Impact of energy efficiency, technology innovation, institutional quality, and trade openness on greenhouse gas emissions in ten Asian economies

A sustainable study of competitive industrial performance amidst environmental quality: New insight from novel Fourier perspective

This paper uses the novel Fourier Augmented Autoregressive Distributed Lag within the load capacity curve framework to investigate the effects of economic growth, trade openness, renewable energy consumption, and competitive industrial performance on environmental sustainability. The results of the empirical analysis provide evidence that the load capacity curve is valid in Turkiye. Moreover, while trade openness jeopardizes environmental sustainability, renewable energy consumption and industrial competitiveness increase environmental quality. Policymakers should focus intensively on policies that can achieve SDG 9 and industrialization activities. It is essential to give privileges, especially to companies operating in the industrial sector, regarding the transition to renewable energy. Energy efficiency policies that will accelerate the transition to clean energy sources are also an alternative to escape from fossil energy immediately. Environmental factors should be considered when importing intermediate goods used in industry, and these policies should be guaranteed by law as soon as possible.

Can forests realize the carbon neutrality dream? Evidence from a global sample

The enlarge in economic activities and the urban population at the global level has brought about an increase in the demand for energy, food, and natural resources, as well as an exacerbation in global climate change concerns. In this respect, it is important to ensure the balance between global climate change and global economic activities. Therefore, a wide literature has emerged that searches for alternative solutions to improve climate change and carbon dioxide (CO2) emissions. The majority of existing studies emphasize the importance of renewable energy sources in environmental improvement efforts. Few studies highlight the importance of forestation in environmental improvement efforts, highlighting the non-linear effects of forestation. To fill this gap, this study uses panel data from 181 countries between 1990 and 2022 and evaluates the non-linear impact of economic growth, forest extent, energy efficiency, and urban growth on per capita CO2 emissions using a dynamic panel threshold and dynamic panel quantile threshold methods. Furthermore, we extend the model and conduct robustness tests examining the non-linear threshold effects of renewable and non-renewable energy consumption on per capita CO2 emissions. Our findings provide pieces of evidence that forest extents are an alternative solution to renewable energy use and energy efficiency in environmental improvement efforts.

Role of natural resources, renewable energy sources, eco-innovation and carbon taxes in carbon neutrality: Evidence from G7 economies

Global warming has created problems for human life, and it has been increasing for a few years. All the developing and developed countries are establishing policies to attain zero carbon status. This study extends the ongoing debate on carbon emissions. It examines the effect of natural resources and RE (Biofuel and other renewable sources) on greenhouse gas (CO2 emission and PM2.5) emissions while using data over 22 years (1999-2021) from G7 countries. In addition, this study has investigated the effect of carbon taxes, financial development, and environmental policies on carbon neutrality. The cross-sectional-ARDL, the Common correlated effect means group (CCEMG), and the Augmented mean group (AMG) cutting-edge model have been employed. Quantile regression has been employed for robustness. The study results demonstrate that biofuel and other renewable energy (RE) sources, carbon taxes, environmental policy, and eco-innovation decrease greenhouse gas emissions (CO2 emissions). Meanwhile, financial development, and natural resource dependence positively impact carbon neutrality. The robustness result also verifies the findings from CS-ARDL, AMG, and CCEMG methods. The empirical findings are used to infer policy implications for G7 economies.

Do circular economy, renewable energy, industrialization, and globalization influence environmental indicators in belt and road initiative countries?

This paper is the first comprehensive research to examine the effect of circular economy on environment employing two environmental degradation indicators (CO2 emissions, ecological footprint) and one environmental quality indicator (load capacity factor) for 57 Belt and Road Initiative (BRI) countries during 2000-2019. The effect of other variables such as renewable energy, industrialization, and globalization was also controlled. The study applied the cross-sectional autoregressive distributed lag method (CS-ARDL), the augmented mean group (AMG), and common correlated effects mean group (CCEMG) methods as a robustness checks. The empirical findings reveal that circular economy and renewable energy have pro-environmental effects by decreasing carbon emissions and ecological footprint and increasing the load capacity factor in BRI countries. However, industrialization and globalization have detrimental effects on the environment. The result of causality shows a bidirectional causality between renewable energy, circular economy, industrialization, and three environmental indicators, but the relationship of globalization with CO2 emissions and the load capacity factor is unidirectional and with the ecological footprint is bidirectional. All the results are confirmed by the robustness tests. The study suggests policy implications for the BRI government.

Time-varying causality relationships between trade openness, technological innovation, industrialization, financial development, and carbon emissions in Thailand

Over the last twenty years, there has been swift growth in industrialization and technological advancements, driving economic progress. Nevertheless, it is inevitable that these sectors will bring about environmental shifts. Thus far, endeavors have been undertaken to assess the influence of industrialization and technological advancements on environmental deterioration. Additionally, the extensive discussion surrounding the impact of financial development, trade openness, and technological innovation on the environment has not yielded conclusive empirical findings. Studies often operate under the assumption of symmetric relationships, potentially leading to biased results. Adding to the discussion on the drivers of carbon neutrality, the time-dependent effects of critical aspects such as financial development and technological innovation should inform meaningful policies for environmental management. This article explores the time-varying causal association between trade openness, industrialization, financial development, technological innovation, and CO2 emissions in Thailand using novel time-varying Granger causality tests. The time-varying causality outcomes demonstrate that the associations change significantly over time, in contrast to the results of Toda-Yamamoto causality. Overall, there exists a bidirectional relationship between industrialization, financial development, trade openness, technological innovation, and CO2 emissions over different time sequences. These outcomes have implications for both policy and research.

Assessing the impact of geopolitical, economic, and institutional factors on China's environmental management in the Russian-Ukraine conflicting era

In contemporary times, geopolitical risk, and natural resources prices are susceptible due to the Russian-Ukraine conflict. In the meantime, emerging economies are struggling to explore the factors that could reduce ecological challenges and enhance environmental management. This research aims to analyze several economic, environmental, political, and institutional variables to ascertain their influence on greenhouse gas emissions in China. Covering the latest period from 1990 to 2022, various time series tests, including normality, stationarity, and cointegration tests. The results confirm that the variables studied have a stable pattern over time and are connected in the long run. The non-normal distribution of variables leads to opt novel moment quantile regression, where the results are tested for robustness via parametric approaches. The empirical results asserted that economic growth, natural resource prices, and trade significantly enhance ecological challenges (emissions). However, globalization, geopolitical risk, and institutional quality significantly reduce such environmental challenges. The results are robust, and both unidirectional and bidirectional causal associations confirm the importance of these variables in environmental management. Based on the results, this study recommends engagement in environmentally-friendly trading, investment in clean and green energy, and strengthening institutional quality for the region's environmental recovery.

Towards a greener future: examining carbon emission dynamics in Asia amid gross domestic product, energy consumption, and trade openness

The purpose of this study is to examine the impact of gross domestic product, energy consumption, and trade openness on carbon emission in Asia. Among the 48 countries in Asia, 42 were included in the analysis, spanning a period of 20 years. Given that Asia is the predominant contributor, accounting for 53% of global emissions as of 2019, a comprehensive examination at both continental and individual country levels becomes imperative. Such an approach aligns with local, regional, and global development agendas, contributing directly and indirectly to climate change mitigation. The analytical techniques employed in this study encompassed panel regression and multiple linear regression, illuminating the specific contributions of each country to the study variables and their impact on carbon emissions. The findings suggest that gross domestic product (13 out of 42 countries), energy consumption (21 out of 42 countries), and trade openness (eight out of 42 countries) have a highly significant impact (p < 0.01) on carbon emissions in Asia. Energy consumption plays a vital role in increasing carbon emissions in Asia, driven by rising populations, urbanisation, and oil and gas production. Policymakers can take several actions such as adopting a carbon pricing system, using sustainable transportation, renewable energy development, and international cooperation within Asia to reach the goal of being carbon neutral by 2050.

Revisiting the environmental Kuznets curve: assessing the impact of climate policy uncertainty in the Belt and Road Initiative

Climate change repercussions such as temperature shifts and more severe weather occurrences are felt globally. It contributes to larger-scale challenges, such as climate change and biodiversity loss in food production. As a result, the purpose of this research is to develop strategies to grow the economy without harming the environment. Therefore, we revisit the environmental Kuznets curve (EKC) hypothesis, considering the impact of climate policy uncertainty along with other control variables. We investigated yearly panel data from 47 Belt and Road Initiative (BRI) nations from 1998 to 2021. Pooled regression, fixed effect, and the generalized method of moment (GMM) findings all confirmed the presence of inverted U-shaped EKC in BRI counties. Findings from this paper provide policymakers with actionable ideas, outlining a framework for bringing trade and climate agendas into harmony in BRI countries. The best way to promote economic growth and reduce carbon dioxide emissions is to push for trade and climate policies to be coordinated. Moreover, improving institutional quality is essential for strong environmental governance, as it facilitates the adoption of environmentally friendly industrialization techniques and the efficient administration of climate policy uncertainties.

Moderating effect of governance on healthcare and environmental emissions

Governance has become indispensable within the healthcare sector, but previous studies have not explored the potential environmental benefits linked to healthcare governance. Thus, this study focuses on the role of governance in moderating healthcare and environmental emissions in 159 low, lower-middle, upper-middle and high-income countries. To do so, cross-sectional autoregressive distributed lag (CS-ARDL) techniques were applied using panel data from 1999 to 2021, followed by the computation of threshold and marginal effect of governance on healthcare and environmental emissions nexus. Findings revealed that, with the exception of high-income countries in the short run, governance has an insignificant impact on healthcare and emissions nexus in low-, lower-middle and upper-middle-income countries. Surprisingly, the findings imply that, in the long run, countries with greater levels of governance are likely to have lesser environmental impacts related to healthcare. There was also evidence indicating that low, lower-middle, upper-middle and high-income countries must reach a certain level of governance before realising the benefits of healthcare. Therefore, to achieve lower environmental impacts from healthcare, countries must promote effective governance policies that can incentivise and enforce sustainable practices and technologies in the healthcare sector.

Revisiting the nexus between digital trade, green technological innovation, and environmental sustainability in BRICS economies

After the UN Climate Action Summit in 2019, many countries started progressing towards race to zero targets. The intricate framework of digitalization and green technologies has the potential to persuade governments to implement policies that promote a zero-carbon economy, i.e., green economy. Hence, this study determines the effect of digital trade (DGT) and green technological innovation (GTI) on environmental sustainability (ENS) by considering the role of renewable energy consumption (REC), globalization (GLOB), and economic growth (EG). The study measured ENS by taking into account three proxy variables, i.e., ecological footprint (EF), carbon dioxide emission (CO2e), and methane emissions (CH4e). POLS and PMG-ARDL techniques are applied to the panel data of BRICS (Brazil, Russia, India, China, and South Africa) from 2000 to 2019. Panel Quantile Regression (PQR) along with AMG and CCEMG estimators is applied hereafter for checking the robustness of the empirical results. The long-run empirical outcomes show the positive association of DGT, GTI, REC, and GLOB with ENS. Lastly, this study inscribed the Environmental Kuznets Curve (EKC) and highlights policy implications and governmental measures to ensure environmental sustainability in BRICS economies.

Does higher energy efficiency growth homogeneously affect carbon emission growth rate across developing Sub-Saharan African nations? The importance of utilizing clean energy

Establishing a sustainable environment and acquiring a carbon-neutral status require Sub-Saharan African nations to reduce their year-on-year growth rates of carbon emission levels. Thus, this study considers a sample of 38 countries from this region and selects the time period from 2000 to 2020 for analyzing the annual carbon emission growth rate influencing impacts of energy efficiency, clean energy, institutional quality, international trade, and net receipts of foreign direct investment. Overall, for the full sample of Sub-Saharan African nations, the results verify that the enhancing the growth rate of energy efficiency improvement reduces both total and per capita annual carbon emission growth rates. Besides, the results endorse that enhancing renewable energy shares of the final energy consumption profiles and promoting good governance-led betterment of institutional quality also plunge emission growth rates in the long run. More importantly, energy efficiency improvement, renewable energy consumption, and better quality institutions are observed to jointly exert carbon emission growth rate-impeding effects, as well. By contrast, more openness to international trade is not seen to influence the carbon emission growth rates of the Sub-Saharan African nations of concern. Lastly, a greater share of net foreign direct investment receipts in the national output level is evidenced to boost annual carbon emission growth rates across this region; consequently, the pollution haven hypothesis is verified. Furthermore, these above-mentioned findings are found to be heterogeneous across groups of low-income and middle-income Sub-Saharan African nations. Accordingly, in line with the findings, a couple of policies are recommended to the governments of the Sub-Saharan African countries in order to guide them in designing effective environmental sustainability policies that are relevant for tackling climate change-related atrocities in the future.

Powering sustainable growth in West Africa: exploring the role of environmental tax, economic development, and financial development in shaping renewable energy consumption patterns

Over time, the economy's growth, financial development, and environmental taxes have become vital tools in countering ecological degradation and promoting clean energy. However, there needs to be a research gap in assessing these policies' collective impact on renewable energy adoption, especially in developing West African countries. This study addresses this gap by evaluating the effectiveness of these policies from 1990 to 2020, using the Generalized Method of Moments (GMM), fixed effect, and pooled Ordinary Least Squares (OLS) models. The Dumitrescu-Hurlin panel causality test reveals bidirectional causality between economic growth and renewable energy consumption, as well as between financial development and renewable energy use. Unidirectional causality is found from environmental tax to renewable energy consumption. GMM results highlight the positive influences of economic growth and environmental taxes on renewable energy consumption, while financial development negatively affects it. These outcomes are consistent with fixed effect and pooled OLS models. Sectorial heterogeneity analysis indicates better results for countries with strong institutions, advanced technology, and strict regulations. In conclusion, this study's insights can guide policies for sustainability in West Africa, leveraging economic growth, environmental taxes, and technology for effective renewable energy integration.

The impacts of renewable energy and institutional quality in environmental sustainability in the context of the sustainable development goals: A novel approach with the inverted load capacity factor

It is crucial to fulfill sustainable development goals in combating environmental pollution. Recently, there has been a growing literature on environmental pollution; however, while many proxies represent environmental pollution, few proxies represent environmental sustainability. In this paper, we examine the effects of institutional quality (SDG-16), economic growth (SDG-8), and renewable energy (SDG-7) on the inverted load capacity factor (SDG-13) in OECD countries from 1999 to 2018. The objective is to ensure environmental sustainability within the Sustainable Development Goals (SDGs) framework. In this respect, the study differs from the existing literature by approaching the sustainable environment literature from a broader perspective. Long-term empirical estimates from the PMG-ARDL technique have shown that institutional quality, reel income, and population increase the inverted load capacity factor, that is, decrease environmental sustainability. However, on the contrary, renewable energy decreases the inverted load capacity factor. Therefore, renewable energy consumption helps reach SDG-7 and SDG-13 in OECD countries. In addition, it is found that economic growth is significant both in the long run and in the short run, and the impact of economic growth on the environment is greater in the short run than in the long run. This result supports the environmental Kuznets curve (EKC) hypothesis for OECD countries. The panel causality test results find a bidirectional causality relationship from renewable energy and population to inverted load capacity factor and a unidirectional causality relationship from institutional quality to inverted load capacity factor. This study argues that policymakers should concentrate on deploying environmentally friendly technology to slow down environmental degradation, increase the usage of renewable energy sources, and promote sustainable development in line with the SDGs.

The role of quality institutions and technological innovations in environmental sustainability: Panel data analysis of BRI countries

The majority of countries struggle to accomplish sustainable development and environmental sustainability; nevertheless, environmental degradation issues can be resolved by enhancing technological innovations and institutional effectiveness. This study assesses the impact of technological innovations and institutional quality on carbon dioxide emission in the Belt and road initiative countries for the time period of 2002 to 2019. Fixed effect, OLS, and generalized method of moment estimators were applied to the panel data for analysis. The results shows that energy from fossil fuels, economic growth and technological innovations increase environmental degradation by rising carbon dioxide emission. Renewable energy consumption, the rule of law, and the quality of institutions make a significant contribution to the improvement of environmental quality. In particular, the Environmental Kuznets Curve and Innovation Claudia curve is valid in the Belt and Road Initiative countries. In the presence of quality institutions, countries can achieve sustainable growth and environmental sustainability by expanding their use of green technology and renewable energy. The findings provide suggestions to the sample countries on the improvement of institutional framework and technological innovations in order to achieve sustainable development.

Impact of global value chain and technological innovation on China's industrial greenhouse gas emissions and trend prediction

The global value chain has introduced profound changes in international trade, economic development, and technology progress as well as greenhouse gas emissions worldwide. This paper investigated the impact of the global value chain and technological innovation on greenhouse gas emissions by introducing a partially linear functional-coefficient model based on panel data of 15 industrial sectors in China from 2000 to 2020. Moreover, the greenhouse gas emission trends of China's industrial sectors from 2024 to 2035 were predicted using the autoregressive integrated moving average model. The results showed that (1) Greenhouse gas emissions were affected negatively by global value chain position and independent innovation. Nevertheless, foreign innovation had the opposite effect. (2) The results of the partially linear functional-coefficient model implied that the inhibitory effect of independent innovation on GHG emissions decreased with an improvement in the global value chain position. (3) The positive effect of foreign innovation on greenhouse gas emissions increased and then, decreased as the global value chain position improved. (4) The prediction results indicated that greenhouse gas emissions will continue on an upward trend from 2024 to 2035, while industrial carbon dioxide emissions should peak at 10.21 Gt in 2028. This carbon-peaking goal would be achieved in China's industrial sector by actively improving the global value chain position. Addressing these issues will enable China to take full advantage of the development opportunities of participating in the global value chain.

Rural electrification using renewable energy resources and its environmental impact assessment

Integrating a group of generation units and loads into a microgrid improves power supply sustainability, decreases greenhouse gas emissions, and lowers generating costs. However, this integration necessitates the development of an improved energy management system. The microgrid distributes electricity among energy resources to optimize either the generating cost or the quantity of greenhouse gas emissions, or both at the same time. The low-cost energy supply requires a precise cost model for each energy component. This article aims to develop the generation cost model that incorporates renewable energy to lower the total operating cost and curb greenhouse gas emissions. The suggested optimization problem deals with the low-cost energy solution for the rural area of India. The proposed system used particle swarm optimization, a global optimization strategy, in the study. Minimum cost and emission scenarios are objective issues while operating with tolerable emissions, and costs are multi-objective of the present study. The outcomes of the scenarios are used to provide viable optimized solutions to multi-objective problems using the optimization technique. Finally, a battery bank's potential to compensate for generation shortages while minimizing emissions is being studied. The study is performed on a microgrid comprising photovoltaic PV, diesel generator, battery, wind turbine, and an Indian rural scenario load profile. The finding suggested that the optimal configuration has a total net cost of operation is $59,195.61. The per-unit cost of energy is 0.20 $/kWh with a saving of [Formula: see text] emission is 5994 kg/year. This modular feasibility analysis demonstrates that utilizing a hybrid energy system to power the planning is cost-effective. This research is anticipated to aid rural communities and other stakeholders in making well-informed decisions throughout the planning stages of similar initiatives.