Do renewable and nuclear energy enhance environmental quality in France? A new EKC approach with the load capacity factor

Achieving ecological sustainability in European countries: Does low carbon energy lead to a carbon neutrality pathway?

The European Union (EU) recently intensified its focus on Sustainable Development Goals (SDGs) to achieve its net-zero emissions target. Thus, climate action and access to clean energy have become prominent research topics. Previous studies have predominantly explored the individual impacts of nuclear and renewable energy on EU economies within the environmental Kuznets curve (EKC) hypothesis. Departing from this conventional approach, the present study examines the effect of low-carbon energy consumption (LEC) on environmental quality while controlling for ecological influences of natural resource rents (NAT) and foreign direct investment (FDI). The study adopts the CS-ARDL approach to analyze annual data from 1996 to 2022. This analysis is framed within a novel framework: the load capacity curve (LCC) hypothesis. The empirical assessment reveals the following findings: i) The LCC hypothesis is validated for EU economies, indicating that these countries are on a path towards achieving their net-zero emissions target. ii) LEC positively impacts the ecosystem. iii) FDI and NAT are found to degrade environmental quality. Given these findings, EU economies should continue to increase their LEC within the total energy mix. Environmental sustainability can be further supported by implementing green policies aimed at regulating NAT and FDI. In conclusion, this study offers policies that will put the EU on the zero-emission path within the framework of SDGs.

Are clean energy technologies a panacea for environmental sustainability in sub-Saharan African countries?

The average population in sub-Saharan Africa that has access to clean fuel for cooking and technology is 23.6%. This study examines the panel data for 29 sub-Saharan African (SSA) countries for the period 2000-2018 to estimate impacts of clean energy technologies on environmental sustainability measured by load capacity factor (LCF) to capture both nature's supply and man's demand for the environment. The study used generalized quantile regression, which is more robust to outliers and eliminates the endogeneity of variables in the model using lagged instruments. Results show that clean energy technologies (clean fuels for cooking and renewable energy) have positive and statistically significant impacts on environmental sustainability in SSA for almost all quantiles. For robustness checks, we used Bayesian panel regression estimates and the results remained unchanged. The overall results suggest that clean energy technologies improve environmental sustainability in SSA. The result shows a U-shaped relationship between environmental quality and income and confirms the Load Capacity Curve (LCC) hypothesis in SSA, which implies that income first worsens environmental sustainability and then, after exceeding certain quantiles, improves environmental sustainability. On the other hand, the results also confirm the environmental Kuznet curve (EKC) hypothesis in SSA. The findings show the importance of using clean fuels for cooking, trade, and renewable energy consumption in improving environmental sustainability in the region. The policy implication is that governments in SSA should reduce the cost of energy services (i.e., renewable energy and clean fuels for cooking) to achieve greater environmental sustainability in the region.

The dynamic relationships between nuclear energy consumption, nuclear reactors and load capacity factor: time and frequency domain panel data analysis

Nuclear energy is an environmental issue that needs to be carefully considered regarding its consequences. The environmental effects of nuclear energy encompass a complex interplay of factors, ranging from managing radioactive waste to the potential for accidents, emissions, and resource depletion, necessitating a thorough examination of its impact on our planet. This study examines the relationships between nuclear energy, nuclear fission, nuclear fusion, and load capacity factor for the eight countries (Canada, China, France, Germany, Japan, Russia, Spain, USA) that consumed the most nuclear energy from 1993 to 2018 using the time (Emirmahmutoglu & Kose, 2011) and frequency domain (Croux & Reusens, 2013) panel causality tests. The results differ according to time and frequency domain causality tests. While the time-domain causality test results showed no causal relationship between the nuclear energy consumption, nuclear reactors, and the load capacity factor variables, the frequency-domain causality test revealed that there are causal relationships between these variables in the short, intermediate and long run. According to the frequency-domain causality test results, there is a bidirectional causality relationship between nuclear reactors, energy consumption and load capacity factor. In line with the main findings of this study, it is recommended that these countries implement effective policies to increase environmental quality and make investments and incentives in nuclear energy and technologies.

Do the effects of aggregate and disaggregate energy consumption on different environmental quality indicators change in the transition to sustainable development? Evidence from wavelet coherence analysis

In the 2030 Agenda for Sustainable Development, adopted by the United Nations (UN) member states in 2015, half of the target period has been exceeded. However, China, whose energy consumption relies heavily on fossil resources, remains at the top of the list of global polluters. Therefore, investigating the environmental impacts of energy types is essential to China's path towards Sustainable Development Goals (SDG)-7 and SDG-13. Based on this motivation, the paper offers new insights into the energy-environment literature for China with wavelet coherence analysis (WCA). This approach can investigate the relationship between variables in a periodic manner based on the frequency behavior of the models. The paper separately analyzes the effects of primary energy consumption (PEC), fossil energy consumption (FEC), renewable energy consumption (REC), nuclear energy consumption (NEC), GDP, and population (POP) on three different environmental indicators in China. Using two environmental pollution indicators (carbon emission (CO2) and ecological footprint (EF)) and one environmental quality indicator (load capacity factor (LCF)), the paper allows for comparison and robustness checks on the environmental impacts of energy indicators. Empirical findings reveal the following: (i) Except for REC and POP in the CO2 model, the variables in all three models largely move together during the period under observation; (ii) variables other than POP have consistent coefficient signs; (iii) PEC, FEC, NEC, and GDP increase CO2 and EF while decreasing LCF; (iv) the effect of NEC on LCF is more obvious until 2000; (v) unlike the others, REC affects CO2 and EF negatively and LCF positively; (vi) there is bidirectional causality between PEC and environmental indicators but not for REC; (vii) the causality relations of other variables with environmental indicators differ in terms of model, time, and direction of causality. In light of the findings, the paper highlights that only the REC improves environmental quality in China. Other energy indicators contribute to environmental degradation. China, whose ecological deficit has increased dramatically in recent years, urgently needs to reduce its dependence on fossil energy sources by accelerating investments in REC. Governments should also review nuclear energy policies, which are expected to help achieve carbon neutrality.

Is the load capacity curve a true phenomenon for OECD economies? Hidden behavior of financial institutions and markets in Environmental Sustainability

Over the last few decades, the globe has faced severe challenges in isolating entire nations from social, economic, and environmental issues. However, rising pollution levels have become the most debatable agenda. To resolve this, the world has introduced a few green initiatives, i.e., the Paris Agreement, the Kyoto Protocol and the Sustainable Development Goals (SDGs). Interestingly, to meet the desired threshold level, all stockholders demand massive finance to comply with such green initiatives. Thus, to highlight the importance of the financial sector, this study considers 26 OECD economies covering the period of 1982-2018. The leading importance of this study is utilizing the load capacity factor (LCF) as a decent proxy for sustainability. Similarly, the present empirical study utilizes advanced estimators to investigate the role of financial market index (FMI), financial institutions index (FII), renewable energy (REC) and income in environmental quality. The summarized results describe the positive role of REC in LCF in the specified nations. Conversely, FMI and FII are inverse-connected with the load capacity curve. Finally, the Load Capacity Curve (LCC) is validated for the selected economies. Interestingly, this study also suggests some imperative implications for boosting environmental sustainability. Such outcomes highlight the urgent need for legislative frameworks to accelerate the switch to renewable energy sources. Additionally, they emphasize the need for stricter oversight and control of financial institutions regarding their investments and policies for environmental preservation. Finally, the study raises the possibility that financial markets might obstruct ecological safeguards.

Is climate change hindering the economic progress of Nigerian economy? Insights from dynamic models

This study investigates the link between climate change and economic growth in Nigeria from 1961 to 2022. To provide a robust analysis that facilitates a nuanced examination of this dynamic relationship, this study employs state-of-the-art econometric approaches, including autoregressive distributed lag (ARDL), fully modified least squares (FMOLS), novel quantile autoregressive distributed lag (QARDL), and time-varying causality. The empirical results of this study are as follows: (1) the impact of climate change on economic growth is not felt in the short run. However, climate change negatively influences economic growth in Nigeria in the long run, (2) the elasticity of climate change increases across the conditional quantile economic growth, (3) unidirectional causality from climate change to economic growth across different time dimensions. These empirical outcomes advocate for a proactive and adaptive policy framework, emphasising the need for the Nigerian government to adopt climate-smart policies.

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.

Shaping a greener future: The role of geopolitical risk, renewable energy and financial development on environmental sustainability using the LCC hypothesis

The recent progress report of Sustainable Development Goals (SDG) 2023 highlighted the extreme reactions of environmental degradation. This report also shows that the current efforts for achieving environmental sustainability (SDG 13) are inadequate and a comprehensive policy agenda is needed. However, the present literature has highlighted several determinants of environmental degradation but the influence of geopolitical risk on environmental quality (EQ) is relatively ignored. To fill this research gap and propose a inclusive policy structure for achieving the sustainable development goals. This study is the earliest attempt that delve into the effects o of geopolitical risk (GPR), financial development (FD), and renewable energy consumption (REC) on load capacity factor (LCF) under the framework of load capacity curve (LCC) hypothesis for selected Asian countries during 1990-2020. In this regard, we use several preliminary sensitivity tests to check the features and reliability of the dataset. Similarly, we use panel quantile regression for investigating long-run relationships. The factual results affirm the existence of the LCC hypothesis in selected Asian countries. Our findings also show that geopolitical risk reduces environmental quality whereas financial development and REC increase environmental quality. Drawing from the empirical findings, this study suggests a holistic policy approach for achieving the targets of SDG 13 (climate change).

Do institutions contribute to environmental sustainability? A global analysis using the dynamic spatial Durbin and threshold models

There has been a recent surge in attention to the potential involvement of institutions in enhancing environmental quality. This research contributes to the ongoing debate by analyzing the spillover and nonlinear effects of institutions on the load capacity factor (LCF) in a sample of 100 countries between 2000 and 2019. The spillover effects are analyzed using the dynamic spatial Durbin model (DSDM), while the dynamic threshold model is implemented to estimate the nonlinear impacts of institutions. The Moran's I and Geary's C tests reveal a positive spatial autocorrelation for the LCF. The DSDM indicates the existence of positive direct and indirect (spillover) effects of political stability, control of corruption, and the rule of law on the LCF. Moreover, control of corruption has the highest positive influence on the environment. When conducting the threshold analysis, the locally weighted scatterplot smoothing curve indicates a nonlinear relationship between institutions and LCF, while the threshold test suggests a single threshold and two regimes. The dynamic panel threshold model reveals that government effectiveness and the rule of law positively affect the environment under both regimes. On the contrary, the positive effects of control of corruption, regulatory quality, and political stability are only observed under the upper regime. Furthermore, control of corruption has the highest positive environmental impact, albeit it needs more time to be achieved. The research emphasizes the importance of international collaboration and the design of both short- and long-term strategies to enhance institutional quality and, consequently, safeguard the environment.

Global production patterns: Understanding the relationship between greenhouse gas emissions, agriculture greening and climate variability

Climate change due to increased greenhouse gas emissions (GHG) in the atmosphere has been consistently observed since the mid-20th century. The profound influence of global climate change on greenhouse gas (GHG) emissions, encompassing carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), has established a vital feedback loop that contributes to further climate change. This intricate relationship necessitates a comprehensive understanding of the underlying feedback mechanisms. By examining the interactions between global climate change, soil, and GHG emissions, we can elucidate the complexities of CO2, CH4, and N2O dynamics and their implications. In this study, we evaluate the global climate change relationship with GHG globally in 246 countries. We find a robust positive association between climate and GHG emissions. By 2100, GHG emissions will increase in all G7 countries and China while decreasing in the United Kingdom based on current economic growth policies, resulting in a net global increase, suggesting that climate-driven increase in GHG and climate variations impact crop production loss due to soil impacts and not provide climate adaptation. The study highlights the diverse strategies employed by G7 countries in reducing GHG emissions, with France leveraging nuclear power, Germany focusing on renewables, and Italy targeting its industrial and transportation sectors. The UK and Japan are making significant progress in emission reduction through renewable energy, while the US and Canada face challenges due to their industrial activities and reliance on fossil fuels.

Do renewable energy and human capital facilitate the improvement of environmental quality in the United States? A new perspective on environmental issues with the load capacity factor

Recently, countries have been making intensive efforts to alleviate the burden on the environment and to make environmental conditions sustainable. In this context, our study aims to investigate the long-term impact of renewable energy consumption (REC) and human capital (HC) by considering the load capacity factor (LCF). We also investigate the long-term impact of economic growth (Y) and non-renewable energy consumption (NREC) on the LCF. In this context, we analyze annual data for the U.S. for the period 1965-2018 using the newly developed augmented ARDL (AARDL) approach. The long-term empirical results show the following. i) Increases in Y negatively affect LCF and deteriorate environmental quality. ii) Increases in NREC negatively affect LCF and accelerate the deterioration of environmental quality. iii) REC has no significant impact on environmental quality. iv) Increases in HC support the improvement of environmental quality. The empirical results show that contrary to expectations, renewable energy consumption does not have a significant impact on environmental quality in the U.S., whereas human capital is an important factor in improving environmental quality. In this context, US policymakers should pave the way for more investment in eco-friendly renewable energy investments and human capital to establish sustainable environmental quality. Policymakers should also take steps to reduce the use of fossil fuels.

Assessment of the environmental kuznets curve within EU-27: Steps toward environmental sustainability (1990-2019)

Reducing environmental pollution is a critical goal in global environmental economics and economic development. The European Union (EU) faces environmental challenges due to its development activities. Here we present a comprehensive approach to assess the impact of carbon dioxide (CO2) emissions, energy consumption (EC), population structure (POP), economy (GDP), and policies on the environment within the EU using the environmental Kuznets curve (EKC). Our research reveals that between 1990 and 2019, the EU-27 experienced an increase of +1.18 million tonnes of oil equivalent (Mtoe) per year in energy consumption (p < 0.05), while CO2 emissions decreased by 24.25 million tonnes (Mt) per year (p < 0.05). The highest reduction in CO2 emissions occurred in Germany (-7.52 Mt CO2 annually), and the lowest in Latvia (-0.087 Mt CO2 annually). The empirical EKC analysis shows an inverted-U shaped relationship between GDP and CO2 emissions in the EU-27. Specifically, a 1% increase in GDP results in a 0.705% increase in carbon emission, while a 1% increase in GDP2 leads to a 0.062% reduction in environmental pollution in the long run (p < 0.01). These findings indicate that economic development within the EU has reached a stage where economic growth positively impacts the environment. Overall, this study provides insights into the effectiveness of environmental policies in mitigating degradation and promoting green growth in the EU 27 countries.

How do information and communication technology, human capital and renewable energy affect CO2 emission; New insights from BRI countries

If nations want to attain sustainable development with the exponential growth of information and communication technology (ICT) around the world, they must understand the connection between ICT and carbon emissions. Therefore, this study has used panel data from 64 ''Belt and Road Initiative economies between 2000 and 2021 while finding the impact of ICT, renewable energy consumption (REC), human capital (HC) and economic growth (EG) on CO2 emissions. This study employs the Augmented Mean Group (AMG) estimator, Mean Group (MG) estimator and the Dumitrescu-Hurlin panel causality. The findings indicate that the use of ICT, HC and the REC are inversely related to CO2 emissions, whereas EG is positively associated to CO2 emissions and hence poses a danger to environmental sustainability. In addition, the interaction term of EG with ICT, REC and HC has negative impact on CO2 emissions in BRI economies. Intriguingly, the results reveal that ICT and CO2 emissions has inverted U-shape relationship in BRI economies. Furthermore, the causality results show that ICT, REC, and human capital are all cause and effect linkages that affect CO2 emissions in both directions. In order to reduce energy utilization and boost economic growth, the findings stress the importance of implementing cutting-edge ICT and REC in the industrial sector.

Evaluating forest depletion and structural change effects on environmental sustainability in Pakistan: Through the lens of the load capacity factor

The pace of species extinction and deforestation has increased dramatically due to the substantial increase in global environmental degradation. This trend is approaching the crucial temperature threshold of 2 °C and calls for more attention. Although previous research has observed the individual impacts of forest depletion, structural change, economic growth, and urbanization on various sustainability outcomes, there has been no previous research into their interrelationships with an emphasis on the load capacity factor (LCF). Furthermore, no previous study has examined the environmental impacts of the abovementioned variables by contrasting the results of LCF and CO2 emissions in Pakistan. Therefore, this research suggests a theoretical framework that integrates these concepts, provides a roadmap for an effective and sustainable mitigation strategy for Pakistan and compares LCF results with CO2 emissions. Using the time-series data from 1970 to 2021, a unique and sophisticated dynamic Autoregressive Distributed Lag (DARDL) technique, the authors found that (i) a 1 % rise in forest depletion leads to a decline in load capacity factor by 0.026 %. (ii) A one per cent upsurge in structural change fosters environmental sustainability by raising the load capacity factor by 0.084 %. (iii) An increase of 1 % in economic growth dwindles the load capacity factor by 0.027 %. (iv) A one per cent surge in urbanization enhances the load capacity factor by 0.029 %. The findings suggest that Pakistan's Government should promote afforestation by emphasizing the constructive role of structural change in achieving environmental sustainability.

Role of the government towards stock markets and carbon emissions: evidence from wavelet approach

The government of any country can play a great role in promoting economic and environmental policy reforms in both normal and crisis periods, but during the crisis period, the role of the government should take the economy into a recovery position. The stock market is the backbone of the financial system that needs the government's attention, especially in the period of financial stress and environmental protection is the responsibility of every economy to live in a healthy environment. Combining this motive, this study analyzed the role of the government towards the stock market and carbon emission by using different approaches, including the wavelet approach, OLS regression, and the Granger causality test. The wavelet approach is useful for analyzing the role of the government at different time intervals by using the time horizon from 1993 to 2021. World governance's six indicators in terms of voice and accountability, control of corruption, rules of law, regulatory quality, political stability, and government effectiveness are used as the proxy for the role of the government. Our findings show that all WGI indicators have a positive relationship with the stock market of Malaysia except voice and accountability while concerning voice and accountability, the role of the government of Malaysia is negative on the stock market. Similarly, our findings also show that the effective government governance mechanism through WGI indicators has a significant positive impact on CO2 emission due to industrialization. Furthermore, findings of the Granger causality test reveal that all the WGI indicators cause to stock market of Malaysia, and political stability has bi-directional causality indicating stock market index is also a factor that caused the political stability within Malaysia. In the Granger causality results of the CO2 and WGI indicators, there is unidirectional causality found between rules of law and regulatory quality with CO2 emission. This study advocated strong implementations for the investors for investment decisions in effective governance countries and implications for the government to remove their weakness by making effective governance related to the economy and as well as the environments within the country.

The role of environmental technologies, institutional quality, and globalization on environmental sustainability in European Union countries: new evidence from advanced panel data estimations

Factors such as investments in environmentally clean technologies, globalization, and institutional quality significantly increase environmental quality. The study aims to provide light on how environmental technologies, institutional quality, globalization, and economic growth affect a sustainable environment. In addition, this study evaluates the European Union's carbon zero target by 2050 and the results of achieving carbon neutrality by 2030, which was put on the agenda at the UN Climate Change Conference of the Parties (COP-26). For this purpose, ten countries (Germany, Austria, Denmark, Finland, France, Netherlands, Spain, Italy, Sweden, and Switzerland) that invest in the highest environmental technology in the European Union were selected in the study. The data range of the study is from 1990 to 2019. Also, the validity of the load capacity curve (LCC) hypothesis was investigated in these countries. The CCEMG and DCCE estimators were used to estimate long-run coefficients. When the panel was assessed as a whole, the LCC hypothesis was determined to be valid by both estimators. According to country-based results, it has been determined that the LCC hypothesis is valid only for Spain. The study also includes the following observations. (i) Environmental technologies increase LCF for Austria, improving environmental quality. (ii) Globalization reduces LCF for Austria. (iii) Institutional quality variable decreases LCF for Austria and increases LCF for Germany and France. These findings suggest that to attain a sustainable environment in the future, policymakers should raise research and development budgets for environmental technology, enhance the standards of institutions, and take globalization into account.

Evaluating the impact of technological innovation and energy efficiency on load capacity factor: empirical analysis of India

The determinants of environmental degradation have been investigated many times by utilizing carbon dioxide emissions and/or ecological footprint. However, these traditional environmental degradation indicators do not consider the supply side of environmental problems. Therefore, this study focuses on the dynamic influence of financial development, energy efficiency, economic growth, and technological innovation on environmental degradation in India through the load capacity factor, including both the supply and demand sides of environmental problems. For that purpose, the recently developed dynamically simulated autoregressive distributed lag (ARDL) method is employed using the annual time-series data extending from 1980-2020. The dynamically simulated ARDL results demonstrate that financial development, economic growth, and technological innovation have a dynamic adverse impact on the load capacity factor, whereas energy efficiency has a positive dynamic influence on environmental quality. In addition, the results support the validity of the environmental Kuznets curve hypothesis as the negative effect of economic growth on environmental quality decreases over time. Based on the study findings, policy recommendations are provided for India. Finally, this study utilizing load capacity factor as an indicator for environmental quality will provide new topics in exploring the determinants of environmental degradation.

Digital finance, government intervention, and carbon emission efficiency in China

In accordance with the "dual carbon" objective, China is required to effectively pursue economic expansion and environmental preservation while concurrently enhancing carbon emission efficiency (CEE). This study examines the influence of digital finance on CEE and evaluates the moderating effect of government intervention. The analysis uses panel data collected from 282 cities in China at the prefecture level and above, spanning the period from 2011 to 2021. The findings indicate the following: (1) CEE in China is relatively low, and there are notable regional disparities. Specifically, there is a discernible downward trend in CEE throughout the eastern, central, and western areas. (2) In general, the implementation of digital finance has the potential to enhance the efficiency of carbon emissions. The observed effect is significant in the eastern and central regions but not in the western region. (3) Government subsidies have the potential to amplify digital finance's impact on CEE in the eastern region. Conversely, in the central and western regions, its influence can be increased by environmental regulations. Based on these findings, this study presents recommendations for advancing digital finance, enhancing the targeting and assessment of government subsidies, refining environmental regulations, and encouraging the adoption of green technologies.

Exploring the role of renewable energy and carbon dioxide emissions for sustainable current account balance under the shadow of energy crisis: evidence from OECD countries

Considering the substantial environmental and economic consequences, countries worldwide have placed renewable energy at the forefront of their priorities. While previous empirical research has extensively explored the link between renewable energy and economic growth, this study seeks to address an overlooked aspect by investigating the potential impact of a particular indicator on economic activity. This paper examines the relationship between current account balance and renewable energy in OECD countries using an autoregressive distributive lags (ARDL) model to explore symmetric relationships and the non-linear autoregressive distributive lag model (NARDL) approach and panel vector autoregression (P-VAR) model over the period 1995-2020. The results indicate that there is a cointegrating relationship and that renewable energy consumption has a positive impact on the current account balance in the long term, but no significant impact in the short term. Given that many OECD countries are struggling with deficits, prioritizing bioenergy trade would be beneficial to increase the current account surplus.

Unraveling the non-linear impact of financial development on environmental sustainability: insights from developing countries agreeing the accord

This study delves into the intricate relationship between financial development and environmental sustainability by considering the role of the Paris Agreement in the context of developing countries. By employing advanced econometric techniques method of moment quantile regression (MMQR) and considering a period spanning from 1996 to 2021, this research unravels the non-linear impact of financial development on environmental degradation while considering population and GDP as control variables. The study reveals an inverted N-shaped relationship between financial development and environmental degradation, indicating that environmental degradation (ED) decreases as financial development increases. However, this is followed by a rise in ED before eventually witnessing a further decline. Additionally, the study highlights the positive correlation between GDP and population with ED across all quantiles, with a more pronounced impact observed in higher quantiles. Furthermore, the coefficient of the Paris Agreement demonstrates its effectiveness in decreasing environmental degradation, particularly at higher quantiles of ED. The findings of this study hold practical implications for policymakers, emphasizing the importance of designing and implementing coherent environmental and economic policies in developing countries. This study contributes to understanding the complex dynamics between financial development and environmental sustainability, offering valuable insights for fostering sustainable development pathways.

Incorporating Russo-Ukrainian war in Brent crude oil price forecasting: A comparative analysis of ARIMA, TARMA and ENNReg models

This article investigates the performance of three models - Autoregressive Integrated Moving Average (ARIMA), Threshold Autoregressive Moving Average (TARMA) and Evidential Neural Network for Regression (ENNReg) - in forecasting the Brent crude oil price, a crucial economic variable with a significant impact on the global economy. With the increasing complexity of the price dynamics due to geopolitical factors such as the Russo-Ukrainian war, we examine the impact of incorporating information on the war on the forecasting accuracy of these models. Our analysis shows that incorporating the impact of the war can significantly improve the forecasting accuracy of the models, and the ENNReg model with the inclusion of the dummy variable outperforms the other models during the war period. Including the war variable has enhanced the forecasting accuracy of the ENNReg model by 0.11%. These results carry significant implications regarding policymakers, investors, and researchers interested in developing accurate forecasting models in the presence of geopolitical events such as the Russo-Ukrainian war. The results can be used by the governments of oil-exporting countries for budget policies.

The impact of agriculture production and renewable energy consumption on CO2 emissions in developing countries: the role of governance

Environmental pollution has aggravated the climate change issues posing unusual challenges to the survival and growth of humanity, including extreme weather, loss of species, and sustainability of the ecosystem in developing countries. Unlike previous studies, this paper adds new dimension to the literature by incorporating corruption into agriculture production-environment nexus. This study adds new dimension to the literature by examining corruption, agriculture, and renewable energy on CO2 emissions. The study therefore examines the effects of governance (corruption) and agriculture production on CO2 emissions in 20 countries in Africa from 1990 to 2019. The study employed recent panel econometric approach which accounts for cross-sectional dependence in the variables. The findings of the fixed effect model and panel dynamic ordinary least squares (PDOLS) show that forest and renewable energy consumption decrease CO2 emissions. However, corruption, agriculture production, export, and urbanization escalate CO2 emissions in African countries covered in the paper. Moreover, the Dumitrescu-Hurlin Granger causality indicates a bidirectional causality between agriculture production and CO2 emissions, renewable energy use, agricultural output, and forest. Also, unidirectional Granger causality runs from corruption to forest and agriculture production. On these premises, consented efforts by governments should be made to support good institutions in order to promote good governance to avert pervasive consequences of corruption on the environment.

Does Economic Policy Uncertainty Cause Environmental Pollution? Fresh Evidence From Developed Countries

The industrial revolution has dramatically altered the environment and ecosystem. So many scholars have empirically attempted to reveal the most influential anthropogenic factors on environmental degradation. For this purpose, this study examines the leading determinants of CO2 emissions in the context of economic policy uncertainty (EPU) for 14 developed countries within the framework of the extended stochastic impacts by regression on population, affluence and technology (STIRPAT) environmental model from 1997-2018. For empirical modeling, CO2 emission is treated as the dependent variable, which is a strong proxy for environmental degradation. In addition to the GDP per capita, population density, and energy intensity (a proxy for technology), the basic model is extended to include variables such as EPU, renewable energy, trade openness, globalization, and information and communications technology (ICT) index. While the estimation results by the dynamic conditional correlation (DCC) estimator, which are also supported by robustness analysis, suggest that GDP per capita and energy intensity are the main contributors to emission levels, population density has no significant impact on CO2. Furthermore, while renewable energy (in model 2), trade openness (in model 4), and globalization (in model 6) have negative impacts on CO2 emission, technology (in models 5 and 6) and EPU (in model 6) make marginal contributions to CO2.

Impact of banking development and renewable energy consumption on environmental sustainability in Germany: Novel findings using the bootstrap ARDL approach

This study examines the effects of banking development, economic growth and consumption of renewable energy on carbon dioxide (CO2) emissions and load capacity factor (LCF). Previous empirical studies have assessed the interrelationship between banking development and CO2 emissions; however, these studies have ignored supply-side ecological issues. To overcome this issue, this study evaluates the effect of banking development on LCF, which is considered to be one of the most comprehensive ecological proxies to date, including both biocapacity and ecological footprint (EF). Using the bootstrap autoregressive distributed lag model, the study reveals that renewable energy improves ecological quality in Germany. The results of the investigation demonstrate that the environmental Kuznets curve hypothesis is valid in Germany using CO2 emissions and LCF indicators. Furthermore, this study demonstrates that banking growth and renewable energy in Germany correlate with improved environmental quality. These findings provide policymakers with important insights. In this context, the study advises the banking industry and government authorities to leverage banking expansion to support green energy to achieve the national goal of zero CO2 emissions by 2045.

Examining the Energy-Environmental Kuznets Curve in OECD Countries Considering their Population

This research aims to examine the validity of the Environmental Kuznets Curve (EKC) hypothesis in 37 Organization for Economic Co-operation and Development (OECD) countries over the period from 1960 to 2019. Panel Quantile Regressions (QR) show that for the lower quartile, economic growth does not impact emissions; for the central quartile a U-shaped curve emerges; while for the upper quartile, an N-shaped curve is found. In addition, cointegrating regressions highlight that economic growth, fossil fuel consumption, and population exert a detrimental effect on the environment, while renewable energy consumption reduces carbon dioxide (CO2) emissions. These results are confirmed by panel causality tests since a feedback mechanism is found between CO2 emissions and the remaining series. Furthermore, single-country estimates provide evidence of great variability in the sample.

Investigating the fishing grounds load capacity curve in G7 nations: Evaluating the influence of human capital and renewable energy use

This paper introduces a novel approach to explore marine ecosystem by examining the Fishing Grounds Load Capacity Curve (FGLCC) hypothesis. The study investigates the impact of income on the marine condition in G7 nations from 1970 to 2019 by exploring the U-shaped relationship between income and the Fishing Grounds Load Capacity Factor (FGLCF). This research diverges from previous studies focused solely on the demand side through fishing footprints, as it considers the neglected aspect of the marine supply side. Furthermore, it explores the influence of renewable energies and human capital as indicators inversely related to non-renewable energy use and population on the marine condition. The findings reveal the U-shaped FGLCC hypothesis. Additionally, the results demonstrate that renewable energies and human capital have a positive impact on the marine ecosystem. These outcomes provide valuable insights for decision-makers, enabling them to identify key variables that contribute to the preservation of marine diversity.

Natural gas supply cuts and searching alternatives in Germany: A disaggregated level energy consumption analysis for environmental quality by time series approaches

By considering the search for alternatives against Russia's natural gas supply cuts, this study explores the impact and causality of disaggregated level energy consumption indicators on environmental quality. Hence, the study investigates Germany, which is the leading economy in Europe and highly dependent on Russia's natural gas supply, by using carbon dioxide (CO2) emissions as the environment indicator, including annual data from 1970 to 2021, and applying novel time series approaches. In the empirical examination, Granger causality-in-quantiles (GCiQ), quantile-on-quantile regression (QoQR), and multivariate adaptive regression splines (MARS) are applied as base models while quantile regression (QR) and dynamic ordinary least squares (DOLS) are used for robustness. The empirical findings show that (i) there are causal impacts of disaggregated level energy consumption indicators on CO2 emissions; (ii) renewable energy and hydroelectricity consumption have a decreasing impact, whereas natural gas, coal, and oil energy consumption have an increasing impact on CO2 emissions; (iii) although nuclear energy has been discussed as a potential alternative, nuclear energy does not have a significant impact in decreasing CO2 emissions; (iv) natural gas consumption has an interaction with renewable energy, hydroelectricity, and coal energy consumption; (v) the power of disaggregated level energy consumption indicators on CO2 emissions vary according to quantiles, thresholds, and interactions between energy consumption indicators; (iv) alternative models validate robustness of the results obtained. Thus, the results imply that the most appropriate alternative is coal energy consumption in the short-term and renewable energy consumption in the long-term to compensate for Russia's natural gas supply cuts, whereas nuclear energy consumption is not a real alternative for Germany.

Testing the income-finance-trade-environment nexus based on the ecological load capacity factor: Frequency-domain causality evidence from Nigeria

To ensure sustainable development, it is crucial that the consumption of ecological resources remains within their productive capacity. This study aims to support policy formulation by examining the nexus between income, financial development, trade openness, and the ecological load capacity factor in Nigeria from 1970 to 2021. The results of the Bayer-Hanck and autoregressive distributed lag (ARDL) bounds cointegration tests indicate a long-run equilibrium relationship among the variables. Parameter estimations were conducted using the dynamic ordinary least squares (DOLS) and ARDL model estimators. Both the long-run and short-run results indicate that the ecological load capacity factor has a U-shaped curve with income, thereby validating the load capacity curve hypothesis in Nigeria. The estimated threshold turning points of the curve fall within Nigeria's current range of per capita GDP, which indicates that further increases in income will enhance ecological sustainability. Additionally, the ecological load capacity factor exhibits a negative relationship with financial development and trade openness in the long run. The Breitung-Candelon spectral Granger causality tests reveal that, in the long run, unidirectional causality runs from income and trade openness to the ecological load capacity factor, and bidirectional causality exists in the case of financial development. Furthermore, the tests indicate that none of the causal paths are significant for wavelength periods below four years. Therefore, the study recommends implementing medium-to long-term policy strategies to strengthen the ecological resilience base of the economy.

Do financial inclusion and environmental regulations affect the green economy? An empirical study with a generalized linear model

Reducing carbon emissions is an efficient strategy to cope with global warming, which continues to be a frightening element for environmental protection. However, the energy industry is responsible for a lot of pollution in the atmosphere. To promote a low-carbon growth model, it is essential to endorse financial inclusion and environmental regulations. This research uses panel data from 70 nations, covering 1995 to 2021, to examine the interplay between economic growth, human capital, urbanization, trade openness, and environmental regulation as the primary defining element of efficient energy. Several tests have been used to ensure that the data are typically distributed; these include the cross-sectional dependence test, the KMO test, and the Bartlett test. The generalized linear model and Driscoll-Kraay standard errors have also been implemented for interim and final analysis. Results show that low-carbon energy sources are guaranteed for certain economies when financial inclusion and environmental regulation are implemented. Economic development, urbanization, trade openness, and human capital significantly impact green economic recovery. In light of these findings, policymakers are working to increase energy efficiency and boost their citizens' living standards by promoting financial inclusion and environmental regulation like imposing environmental taxes and governmental laws for industries.

Analyzing the validity of load capability curve: how economic complexity, renewable energy, R&D, and communication technologies take their part in G-20 countries

Intense anthropogenic contamination of the air, water, and soil inspires scholars to examine the causes of pollution and provide remedies to assure environmental sustainability. Therefore, researchers in this study are driven to investigate the causes of the severe air, water, and soil contamination that has resulted from human activity and to offer recommendations for achieving environmental sustainability. This research contributes to the ecological works by suggesting the load capability curve (LCH) hypothesis and using the load capacity factor (LC) to investigate components influencing climatic quality. The LC enables thorough climatic value examination when comparing ecological footprint and biocapacity. Information and communication technologies (INF), development and research (R&D), renewable energy (RE) usage, and disposable income are all examined, considering their effects on the load capacity factor. This analysis utilizes the cross-sectionally augmented autoregressive distributed lag estimator and the Westerlund cointegration on data for the G-20 countries from 1995 to 2018. Empirical evidence suggests that renewables, R&D spending, economic complexity, and INF all benefit environmental quality. This study cannot support the LCH hypothesis, which states that increasing income worsens ecological conditions up to a certain point but then aids in improving environmental quality afterward. Based on the findings, G-20 governments should prioritize environmental policies that boost economic growth, spread renewable energy, prioritize research and development spending, and assist the implementation of green INF infrastructure.

City-level meteorological conditions modify the relationships between exposure to multiple air pollutants and the risk of pediatric hand, foot, and mouth disease in the Sichuan Basin, China

Background

Several studies have examined the effects of city-level meteorological conditions on the associations between meteorological factors and hand, foot, and mouth disease (HFMD) risk. However, evidence that city-level meteorological conditions modify air pollutant-HFMD associations is lacking.

Methods

For each of the 17 cities in the Sichuan Basin, we obtained estimates of the relationship between exposures to multiple air pollutants and childhood HFMD risk by using a unified distributed lag nonlinear model (DLNM). Multivariate meta-regression models were used to identify the effects of city-level meteorological conditions as effect modifiers. Finally, we conducted subgroup analyses of age and sex to explore whether the modification effects varied in different subgroups.

Results

The associations between PM2.5/CO/O3 and HFMD risk showed moderate or substantial heterogeneity among cities (I 2 statistics: 48.5%, 53.1%, and 61.1%). Temperature conditions significantly modified the PM2.5-HFMD association, while relative humidity and rainfall modified the O3-HFMD association. Low temperatures enhanced the protective effect of PM2.5 exposure against HFMD risk [PM2.5 <32.7  μg/m3 or PM2.5 >100  μg/m3, at the 99th percentile: relative risk (RR) = 0.14, 95% CI: 0.03-0.60]. Low relative humidity increased the adverse effect of O3 exposure on HFMD risk (O3 >128.7 μg/m3, at the 99th percentile: RR = 2.58, 95% CI: 1.48-4.50). However, high rainfall decreased the risk of HFMD due to O3 exposure (O3: 14.1-41.4  μg/m3). In addition, the modification effects of temperature and relative humidity differed in the female and 3-5  years-old subgroups.

Conclusion

Our findings revealed moderate or substantial heterogeneity in multiple air pollutant-HFMD relationships. Temperature, relative humidity, and rainfall modified the relationships between PM2.5 or O3 exposure and HFMD risk.

Role of natural gas and nuclear energy consumption in fostering environmental sustainability in India

This paper investigates the role of nuclear energy in promoting ecological sustainability in India, focusing on three ecological indicators: ecological footprint (EF), CO2 emissions (CO2), and load capacity factor (LF). In addition to nuclear energy, the study considers the influence of gas consumption and other drivers of ecological sustainability using data spanning from 1970 to 2018. The analysis also takes into account the impact of the 2008 global financial crisis on the model, employing the autoregressive distributed lag (ARDL) and frequency domain causality approaches to assess the relationships. Unlike previous studies, this research evaluates both the Environmental Kuznets Curve (EKC) and load capacity curve (LCC) hypotheses. The ARDL results support the validity of both the EKC and LCC hypotheses in the Indian context. Furthermore, the findings reveal that nuclear energy and human capital contribute positively to ecological quality, while gas consumption and economic growth have a negative impact on ecological sustainability. The study also highlights the increasing effect of the 2008 global financial crisis on ecological sustainability. Additionally, the causality analysis demonstrates that nuclear energy, human capital, gas consumption, and economic growth can serve as predictors of long-term ecological sustainability in India. Based on these findings, the research presents policy recommendations that can guide efforts towards achieving SDGs 7 and 13.

Links between renewable and non-renewable energy consumption, economic growth, and climate change, evidence from five emerging Asian countries

One of the greatest challenges facing humanity in the current millennium is the need to mitigate climate change, and one of the most viable options to overcome this challenge is to invest in renewable energy. The study dynamically examines the links between renewable energy consumption, non-renewable energy consumption, climate change, and economic growth in five emerging Asian countries during the period 1975-2020. Variables selected in the model have long-term cointegration, as explored by the Pedroni cointegration test and the Westerlund cointegration test. The long-term estimated parameters of the augmented mean group (AMG) method show that renewable energy consumption significantly reduces climate change, while non-renewable energy consumption significantly promotes climate change. The results also show that GDP, investment in transport infrastructure, and urbanization can significantly contribute to climate change in selected emerging Asian countries. Moreover, the results validate the inverted U-shaped EKC hypothesis for emerging Asian economies. Country-specific analysis results using AMG estimates shows that renewable energy consumption reduces climate change in selected emerging Asian countries. Non-renewable energy consumption and investment in transport infrastructure have had significant progressive impacts on climate change in all countries. Urbanization contributes significantly to climate change, with the exception of Japan, which does not have any significant impact on climate change. GDP contributes significantly to climate change in all countries; however, GDP2 has significant adverse effects on climate change in India, China, Japan, and Korea, validating the inverted U-shaped EKC assumption for all countries except Bangladesh. Moreover, the Dumitrescu and Hurlin causality test confirmed a pairwise causal relationship between non-renewable energy consumption and GDP, supporting the feedback hypothesis. The results suggest that the best option for climate change mitigation in selected emerging Asian countries is to transition from non-renewable to renewable energy sources.

Testing the impact of renewable energy and oil price on carbon emission intensity in China's transportation sector

As the largest carbon emitter in the world, with its transportation sector contributing the largest shares of its emission, the need for a low-carbon transition economy has become a policy agenda for China because in order to reach carbon neutrality by 2050, lowering the intensity of carbon emissions in the transportation sector will be crucial. In this regard, we used the "bootstrap autoregressive distributed lag model" to explore the impact of clean energy and oil prices on the intensity of carbon emissions in China's transportation sector. The study found that an increase in oil prices decreases the intensity of carbon emissions in the short and long run. Similarly, an increase in the level of renewable energy and economic complexity declines the intensity of carbon emissions in the transportation sector. On the contrary, the research demonstrates that non-renewable energy contributes positively to carbon emission intensity. Therefore, the authorities must promote green technology to neutralize the transportation system's detrimental effects on China's environmental quality. The implications for successfully promoting carbon emission intensity mitigation in the transportation sector are examined in the conclusion.

Do financial development and renewable energy shocks matter for environmental quality: evidence from top 10 emitting emissions countries

Creating a reliable energy supply, ecological quality, and economic development has become a global effort. Finance is at the center stage ecological transition to low-carbon emission. Against this backdrop, the present work analyses the impact of the financial sector on CO₂ emissions using data from the top 10 emitting emissions economies from 1990 to 2018. Using the novel method of moments quantile regression, the findings illustrate that renewable energy usage enhances ecological quality while economic growth lowers it. The results also affirm that financial development is positively linked with carbon emission in the top 10 emitting emissions economies. These results can be explained by the fact that financial development facilities offer low borrowing rates with less restrictions for environmental sustainability projects. The empirical findings of this study highlight the necessity for policies that boost the proportion of clean energy consumption in the top 10 polluting nations' overall energy mix to reduce carbon emissions. It follows that the financial sectors in these nations must invest in cutting-edge energy-efficient technology and clean, green, and environmentally friendly initiatives. This trend will increase productivity, improve energy efficiency, and reduce pollution.

How institutional quality and renewable energy interact with ecological footprints: do the human capital and economic complexity matter in the Next Eleven nations?

Changes in the economy and human conduct have contributed to one of today's most urgent challenges: environmental pollution. This study's overarching objective is to evaluate the following Next Eleven nations (N-11) ecological footprints (EF) with their natural resources (NR), economic complexity (EC), renewable energy (RE), and foreign direct investment (FDI). The data from 1995 to 2018 are used with the panel data estimations. The complexity of an economy is found to influence the EF. For this purpose, the cross-sectional autoregressive distributed lag method is appropriate. The analysis shows that a higher degree of economic complexity was associated with a larger ecological impact. Moreover, this correlation was the highest among all the variables considered. However, the consumption of natural resources and the economies' complexity enhance environmental conditions. The key recommendation from the study's conclusions is to improve R&D activities to build environmentally friendly technology and clean energy infrastructures and to change to a clean industry pattern. Meanwhile, strategic initiatives are offered to legislators depending on the stability of institutional quality.

Do banking sector development, economic growth, and clean energy consumption scale up green finance investment for a sustainable environment in South Asia: evidence for newly developed RALS co-integration

Concern about climate change is spreading around the globe. The urge to comprehend the environmental effects and take action is sharply rising. Regarding this, the banking industry has a great chance to offer a solution in terms of green financial solutions and can meet the needs of carbon-conscious organizations to combat and defend our planet. Therefore, in light of this, according to the greatest understanding of the authors, this is the first study to investigate the role of banking sector development, economic growth, and clean energy consumption in scaling up green finance investment in South Asian nations, taking carbon emissions, foreign direct investment, remittances, inflation, and trade openness as control variables. This study uses a novel residual augmented least squares-Engle and Granger (RALS-EG) co-integration to test the long-term link and the quantile autoregressive distributed lag (QARDL) econometric approach to extract the association across the quantiles (q0.05-q0.95) for the period 2000-2020. The outcomes of QARDL show that banking sector development, economic growth, clean energy, carbon emissions, foreign direct investment, remittances, and trade openness play a positive role in attracting green finance in the long term. However, only inflation has a negative influence on scaling up finance in South Asian nations. Therefore, the concerned authorities (government, central banks, environmentalists, and policymakers) are urged to implement green finance policies and strategies as suggested and recommended by the results of this study.

The potency of natural resources and trade globalisation in the ecological sustainability target for the BRICS economies

The BRICS nations have yet to significantly contribute to achieving Sustainable Development Goals (SDG) 7 and 13. Dealing with this problem might necessitate a policy shift, which is the main topic of this research. Therefore, the current study scrutinizes the interrelationship between natural resources, energy, trade globalisation and ecological footprint using panel data from the period between 1990 and 2018 for the BRICS nations. To assess the interrelationship between ecological footprint and its determinants, we used the Cross sectional autoregressive distributed lag (CS-ARDL) and common correlated effects. mean group (CCEMG) estimators. The findings show that economic progress, and natural resources lessen ecological quality, while renewable energy and trade globalization improves ecological quality in the BRICS nations. Based on these results, the BRICS nations need to upgrade their use of renewable energy sources and improve the structure of their natural resource endowments. Furthermore, trade globalisation necessitates immediate policy responses in these nations since it reduces ecological damage.

The role of environmental protection expenditures and renewable energy consumption in the context of ecological challenges: Insights from the European Union with the novel panel econometric approach

In line with the United Nations' sustainable development goals (SDGs), countries are taking action to achieve their carbon reduction goals. Because countries have limited financial resources, it is important for carbon reduction policies that public expenditure is used effectively. Researchers have neglected to probe the environmental quality in European Union countries by considering environmental protection expenditure and renewable energy consumption. This study expands the literature by investigating the impact of renewable energy consumption and environmental protection expenditure on the load capacity factor, which considers both the supply and demand directions of the environment. Hence, this work contributes to the SDG 7 (affordable and clean energy), SDG 6 (clean water and sanitation), and SDG 15 (life on land) targets of European Union-22 countries. The study uses the CS-ARDL approach, which considers cross-sectional dependence, endogeneity, and heterogeneity. Empirical analysis showed that environmental protection expenditure is insufficient for European Union economies. In addition, renewable energy consumption contributed to environmental quality. Based on the outcomes, European Union countries should allocate larger budgets from their general budgets for environmental protection. Policies that can attract the attention of the private sector and not just the public sector should be implemented.

Assessing the role of the insurance market and renewable energy in the load capacity factor of OECD countries

In the empirical literature, few studies assessed the influence of the insurance market on carbon emissions. However, the effects of insurance markets on the load capacity factor (LCF) have been ignored. In this regard, the objective of the current work is to assess the potential impact of the insurance market on environmental sustainability in 27 OECD countries from 1990 to 2018 based on the LCF, which implies the strength of a state to enhance the population based on the current lifestyle. The present work employed the novel Method of Moments Quantile Regression (MMQR). This model is the prime and correct technique to better understand the association between the insurance market and the LCF across heterogeneous quantiles and to yield more robust empirical outcomes. The MMQR findings indicate a negative interaction between the insurance market and the LCF. In other words, the insurance sector has a powerful influence on economic activities and investments, such that insurance activities lead to an increase in the level of energy utilization, and thus have a negative influence on ecological sustainability. In contrast, the findings illustrate a positive and considerable association between renewable energy consumption and LCF. Based on the overall outcomes, it is suggested that OECD countries should focus on policies that encourage the use of renewable energy rather than incentivizing the insurance market. OECD country governments should also support green insurance activities to minimize the environmental damage of the insurance market.

Quantile causality and dependence between renewable energy consumption, WTI prices, and CO2 emissions: new evidence from the USA

This study investigates the Granger causal interplays between renewable energy consumption, WTI crude oil prices, and CO₂ emissions in the USA using monthly data between January 1986 and May 2022. The study applies quantile-based techniques, namely, the quantile unit root test developed by Galvao (2009), the quantile cointegration test proposed by Xiao (2009), and the novel Granger causality-in-quantiles test suggested by Troster (2018). The results suggest that the series display a unit root across different quantiles and that the cointegration relationships exhibit heterogeneous behavior across quantiles. Regarding the causal linkages, the findings show: (i) a unidirectional causality from renewable energy consumption to oil prices, mainly at the lowest or highest quantiles of the distribution, (ii) a bidirectional causality between oil prices and CO₂ emissions mainly in the middle and extreme quantiles, but there is evidence of causality from oil prices to CO₂ emissions across the quantiles than in the reverse direction, and (iii) a unidirectional causality from renewable energy consumption to CO₂ emissions at the lowest to medium and the highest quantiles. These findings have important implications for policy-makers.

Insights from BRICS-T economies on the impact of human capital and renewable electricity consumption on environmental quality

This paper evaluates the impact of electricity consumption from renewable and nonrenewable sources on the load capacity factor for BRICS-T nations using data from 1990 to 2018. The paper used linear and nonlinear autoregressive distributed lag (ARDL) approaches to explore these associations. The results of the Westerlund co-integration show long-run co-integration between load capacity factor and the independent variables. The results show that renewable electricity energy and human capital contribute to the sustainability of the environment, while electricity consumption, economic growth, and industrialization impede environmental sustainability. Similarly, the nonlinear effect of renewable electricity energy on LCF shows interesting findings. The positive (negative) shift in renewable electricity energy increases ecological sustainability in the BRICS-T nations. Furthermore, the Dumitrescu Hurlin panel causality gives credence to both linear and nonlinear ARDL results. The study suggests policy recommendations based on these results.

The effect of energy prices, energy losses, and renewable energy use on CO2 emissions in energy-importing developing economies in the presence of an environmental Kuznets curve

In this study, energy losses, energy prices, and the relationship between green energy and environmental quality are investigated for 15 energy-importing emerging economies. In addition, the validity of the environmental Kuznets curve is tested in this study. Autoregressive Distributed Lag (ARDL) approach based on panel dataset, related intermediate estimators including PMG, MG, and DFE were used as a method. In addition, FMOLS and DOLS estimators were used for robustness testing in the study. According to empirical findings, the environmental Kuznets curve is valid in energy-importing emerging economies. In addition, green energy use and energy prices have a reducing effect on CO₂ emissions. However, energy losses increase CO₂ emissions. While the long-term results of the variables were similar, the short-term results were mixed. This situation is attributed to different economic growths in energy-importing developing economies, the share of energy resources in total energy resources, and energy-efficient technologies in the energy field. The fact that these variables have never been investigated for this economy group makes the study different.

Analyzing the co-movement between CO2 emissions and disaggregated nonrenewable and renewable energy consumption in BRICS: evidence through the lens of wavelet coherence

This study investigates the time-frequency nexus of carbon dioxide (CO₂) emissions with economic growth, nonrenewable (i.e., coal, natural gas, and oil), and renewable (i.e., hydro and geothermal) energy consumption. In this context, BRICS countries (namely, Brazil, Russian Federation, India, China, and South Africa), which are leading emerging countries, are included, and quarterly data from 1990/Q1 to 2019/Q4 is used. The study employs the wavelet coherence (WC) approach to explore the co-movement between the variables at different frequencies. The empirical results show that (i) there is a strong and positive co-movement between CO₂ emission and economic growth; however, it is weak for Russia and South Africa in the medium and long-term; (ii) coal energy consumption is strongly and positively co-moved with CO₂ emission for all BRICS countries; (iii) natural gas energy consumption is strongly and positively co-moved with CO₂ emissions in Brazil, India, and China; however, it is weakly and positively co-moved in Russia and South Africa; (iv) oil energy consumption is strongly and positively co-moved with CO₂ emissions in Brazil, India, and China; however, it changes a bit for Russia and South Africa; (v) hydro energy consumption is weakly and positively co-moved with CO₂ emissions in general, whereas country-based results vary; (vi) geothermal energy consumption is also similar to hydro energy consumption. Thus, the WC results highlight the strong co-movement of economic growth and nonrenewable energy consumption with CO₂ emissions, whereas renewable energy consumption has a relatively lower co-movement. Based on the results, policy implications are also discussed for BRICS countries.

Climate change, insurance market, renewable energy, and biodiversity: double-materiality concept from BRICS countries

The threat of biodiversity loss and mass extinction of species with an aftermath will shape all lives now and those to come. In this context, recent empirical studies illustrate various drivers of biodiversity for better environmental quality; however, the impact of the insurance market has not been thoroughly examined. Likewise, the possible non-linearities between biodiversity and its determinants are ignored in the current empirical literature for BRICS economies. Therefore, this work is the first to explore the effect of the insurance market, climate change, and renewable energy on biodiversity in BRICS economies using an advanced method of the non-linear autoregressive distributed lag (NARDL) method. The findings illustrated that a decline in the insurance market alleviates biodiversity loss and stimulates environmental quality. In contrast, an increasing insurance market augments biodiversity loss and negatively affects ecological quality. Furthermore, the findings uncovered that carbon emissions are detrimental to environmental quality. Lastly, the results report that reducing the level of renewable energy worsens biodiversity loss while boosting renewable energy utilization declines biodiversity loss. The policymakers and regulatory authorities in the BRICS should adopt the risk-based approach proposed by the network of greening the financial system (NGFS) to tackle the dilemma of double materiality between financial institutions and biodiversity.

Can financial globalization and good governance help turning emerging economies carbon neutral? Evidence from members of the BRICS-T

Since turning carbon neutral is regarded as a major macroeconomic agenda worldwide, this study examines whether financial globalization and good governance can help Brazil, Russia, India, China, South Africa, and Turkey in achieving carbon neutrality. Considering the period of analysis from 2000 to 2020 and utilizing robust econometric methods, it is observed that the environmental consequences vary across different components of financial globalization. In particular, the results validate the pollution haven hypothesis by confirming the carbon emission-boosting effect of de facto financial globalization indicators. In contrast, the pollution halo effect hypothesis is verified by the finding of the carbon emission-abating effect of de jure financial globalization indicators. Besides, promoting good governance is evidenced to impose carbon emission-mitigating impact in the long-run. The findings also authenticate the existence of the Environmental Kuznets Curve (EKC) hypothesis for the emerging countries of concern. Finally, for both the short and long runs, it is found that the non-renewable to renewable energy transition contributes to lower discharges of carbon dioxide, while urbanization results in the amplification of the carbon emission figures. Considering these critically important findings, it is necessary for these countries to impose restrictions on the influx of unclean foreign direct investment, facilitate and ease the investment process for foreign investors for investing in environment-friendly projects, promote good governance, and adopt green economic growth and sustainable urbanization policies by developing their respective renewable energy sectors.

Role of country risks and renewable energy consumption on environmental quality: Evidence from MINT countries

This study focuses on uncovering the effect of country risks and renewable energy consumption on environmental quality. In this context, the study examines Mexico, Indonesia, Nigeria, and Turkey (MINT) nations; takes economic growth, trade openness, and urbanization into account; includes data from 1990 to 2018; applies cross-sectional autoregressive distributed lag (CS-ARDL) as the main model while common correlated effects mean group (CCEMG) and augmented mean group (AMG) for robustness checks. The empirical results show that (i) economic growth, political risk, urbanization, and trade openness contribute to an increase in ecological footprint; (ii) economic and financial risks as well as renewable energy use have a positive influence on environmental quality; (iii) a unidirectional causality exists from economic risk, financial risk, political risk, economic growth, urbanization, and trade openness to the ecological footprint: (iv) the validity of the EKC hypothesis for the MINT economies is verified; (v) the robustness of CS-ARDL results are validated by CCEMG and AMG approaches. Based on these results, policymakers should promote a sustainable environment to lessen the ecological footprint. Additionally, governments should firmly support investments in green technology as well as economic and financial stability to boost energy efficiency and promote the adoption and usage of energy-saving products.

Are the impacts of renewable energy use on load capacity factors homogeneous for developed and developing nations? Evidence from the G7 and E7 nations

Both developed and underdeveloped economies worldwide are now more concerned than ever in respect of achieving environmental sustainability. Accordingly, the majority of the global economies have ratified several environment-related pacts to facilitate the tackling of global environment-related problems. Although these problems are assumed to be addressed using diverse mechanisms, limiting the use of fossil fuels has often been recognized as the ultimate enabler of environmental sustainability. Against this backdrop, this study aims to assess the environmental impacts associated with higher renewable energy use, controlling for economic growth and population size, in the context of the G7 and E7 countries using data from 1997 to 2018. Moreover, instead of using the traditional environmental quality proxies, this study tries to proxy environmental degradation with the load capacity factor levels of the countries of concern. The long-run associations among the study's variables are confirmed by outcomes generated from the cointegration analysis. Besides, regression analysis highlighted that integrating renewable energy into the energy systems while withdrawing from the use of fossil fuels can help to improve environmental quality by increasing the load capacity factor levels. In contrast, economic growth and population size expansion are evidenced to impose environmental quality-dampening impacts by reducing the load capacity factor levels. However, the findings, in the majority of the cases, are seen to differ across the groups of the G7 and E7 countries, especially in terms of the variations in the magnitudes of marginal environmental effects over the short and long run. Lastly, the causality analysis confirms the directions of the causal relationships among the variables of concern. Based on these results, a couple of policy interventions are recommended for improving environmental quality in the G7 and E7 countries.

Role of energy consumption and trade openness towards environmental sustainability in Turkey

The growth of financial services has been critical in Turkey's pursuit of economic growth objectives throughout the last two decades. Nevertheless, it cannot be denied that it has a negative impact on environmental quality. Based on this, in the current paper, the effect of energy use, trade openness, and financial development on the load capacity factor (LCF) is explored for Turkey between 1965 and 2018. In doing so, a series of quantile approaches such as quantile cointegration (QC), quantile-on-quantile regression (QQR), nonparametric causality-in-quantiles (NCQ), and quantile regression (QR) are used. The results generated from the QQR and also validated by the QR reveal that in the majority of the quantiles, primary energy use, trade openness, and financial development impact the LCF negatively. These results suggest that primary energy use, trade openness, and financial development damage environmental quality. Furthermore, the findings gathered from the quantile causality disclose that all primary energy use, trade openness, and financial development can forecast LCF in the majority of the quantiles. Based on the research outcomes, policies, which may aid to solve the damaging environmental effects of the primary energy use, trade openness, and financial sector development in Turkey are recommended.