution emissions model of the logistics industry developed within China faces challenges from severe resource and environmental constraints. It is generally believed that environmental regulations effectively restrain pollution emissions and help protect the environment.

The authors employ the undesirable slack-based Malmquist Luenberger model to calculate the GTFP across the provincial logistics industry and use the mediation effect model and threshold effect model to explore the effects and mechanics of environmental transmission regulations on the GTFP.

The main results show significant regional differences in the GTFP of logistics industry across China. In the transmission path of the impact of environmental regulations on the GTFP, regional innovation capabilities have mediation effects. Regional innovation capacities have a masking effect on the transmission path of environmental regulations on accumulated technical efficiency changes (AEC) and accumulated technical changes (ATC). The threshold effect test results show a dual-threshold effect between environmental regulations and the GTFP, with environmental regulations as threshold variable. Furthermore, the impact of regional innovation capability on the GTFP has a dual-threshold effect, with environmental regulation as threshold variable.

First, it is advisable to plan the environmental regulation policy system thoroughly and add supporting measures to ensure the efficiency and smooth implementation of the nation's environmental policies. Second, it is important to further understand the critical role of innovation capability in improving the GTFP. Third, there is an urgent need to standardize the operating behavior and market order of the leading players in the logistics market and to improve the operational efficiency of logistics enterprises.

So far, a systematical study researched on effect of environmental regulation on the GTFP in logistics industry was not published. This study can provide experience for the high-quality development of the logistics industry.

The purpose of this study is to analyze the effect of foreign direct investment (FDI) on pollution emissions and how environmental regulation affects this relationship.

In the empirical research, the authors selected panel data for 30 provinces in China from 2005 to 2019 as samples. First, the authors used the instrumental variable method to verify the existence of the above hypotheses in China. Then, the authors analyzed the moderating effect of different types of environmental regulations on the environmental effects of FDI. Next, in further discussion, the authors analyzed the difference between the environmental effect and the moderating effect in different time periods and regions, respectively. Finally, the authors discussed whether the different intensities of environmental regulations lead to the transfer effect of FDI in choosing investment destinations.

The result shows that FDI can help reduce pollution emissions and create a “pollution halo” effect, which is enhanced by command-and-control regulation but suppressed by market-based incentives. The heterogeneity analysis reveals that the 18th National Congress of the Communist Party has weakened the pollution halo effect of FDI, while the environmental effect of FDI in the eastern region is not significant, but in the middle and western regions, there is a significant pollution halo effect and a positive moderating effect of environmental regulations. Finally, further analysis reveals that FDI has a transfer effect under command-and-control environmental regulations.

First, the main purpose of this paper is to study the relationship between FDI and pollution emissions from the perspective of heterogeneous environmental regulation. Therefore, there is no detailed discussion on their effect mechanism of them. Second, limited by data, the authors adopt the single index to measure the stringency index of command-and-control and market-based incentive environmental regulations in China. The single index may not be able to fully reflect the intensity of regional environmental regulation, so the construction of a composite indicator is necessary. These shortcomings are the focus of the authors' future research.

Under the guidance of high-quality development, the conclusions above can provide reference for adjusting FDI policies and improving environmental regulation policies.

The innovations in this paper can be summarized as the following four dimensions: First, the authors use the instrumental variable (IV) method to address endogeneity in the relationship between FDI and pollution emission, which can further ensure the robustness of the research results and increases the credibility of the paper. Second, the authors distinguish between two types of environmental regulations to investigate their moderating effect on the environmental impact of FDI. Third, the authors consider the temporal and spatial heterogeneity of both the environmental effects of FDI and the moderating effect of regulation. Last, the authors analyze the spatial spillover of environmental regulation through the study of the transfer effect.

The purpose of this paper is to analyze the impact of the off-office audit of natural resource assets on the prevention and control of water pollution against a background of big data using a differences-in-differences model.

This study constructs a differences-in-differences model to evaluate the policy effects of off-office audit based on panel data from 11 cities in Anhui Province, China, from 2011 to 2017, and analyzes the dynamic effect of the audit and intermediary effect of industrial structure.

The implementation of the audit system can effectively reduce water pollution. Dynamic effect analysis showed that the audit policy can not only improve the quality of water resources but can also have a cumulative effect over time. That is, the prevention and control effect on water pollution is getting stronger and stronger. The results of the robustness test verified the effectiveness of water pollution prevention and control. However, the results of the influence mechanism analysis showed that the mediating effect of the industrial structure was not obvious in the short term.

These findings shed light on the effect of the off-office audit of natural resource assets on the prevention and control of water pollution, and provide a theoretical basis for the formulation of relevant environmental policies. Furthermore, these findings show that the implementation of the audit system can effectively reduce water pollution, which has practical significance for the sustainable development of China's economy against the background of big data.

This study quantitatively analyzes the policy effect of off-office auditing from the perspective of water resources based on a big data background, which differs from the existing research that mainly focuses on basic theoretical analysis.

This paper aims to identify the impact of the new ambient air quality standards (AAQS) on firm innovation.

Taking listed companies from 2009 to 2014 as the research object, the authors focus on the quasinatural experiment of the pilot policy of the new AAQS and apply the time-varying difference-in-differences (DID) method to conduct the empirical test.

The authors find that the new AAQS has a negative effect on firm innovation, and this negative impact may be caused by the increased environmental expenditures following the implementation of the new AAQS. Furthermore, the authors find that firm profitability and state ownership weaken this negative effect, but the effect of the degree of industrial pollution is statistically insignificant.

The study is an initial effort to explore the causal effect of the new AAQS on firm innovation. This study enriches the literature on the impact of environmental regulations on firm innovation and provides some reference value for the formulation of environmental regulation policies in developing countries.

The issue of environmental regulation and productivity has received increasing attention among academics, but little research has focused on Chinese firms despite the serious state of pollution in China. This study aimed to fill that gap. Analyzing a sample of firms from 12 Chinese cities, we found that environmental regulation could improve firm productivity, but the responses to environmental regulation differed across industry sectors, firm sizes, and locations. In this paper, we discuss the implications of these responses toward the environmental policy in China.

The aim of this article is to research on forestry green total factor productivity and explore the impact of financial support on forestry green total factor productivity.

The methods used in this study are super efficiency SBM model of undesired output and empirical model. SBM model is a kind of Data Envelopment Analysis (DEA). The SBM model with non-expected outputs (slacks-based measure) can be used to deal with the problem of efficiency measurement with multiple input and output variables and can be used to analyze the efficiency of green development of forestry economy.

First, the overall green total factor productivity of the authors’ country's forestry has shown a trend of first decline and then an increase from 2008 to 2018, and there are significant spatiotemporal differences; second, financial support has a significant positive impact on forestry green total factor productivity; third, environmental regulation has a significant threshold effect in the process of financial support on forestry green total factor productivity, and the role of financial support shows a trend of first increasing and then decreasing.

Secondly, taking the data of 30 provinces and cities in the authors’ country from 2008 to 2018 as the research object, using the super-efficiency SBM-Malmquist index to measure the country's forestry green total factor productivity and analyze its temporal and spatial changes; finally, a dynamic panel model was established to explore the impact of financial support on forestry green total factors quantitative impact on productivity, and adding environmental regulation as a threshold variable to establish a dynamic threshold regression, and found that financial support has a nonlinear impact on forestry green total factor productivity.

In the post‐war years of fast economic growth extensive government regulations to curb growing environmental problems were developed in most Western countries. This regulative activity was directed primarily at larger fixed industrial installations with locally identifiable environmental effects. Since then, however, smaller and mobile sources, which are more difficult to regulate effectively, have increased their share in pollution. Now the scale of environmental problems has also changed from being mainly a local one to being a regional, a national, an international and even a global one. Examples of this are the diffusion of durable toxic substances, eutrophication, acid rain, depletion of the higher ozone layers, and the rising temperature of the atmosphere. Moreover, perceived social costs of environmental policy and other types of regulation have risen, inspiring a worldwide movement towards deregulation and privatisation. So there is ample reason to reconsider the instruments of environmental policy used so far and to look for ways to amend environmental effectiveness and social costs. In section I some of the directions which the search for improved instruments might take are identified and in the subsequent sections certain financial, social and product‐oriented instruments are analysed in more detail.