Environmental Policy Stringency Research Articles

Green innovation for a sustainable environment: Modeling the new green knowledge production function for OECD countries

AbstractThe world community faces serious challenges such as climate change, biological loss, and environmental degradation. Developing ecological technologies is vital for coping with these unreversible crises. This study proposed a modified green knowledge production function to achieve sustainable development goals and generate policies for promoting environmental technologies. It examined the impact of market demands, environmental research and development expenditures, human capital, and environmental protection policies on the production of green environment technologies. Panel data included 16 OECD countries from 1990 to 2019. Data analysis strategies included the Gengenbach, Urbain, and Westerlund panel co‐integration test, fully modified least squares, mean group dynamic least squares, and estimators such as feasible generalized least squares and panel‐corrected standard errors for robust checks. A novel panel causality test via a half‐panel jackknife estimator was also applied for causality analyses. The findings showed that human capital, market size, and environmental policy stringency played significant roles in producing environmental technologies and innovations. Although environmental expenditures made by the government positively affected the supply of green innovation, no statistically significant results were observed. The study highlights the importance of enhancing environmental innovation factors by promoting policies, including human capital development, environmental sanctions, and market demands for a sustainable environment.

Abandonment Leads to Changes in Forest Structural and Soil Organic Carbon Stocks in Moso Bamboo Forests.

The important role of soil carbon pools in coping with climate change has become widely recognized. Moso bamboo (Phyllostachys pubescens) is an economically important bamboo species in South China; however, owing to factors such as rising labor costs and increasingly stringent environmental policies, Moso bamboo forests have recently been abandoned. The present study aimed to investigate the effects of abandonment on structural factors and soil organic carbon (SOC) stocks in Moso bamboo forests. We investigated Moso bamboo forests subjected to intensive management or abandonment for different durations and measured forest structural characteristics, mineral properties, soil nutrients, and other soil properties. Although abandonment did not significantly affect the height and diameter at breast height, it increased culm densities, biomass, and SOC stocks. The drivers of SOC stocks depended on soil depth and were mainly controlled by carbon decomposition mediated by soil properties. In the topsoil, mineral protection and soil total nitrogen (TN) exerted significant effects on SOC stocks; in the subsoil, soil TN was the main driver of SOC stocks. As the controlling factors of SOC stocks differed between the subsoil and topsoil, more attention should be paid to the subsoil. Overall, these findings refine our understanding of the structural characteristics and SOC stocks associated with Moso bamboo forest abandonment, serving as a reference for the follow-up management of these forests.

Does an environmental stringent policy really matter to achieve environmental sustainability in BRICS-T region? Evidence from novel method of moments quantile regression approach

Amidst pressing global environmental challenges, exacerbated by climate change and the imminent threat of global warming, there is a critical need to assess the efficacy of environmental policies. This study centers its attention on the pivotal role of these policies in addressing environmental concerns. Specifically, our research aims to scrutinize the impact of stringent environmental policies on environmental quality under the theoretical underpinnings of environmental Kuznets curve. To achieve this objective, the study collected data from BRICS-T economies over the period of 1990–2020. This study employed the method of moments quantile regression technique for empirical analysis. Our study validates the presence of the Environmental Kuznets curve (EKC hypothesis). Empirical findings reveal the sustained significance of environmental stringency across all quantiles, demonstrating a positive correlation in lower quantiles and a negative correlation in higher quantiles. At lower quantiles, the impact is insignificant initially, but pronounced due to efficiency improvements induced by stringent policies. The effects became negative at middle quantiles, indicating stringent policies might encounter diminishing returns where policy measures start stabilizing ecological impacts. At higher quantiles, the influence of ESI remains significant, reflecting ongoing adaptations in larger economies with higher ecological footprints. This suggests the potential effectiveness of stringent regulatory measures in mitigating environmental impacts and reducing ecological footprints. The identified inverted U-shaped curve signifies that while stringent policies may not inherently enhance environmental health, beyond a certain threshold, they can indeed contribute to its improvement. Our policy recommendation advocates for the widespread adoption and promotion of such stringent measures to safeguard environmental health.

Climate policy stringency and trade in energy transition minerals: An analysis of response patterns

Climate policies directly affect cleaner energy technology markets, affecting price signals for greener electricity production. In turn, the manufacturing of energy technologies relies heavily on mineral inputs, posing challenges in securing mineral ores and concentrates either from local mines or overseas. This paper contributes to the mineral-energy literature by examining the impact of climate change policies on the net import demand for five essential minerals used in cleaner energy technologies: copper, aluminium, nickel, cobalt, and manganese. We examined country-level panel data from 33 countries from 1992 to 2015 to understand patterns in net imports relative to renewable generation. This metric allows the examination of technological improvements that contribute to more efficient use of imported mineral inputs in renewable energy systems. Results suggest that while both net import volumes and renewable generation have increased over time, net imports per renewable generation have continuously declined on average, suggesting that nations may have efficiently utilized imported resources to generate more than proportionate increases in cleaner energy. Moreover, results from a cross-sectional autoregressive distributed lag model show that the stringency of environmental policies significantly affects net mineral imports per renewable generation, with marked variations across minerals and countries. Notably, with stricter policies, import reliance on cobalt and aluminium per renewable energy increases in the short run and eventually declines in the long run. Import reliance for copper declines per unit of renewable energy in the short run but increases in the long run. These findings emphasize the need for tailored policies to navigate mineral trade dynamics effectively. The research contributes valuable insights to the ongoing discussions surrounding sustainable energy transitions and global mineral trade patterns.

The role of energy intensity, green energy transition, and environmental policy stringency on environmental sustainability in G7 countries

The role of energy intensity, green energy transition, and environmental policy stringency on environmental sustainability in G7 countries

Explaining the stringency of environmental policies: Domestic determinants or international policy coordination?

This paper examines how and to what extent spatial interactions among EU national governments affect the stringency of environmental policies (EP). We innovate on the literature along three dimensions: 1) we evaluate the spatial interactions across countries to assess the “interaction dividend” associated with international treaties; 2) we better examine how political and institutional variables shape EP when such interactions are taken into account; 3) we identify the type of EP for which these interactions play a more relevant role by considering for the first time the new EPS21 disaggregated indexes of policy stringency. In a sample of 21 European countries between 2000 and 2018, a benchmark model shows that, among country-specific effects, proxies for the industries' lobbying power, quality of governance, government's ideology, decentralization and the urbanization rate of voters play important roles. When the model consider spatial interactions among countries, the estimates reveal that between 1/3 and more than one-half of a country's commitment to EP can be attributed to positive spillover effects from other countries, depending on the type of policy, with more prominent effects in technology support policies. These results reinforce the need of supranational coordination through international organizations and treaties.

How mineral resources rent collaborate with consumer price index, environmental policies, and economic performance in Türkiye and India: Evidence from artificial neural networks and machine learning

AbstractTaking focus on the possible effects on welfare and environmental issues in Türkiye and India, this study explores the relationship between the leasing of mineral resources (MRs), economic performance, use of renewable energy, and environmental policies. The study estimates changes in MRs throughout economic expansion using artificial intelligence (artificial neural network [ANN]) and supervised machine learning (SML). It focuses on important variables like index of stringency of environmental policies and the consumer price index, the conclusions of the ANN, ensemble method, and ML studies show how sensitive quarterly changes in the rent on MRs are to changes in the consumer price index, economic performance, and the use of renewable energy. Evaluation criteria such as root mean square error (RMSE), mean absolute error (MAE), mean square error (MSE), mean absolute percentage error (MAPE), and coefficient of determination highlight how much better ML models predict outcomes than ANN trials. In particular, the ML findings show an outstanding R2 of 0.99, an MAE of 0.6625, an MSE of 0.8324, a MAPE of 35.3677, and an RMSE of 0.9123 for India. Türkiye's machine learning results, on the other hand, display an MAE of 0.0164, an MSE of 0.0007, MAPE of 66.1594, RMSE of 0.0279, and a strong R2 of 0.98. For ANN, the error histogram is plotted to assess the model. The extremely low value of 0.0090 and 0.010, respectively, for Türkiye and India on the error histogram reflects the exceptional prediction quality. Türkiye and India have abundant MRs; however, they must be managed correctly for long‐term sustainability. Future researchers may verify this work using time series or panel data from other disciplines. This study examines factors affecting sustainable economic growth, including MR use, environmental policies, and eco‐friendly innovations. Other indicators, such as energy efficiency, carbon dioxide emissions, renewable energy consumption, and global value chain participation, may provide a different perspective. This study's conclusions should be verified by more research employing other geographic locations and others machine learning methods, as well as to illustrate how sustainable development is influenced by other variables.

Synergy for climate actions in G7 countries: Unraveling the role of environmental policy stringency between technological innovation and CO2 emission interplay with DOLS, FMOLS and MMQR approaches

The significant and indestructible repercussions of global warming have an enormous effect on economies worldwide. Inevitably the preservation of the environment remains a crucial element in the pursuit of sustainable development goals. The primary aim of this study is to assess the moderating effect of environmental policy stringency (EPS) between technological innovation (INV) and CO2 emission and direct association between financial development (FD), and financial globalization (FG) and environmental quality among the G7 countries. This analysis is conducted using a dataset covering the time period from 1990 to 2020, employing the Dynamic Ordinary least Square (DOLS), Fully Modified Ordinary Least Square (FMOLS), Canonical Cointegration Regression (CCR), and Method of Moment Quantile Regression (MMQR) estimation approaches. The results of DOLS, FMOLS, & CCR indicates that INV*EPS increase environmental quality by −0.21168, −0.21257 and −0.21255, respectively. Further, the outcomes of MMQR demonstrate that combine effect of INV & EPS contributes −0.2003 to −0.2264 across all quantiles from 20th to 80th. This indicates that technological innovation leads to enhanced environmental quality by mitigating CO2 emissions and implementation of more stringent environmental rules enhance the positive effects of green technologies by employing eco-friendly technologies to achieve carbon neutrality target. In order to effectively attain sustainable development goals, the study suggests that in economies that exhibit a higher degree of innovation, strong financial system, the adoption and implementation of environmentally sustainable technologies have a significant influence on the mitigation of CO2 emissions and the enhancement of environmental conditions. The study findings suggest few polices to policymakers: enhancing the green finance structure and strengthening the design of environmental regulations to promote green innovation. Research and development (R&D) activities have the potential to significantly contribute to the reduction of CO2 emissions through the effective application of scale effects and the implementation of efficient marketing tactics.

Growth-environment nexus in Canada: Revisiting EKC via demand and supply dynamics

Previous research on the growth-environment nexus has predominantly focused on demand-side indicators, disregarding the supply-side dynamic and the environmental Kuznets curve (EKC) hypothesis. This study examines the role of economic growth on environmental quality in Canada, considering various macroeconomic factors such as energy consumption, technology innovation, foreign direct investment, and institutional quality. Using time series data for the period 1990 to 2022, this study employs the dynamic autoregressive distributive lag (DARDL) co-integration model to assess the co-integrating relationship among variables and conduct counterfactual shock analysis. The results demonstrate that economic growth significantly affects demand-side dynamics, leading to increased carbon emissions and ecological footprint, while concurrently reducing the supply-side factor, namely the load capacity factor, in both the short and long run. Notably, these findings include the confirmation of the EKC hypothesis as it relates to environmental safety, measured through energy consumption within the Canadian context. In addition, counterfactual analysis of the DARDL approach examines the effects of (±) 1% and (±) 5% shocks from the independent to dependent variables. For robustness, the kernel regularized least squares machine learning algorithm validates the results obtained from the DARDL estimation technique. The study's findings suggest implementing stringent environmental policies to enhance supply-side environmental parameters while carefully balancing energy consumption to support growth. It is crucial to ensure that economic growth is not achieved at the expense of environmental degradation in Canada.

Unveiling the role of natural resources, energy transition and environmental policy stringency for sustainable environmental development: Evidence from BRIC +1

This study investigates the impacts of economic growth, energy transition, mineral market, traditional energy, environmental policy stringency, and load capacity factor on natural resource and sustainable environment management in BRIC +1 countries from 1993 to 2020. The CS-ARDL model is adopted to demonstrate the nexus between the abovementioned constructs. Empirical findings suggest that the mineral market and energy transition positively impact environmental sustainability. Additionally, environmental policy stringency and effective management of natural resources are equally important for developing a sustainable environment in BRIC +1 countries. Overall, there is a significant association between all the examined variables, and they are all equally important in facilitating environmental sustainability in the BRIC +1 countries. The empirical outcomes of the present study help policymakers establish ecological sustainability and guide them toward sustainable development.

Environmental policy stringency, ICT, and technological innovation for achieving sustainable development: Assessing the importance of governance and infrastructure

Achieving sustainable development goals (SDGs) has garnered significant attention from academia and policymakers worldwide. In this study, we examine the impact of ICT, technological innovation (TI), and environmental policy stringency (EPS) on SDI, considering the moderating role of governance quality (GQI) and transport infrastructure (TIS). A comprehensive dataset of 17 advanced nations is utilized from 1996 to 2021. To capture the dynamic and extreme marginal impacts of these policy instruments on SDG attainment, we employ the advanced technique of Feasible Generalized Least Square (FGLS). The results demonstrate that ICT has a positive and significant effect on SDGs, particularly when combined with high levels of governance quality (GOV) and transport infrastructure (TIS). Likewise, TI has a positive impact on SDGs, especially in the presence of strong governance. Furthermore, EPS exhibits a positive association with SDGs. The findings also reveal that while governance hurts SDGs, this effect diminishes when combined with higher levels of ICT, TI, and EPS, and when TIS positively moderates the relationships. The robustness estimations using DOLS and PCSE methods validate the FGLS findings. These results underscore the importance of ICT, TI, and EPS in advancing sustainable development. Moreover, they highlight the significance of good governance and robust transport infrastructure in maximizing the positive effects of these factors. These findings hold implications for policymakers and stakeholders involved in promoting sustainable development.

THE IMPACT OF FINANCIAL POLICIES ON PROMOTING THE DEVELOPMENT OF GREEN INNOVATION

This research investigates the factors influencing the development of green patents and their implications on green innovation. Green financing has the purpose of funding environmental initiatives by directing capital from financial institutions to eco-friendly projects. Through a review of existing literature and empirical analyses, we identify the influence of financial variables and economic policy strategy as key contributors. Preliminary findings suggest that these factors significantly impact the prevalence of green patents, highlighting the importance of policy and financial decisions in fostering environmentally sustainable technological advancements. Our findings reveal a positive correlation between environmental R&D expenditure and green innovation. Moreover, venture capital emerges as a significant driver of green innovation, facilitating the development of environmentally conscious solutions by mitigating financial risks. Additionally, the stringency of environmental policies and the presence of green bonds and carbon taxes demonstrate positive associations with green innovation. Consequently, the main objectives of this article are to examine the impact of financial policies such as R&D, Venture Capital, Debt financing and environmental regulations on the development of green patents and innovation as well as investigate the relationship between green bonds, carbon taxes and green innovation. Ultimately, this research contributes to the ongoing discourse on sustainable development, offering a nuanced understanding of the dynamics driving green innovation.

How AI shapes greener futures: Comparative insights from equity vs debt investment responses in renewable energy

This paper offers insights regarding the potential of AI software development to narrow the financing gap in renewables. By employing a panel of 49 economies covering 2011–2020, we estimate a two-way fixed effects model and reveal that AI software development significantly promotes equity investments in renewables while imposing no substantial effect on debt investments in the same field. Such results are robust to extra controls, outlier consideration, and the endogeneity concern. Moreover, it is found that AI software development's enhancing effect on equity investments in renewables manifests when the stringency of environmental policies, especially the intensity of public funding support for environmental-related R&D, is sufficiently high. Furthermore, AI software development has a more profound positive impact on equity investments in renewables in economies with more equal business opportunities and lower age dependency.

Environmental policy stringency and ecological footprint linkage: Mitigation measures of renewable energy and innovation

We scrutinize the environmental policies' efficacy in reducing ecological footprint by interweaving two other vibrant parameters of environmental degradation mitigation, i.e., renewable energy sources and innovation. To this end, we apply a Cross-Sectional Autoregressive Distributed Lags (CS-ARDL) approach to analyze panel time-series data (1990–2018) in the context of OECD countries. Our analysis shows that environmental policy significantly reduces ecological footprint through renewable energy and innovation channels. Our findings also support the idea that environmental policy's effectiveness is conditional on countries' bio-capacity surplus/deficit and the level of industrialization. The overall findings hold up well in the presence of cross-sectional dependence, short-run heterogeneity, and long-run homogeneity under the respective sample. Our findings underscore the need for more stringent environmental policies, supported by technological advancements and clean energy initiatives, to mitigate the impact of human economic activities on natural resources.

Environmental Policy and Environmental R&D in the Private Sector: New Evidence on the “Narrow” Porter Hypothesis

We examine the impact of the stringency of market-based and non-market-based environmental policies on private-sector environmental R&D expenditures. We find that the stringency of market-based environmental policies has a positive and statistically significant impact on environmental R&D expenditures in the private sector. In contrast, the stringency of non-market-based environmental policies is statistically insignificant. Thus, our findings provide evidence supporting the “narrow” Porter hypothesis.

Exploring the Combined Impact of Environmental Policy Stringency and Institutional Quality on Sustainable Energy: Evidence from Top 14 Green Economies

The growing concern for a green economy increases the demand for sustainable energy. Previous studies massively concentrate on solutions to achieve the target of sustainable energy. However, limited studies focus on the contribution of stringency to sustainable energy. This study explores the contribution of environmental policy stringency and institutional quality on sustainable energy for the top 14 green economies by utilizing data from 1990 to 2022. In empirical analysis, the study applies the PMG-ARDL and CS-ARDL models to obtain the short- and long-run estimates. The study's findings indicate that after controlling the impact of technological innovation, foreign direct investment, population, economic globalization, and gross domestic product per capita environmental policy stringency and institutional quality significantly promote sustainable energy in the long run. Based on the results, the study recommends strictness in implementing policies is more critical than just designing environmental policies.

Does environmental policy stringency alter the natural resources-emissions nexus? Evidence from G-7 countries

Natural resource management is indispensable keeping in view their positive economic impacts as well as their detrimental environmental consequences. To achieve certain SDGs, it is inevitable to manage natural resources through effective policies that help to inhibit adverse environmental impacts. Based on this approach, the current empirical analysis aims to probe whether environmental policy stringency intensifies, meagres, and/or halts the abysmal environmental impact of natural resources in G-7 countries (United Kingdom, United States, Canada, Italy, France, Japan, and Germany) for the period from 1990 to 2020. To that end, we rely on the second-generation panel data approaches and panel quantile regression. The outcomes reveal that natural resources increase carbon dioxide emission whereas the synergy of natural resources and environmental policy stringency plunges emissions across the quantiles. These findings suggest adoption of a strict environmental policy for attaining the targets of SGD-08 (economic growth), SDG-09 (innovations), SDG-11 (sustainable cities), SDG-12 (responsible consumption of natural resources), and SDG-13 (climate action).

Understanding how climate preferences, environmental policy stringency, and energy policy uncertainty shape renewable energy investments in Germany

Understanding how climate preferences, environmental policy stringency, and energy policy uncertainty shape renewable energy investments in Germany

Artificial Intelligence-Driven Multi-Energy Optimization: Promoting Green Transition of Rural Energy Planning and Sustainable Energy Economy

This research contributes to the overarching objectives of achieving carbon neutrality and enhancing environmental governance by examining the role of artificial intelligence-enhanced multi-energy optimization in rural energy planning within the broader context of a sustainable energy economy. By proposing an innovative planning framework that accounts for geographical and economic disparities across rural regions, this study specifically targets the optimization of energy systems in X County of Yantai City, Y County of Luoyang City, and Z County of Lanzhou City. Furthermore, it establishes a foundation for integrating these localized approaches into broader national carbon-neutral efforts and assessments of green total factor productivity. The comparative analysis of energy demand, conservation, efficiency, and economic metrics among these counties underscores the potential of tailored solutions to significantly advance low-carbon practices in agriculture, urban development, and industry. Additionally, the insights derived from this study offer a deeper understanding of the dynamics between government and enterprise in environmental governance, empirically supporting the Porter hypothesis, which postulates that stringent environmental policies can foster innovation and competitiveness. The rural coal-coupled biomass power generation model introduced in this work represents the convergence of green economy principles and financial systems, serving as a valuable guide for decision-making in decisions aimed at sustainable consumption and production. Moreover, this research underscores the importance of resilient and adaptable energy systems, proposing a pathway for evaluating emission trading markets and promoting sustainable economic recovery strategies that align with environmental sustainability goals.

Impact of green financing on CSR and environmental policies and procedures

Despite increasing global attention towards sustainable development, the empirical linkage between green financing and the enhancement of environmental and social governance (ESG) practices within industries remains underexplored. This study investigates the influence of green financing on Corporate Social Responsibility (CSR) and environmental policies and procedures in 40 Chinese industries from 2010 to 2020. By employing a baseline regression and a difference-in-differences methodology, this paper aims to quantify the extent to which green financing initiatives have impacted CSR activities and the adoption of rigorous environmental policies and procedures in the Chinese industrial sector. The results indicate that industries with access to green financing have shown significant improvements in their CSR engagements and the stringency of their environmental policies and procedures compared to those without such financial incentives. Specifically, the difference-in-differences analysis reveals a positive and statistically significant effect of green financing on the adoption of more stringent environmental policies and the enhancement of CSR practices. We identify the specific areas within CSR and environmental policies that are most influenced by green financing. We assess the effectiveness of green financing as a tool for promoting sustainable industrial practices. The analysis utilizes a comprehensive dataset, including industry-specific financing and ESG performance indicators, to conduct a longitudinal assessment over the decade in question. Based on these findings, the study concludes with a policy implication that emphasizes the critical role of green financing as a catalyst for improving CSR and environmental standards in industries. It suggests that policymakers and financial institutions should consider expanding green financing mechanisms to accelerate the transition towards more sustainable industrial practices.