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).

Evaluating the role of financial globalization and oil consumption on ecological quality: A new perspective from quantile-on-quantile granger causality.

Global warming has progressed into a pressing global concern, primarily driven by human activities. To address this issue, it is vital to identify the key drivers of ecological quality and develop effective policies in response. Consequently, this study seeks to empirically examine the causal effect of financial globalization, economic growth, economic policy uncertainty, and oil consumption on the load capacity factor (LF) in Brazil. The analysis utilizes quarterly data spanning from 1990 to 2021. In this pursuit, the study introduces an array of quantile-based methodologies, encompassing quantile ADF, PP, and KPSS tests, as well as the innovative Quantile-on-Quantile Granger Causality (QQGC) approach. The QQGC represents a notable advancement beyond traditional quantile Granger causality (QGC) methods, as it accounts for the conditional distribution of dependent and independent variables. This study bridges a critical gap in the existing literature by introducing the QQGC to capture the causal influence of the regressors on LF. The findings derived from the QQGC analysis indicate that financial globalization, economic growth, economic policy uncertainty, and oil consumption significantly predict LF across all quantiles. These results offer valuable insights that can inform the formulation of effective policies and strategies aimed at addressing ecological quality and mitigating the impacts of global warming.

Differential benefit of coal and natural gas efficiency in Denmark: How clean is the environmental-related innovation?

Inspired by Denmark's ambitious renewable energy initiatives and its commitment to achieving a substantial 70 percent reduction in greenhouse gas (GHG) emissions by 2030 and achieving net-zero emissions by 2050, this study delves deeper into examining the roles of energy source efficiency, renewable energy utilization, and environment-related technologies spanning the years from 1990 to 2021. A comprehensive array of wavelet tools, including wavelet coherence, wavelet-based ordinary least squares (WBOLS), Continuous Wavelet Transform (CWT), Granger causality, and wavelet correlation, was employed to dissect these dynamics. The primary findings underscore the potential for enhancing environmental sustainability through these key indicators. For instance, employing the WBOLS method reveals that a percent increase in renewable energy consumption translates into an approximate reduction of ∼0.02%, ∼0.03%, and ∼0.54% in GHG emissions in the short-, medium-, and long-term, respectively. Similarly, improvements in energy efficiency yield remarkable outcomes. A one percent increase in the efficiency of natural gas utilization leads to GHG emission reductions of ∼0.44%, ∼0.19%, and ∼0.83% in the short-, medium-, and long-term, respectively. Moreover, a 1 percent enhancement in coal energy efficiency results in GHG emission reductions of ∼0.23%, ∼0.19%, and ∼0.91% in the short-, medium-, and long-term, respectively. Furthermore, the study indicates that a surge of 1% in innovation through environment-related technologies corresponds to GHG emission reductions of ∼0.56%, ∼0.10%, and ∼0.02% in the short-, medium-, and long-term, respectively. The results are notably substantiated by the CWT Granger causality approach. Considering the somewhat modest impact of innovation on GHG emissions, especially in the long-term, the study recommends a deliberate emphasis on the design and formulation of environmentally-related innovations that prioritize attributes such as reliability, durability, and adaptability.

Moderating role of green innovation and fiscal expenditure towards achieving the Sustainable Development Agenda 2030 at provincial-level in China: policy implication from green total factor productivity.

Amidst resource loss and environmental protection constraints, achieving green development necessitates enhancing green total factor productivity (GTFP) as a means of promoting rational and efficient resource allocation, thereby balancing economic growth and environmental preservation. Meanwhile, literature on the subject matter of GTFP from a sustainability viewpoint is minimal. As a result, this study employs the panel dataset from 30 provinces of China spanning the period 2005 to 2020 and utilizes the method of moments quantile regression (MMQR) developed by Machado and Santos Silva (2019) to analyze the heterogeneous role of green innovation, environmental regulations, and fiscal expenditure on GTFP. Moreover, the controlling variable for this study includes renewable energy and economic growth. Furthermore, this study investigates the heterogeneous combined impact of green innovation and fiscal expenditure (GTE*FSE) on GTFP. The findings of the MMQR reveal that green innovation has a positive impact on GTFP, while fiscal expenditure, environmental regulations, and renewable energy consumption have a negative impact. GTE*FSE has a positive and significant effect on GTFP, indicating that FSE can reinforce and increase the positive impact of GTE on GTFP in the long run. The study also reveals that economic growth has a mixed effect on GTFP, depending on the quantiles. Furthermore, environmental regulation has a significant and negative impact on GTFP, contradicting the Porter hypothesis. Likewise, the robustness of the findings is confirmed by the results of the fully modified OLS (FMOLS) and dynamic OLS (DOLS) estimations, which indicate a similar impact of the determinants on GTFP as observed in the MMQR analysis. This reinforces the validity of the findings and suggests that the observed relationships are robust to different estimation techniques. Furthermore, the findings of the Dumitrescu and Hurlin (D-H) panel causality test reveal significant bidirectional causality between renewable energy consumption and GTFP and fiscal expenditure and GTFP. Policy-makers need to channel a large chuck of their fiscal spending into green innovation so as to boost sustainability.

Neutralizing the surging emissions amidst natural resource dependence, eco-innovation, and green energy in G7 countries: Insights for global environmental sustainability.

The unrelenting surge in global warming in the current era suggests the inevitable need for governments across the globe to embark on policy measures that will help flatten the curve of the surging emissions. Consequently, the concept of carbon neutrality has become a vital policy approach for countries to achieve sustainable development. The present study extends the debates on carbon neutrality by examining the extent to which prominent factors such as natural resource dependence, eco-innovation, and green energy (biofuel and renewable energy) facilitate or hinder strides toward achieving carbon neutral environment in G7 economies. The study considers the additional roles of carbon tax, environmental policy stringency, and financial development in longitudinal data ranging from 1997 to 2019. The verification of the stated hypotheses hinges on a battery of estimators comprising cross-sectional ARDL, common correlated effects mean group, augmented mean group, and panel quantile regression. The empirical findings show that green energy, carbon tax, and environmental policy support the drive towards carbon neutrality by reducing the stock of CO2 emissions. On the other hand, natural resource dependence and financial development hinder the carbon neutrality agenda by escalating the surge in CO2 emissions. Robustness analyses are conducted from the angle of an additional outcome variable and estimation technique of which the results corroborate the empirical regularity of the main findings. Policy implications are derived from the empirical findings.

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.

Technological innovations, renewable energy, globalization, financial development, and carbon emissions: role of inward remittances for top ten remittances receiving countries.

Asides from renewable energy consumption, technological innovation and remittances are mostly ignored as critical tools and resources that can be adopted to ameliorate environmental worries, even when remittances have more considerable resource inflow than official development aids. Based on this information, the current research investigates the implications of technological innovation, remittances, globalization, financial development, and renewable energy on CO2 emissions in top remittances-receiving countries from 1990 to 2021. To obtain reliable estimates, we use a battery of advanced econometric techniques and method of moments quantile regression (MMQR) method. The AMG results suggest that innovation, remittances, renewable energy, and financial development alleviate CO2 emanations, whereas globalization and economic growth worsen environmental sustainability by increasing CO2 emissions. Besides, the MMQR results confirm that renewable energy, innovation, and remittances decrease CO2 emissions across all quantiles. A bidirectional causality exists amid financial development and CO2 emanations, and across remittances and CO2 emissions. However, one-way causality flows from economic growth, renewable energy and innovation to CO2. This study suggests some essential measures for ecological sustainability in light of the findings.

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.

Environmental quality and energy transition prospects for G-7 economies: The prominence of environment-related ICT innovations, financial and human development.

Energy transition and reducing greenhouse gas emissions are fundamental to achieving sustainable development and ensuring a bright and healthy future. To contribute to the empirical literature on these objectives, this study explores the long-term influence of environment-related ICT innovations (EICT) on energy transition and greenhouse gas emissions (GHGE) in G-7 economies for the first time, while considering financial development (FD) and human development (HD). Additionally, the study investigates the moderating role of FD with EICT and HD in energy transition and GHGE. Using a Cross-Sectional Augmented Distributed Lag (CS-ARDL) technique to tackle the issues of cross-sectional dependency and slope heterogeneity, the study evaluated data from 1990 to 2020. The results indicate that EICT, FD, and HD have a significant positive effect on long-term energy transition, and mitigate GHGE in G-7 economies. Furthermore, the influence of EICT and HD on energy transition and GHGE is amplified in the presence of financial development, as evidenced by the moderating effect of FD. Based on these facts, the study suggests various policy measures, such as investing in clean technologies and education, to promote the energy transition and environmental quality in G-7 economies to achieve sustainable development goals.

Formulating sustainable development policies for China within the framework of socioeconomic conditions and government stability.

Improvement in the environmental quality has been seen as a major concern worldwide, and a crucial agenda of the Sustainable Development Goals (SDG's). In this study, we examined the causal impacts of economic growth, financial development, nuclear energy, government stability, and socioeconomic conditions on the environmental quality of China, using quarterly data, covering the period 1984-2018. We used different proxies for environmental quality, i.e., Carbon dioxide (CO2) emissions, ecological footprints, and load capacity factor, and a unique methodology named Fourier quantile causality, recently recommended by Cheng et al. (2021), for the first time in case of China. We find that nuclear energy, and government stability are positively causing the environmental quality, while economic growth, financial development, and socioeconomic conditions are degrading the environmental quality in China, since they are linked with increased income and energy consumption. Furthermore, all the explanatory variables are largely sensitive on different quantiles to affect the environmental quality; however, economic growth is a highly causing environmental degradation. Our study suggests that increasing nuclear energy consumption along with green financial measures that simultaneously support economic growth and socioeconomic conditions can be effective tools for improving environmental quality and realizing the SDGs in China.

Analyzing the nexus between financial risk and economic risk in India: Evidence through the lens of wavelet coherence and non-parametric approaches.

The gravest challenge for economic sustainability is the undetermined growth in the financial and economic risks of the nation, which need to be overcome with adequate measures without compromising economic growth. The uncertainty of economic factors produces fluctuations in the financial sector and makes them more vulnerable. However, the existing literature has not significantly focused on the economic and financial risk challenge for sustainable economic growth. Therefore, to fill the gap, an in-depth study is imperative to explore the association between these risks. To do so, this study incorporates both economic and financial risk to determine how risks are interconnected across time (frequency) and how they are linked by utilizing quarterly data from 1984-Q1 to 2020-Q4 and by applying both the "wavelet power spectrum (WPS)" and "wavelet coherence (WTC)" approaches, to examine the time-frequency dependency of each variable on the other. The findings of WTC revealed that the economic and financial risks have a positive dependency on each other in India at high, medium, and low frequencies. Likewise, the wavelet power spectrum outcomes reflect the high economic and financial risks vulnerability during 1991, 1992, and 1996. In addition, for the robustness check, the study employed both the "quantile regression (QR)" and "quantile-on-quantile regression (QQR)". Both the QQR and QR endorsed the positive association between FR and ER. Hence, our paper is the first research of its kind for the Indian economy, and it extends to the existing literature by examining the link between the two most significant indicators in terms of both time and frequency dependency. The findings in our paper offer excellent perspectives for investors and policymakers to assess prospects for investment and policy changes if necessary.

Asymmetric impact of renewable energy consumption and technological innovation on environmental degradation: designing an SDG framework for developed economy.

Many European nations, including Spain, are having difficulties achieving their Sustainable Development Goals (SDGs) objectives. Resultantly, the current research discusses the development of an SDG framework for Spain, which can be utilized as a model for other EU nations. This research examines whether GDP growth, technological innovation, and energy sources (renewable and non-renewable) have any effect on CO2 emissions utilizing data from 1980 to 2018. The study applied the non-linear ARDL (NARDL) to investigate these interrelations. The outcomes from the NARDL revealed that positive (negative) shocks in renewable energy improve environmental quality in Spain. Furthermore, positive (negative) shocks in technological innovation lead to a decrease (increase) in CO2. Lastly, positive (negative) shocks in energy consumption lead to an increase (decrease) in CO2. The results reveal that Spain is on the right path towards decarburization. This research has important policy ramifications for the policymakers and government of Spain as well as neighbouring countries.

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.

Enhancing environmental quality in Portugal: can CO2 intensity of GDP and renewable energy consumption be the solution?

Despite Portugal's effort to reduce carbon emissions, the country still emits about 1.6% of the European Union's CO2 emissions. Meanwhile, limited empirical studies have been undertaken in the context of Portugal. As a result, this study examines the asymmetric and long-term impact of CO2 intensity of GDP, energy consumption, renewable energy and economic growth on CO2 emissions in Portugal from 1990 to 2019. The nonlinear autoregressive distributed lag (NARDL) is employed to uncover the asymmetric connection. The findings show that there is nonlinear cointegration among the variables. The long-run estimation reveals a positive change in energy consumption positively affects CO2 emissions, while a negative shock in energy consumption has a neutral effect on CO2 emissions. Furthermore, positive shocks of economic growth and CO2 intensity of GDP enhance environmental deterioration by increasing CO2 emissions. Meanwhile, the negative shock of these regressors positively impacts CO2 emissions. In addition, positive shocks in renewable energy enhance environmental quality, while negative shocks in renewable energy increase environmental deterioration in Portugal. Policymakers should focus on reducing per-unit energy usage and CO2 efficiency gains, which would necessitate a significant reduction in CO2 intensity and energy density of GDP.

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.

World pandemic uncertainty and German stock market: evidence from Markov regime-switching and Fourier based approaches.

This study aims to examine the impact of the world pandemic uncertainty index on the German stock market index (DAX index) for the 1996Q1 to 2020Q3 period while controlling real effective exchange rate, industrial production index, and consumer price index. The present study performs the Fourier Augmented Dickey-Fulle Unit Root, Fourier Engle-Granger Cointegration, Bayer-Hanck Cointegration, and Markov switching regression tests. The outcomes disclose that there is a long-run cointegration association between the stock market index and world pandemic uncertainty index, real effective exchange rate, industrial production index, and consumer price index in Germany, indicating that the combination of these factors significantly affects the German stock market index in the long-run. Moreover, in both high and low volatile regimes, the world pandemic uncertainty index and real effective exchange rate negatively affect the German stock market index while industrial production and consumer price indices impact positively.

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.

Do natural resource volatilities and renewable energy contribute to the environment and economic performance? Empirical evidence from E7 economies.

The economies of the emerging seven (E7) are not insulated from the climate change challenges, which is a key concern for most countries. The E7 nations have undertaken part in initiatives to combat climate change, particularly in terms of reducing CO2 emissions from the trajectory of productivity expansion in their countries. It is for this reason that this study examines the impact of resource volatility, renewable energy, and fossil fuel on both economic performance and CO2 emission from 1990 to 2018. The present study used panel quantile regression and Driscoll-Kraay fixed effect-OLS estimators to examine these associations. From model I, the outcome shows that economic performance, natural gas rent, coal rent, and fossil fuel impact CO2 emission positively. Moreover, oil rent, renewable energy, investment in energy, and the interaction between investment in energy and renewable energy also negatively and significantly impact CO2 emission. On the other hand, model II which has economic performance as a dependent variable shows that all the understudy variables have significant positive relations with economic performance. Based on the empirical outcome, policy ramifications are provided.

Re-visiting the resource curse hypothesis in the MINT economies.

Natural resources are extremely important to the economy, particularly in emerging nations such as the MINT (Mexico, Indonesia, Nigeria, and Turkey) nations. To improve their economic performance, such nations put a priority on maximizing the use of natural resources. These natural materials are the basis on which all living creatures rely, and they are the primary motivation behind contemporary production. Therefore, the current research utilizes a dataset spanning the period from 1970 to 2019 to assess the effect of natural resource on economic growth for the MINT nations. The present study uses a unique quantile-on-quantile regression (QQR) approach to assess this interrelationship. Furthermore, we apply the novel quantile causality suggested by Troster (2018), which identifies causality across quantiles. The findings from the QQR reveal that in the majority of the quantiles, the effect of natural resources on economic expansion is positive in Nigeria and Mexico, while it is negative in Indonesia and Turkey. In addition, a feedback causality is found between economic growth and natural resources for Mexico, Indonesia, and Nigeria. Based on the results, it is paramount for policymakers to develop policies or frameworks that promote cleaner energy sources and more effective use of natural resources, which can aid the country's economic growth.

Assessing the environmental sustainability corridor: linking oil consumption, hydro energy consumption, and ecological footprint in Turkey.

Climate change has been a topic of significant discourse and debate among scholars and policy makers for several decades. In recent decades, it has become a major problem for the entire human race. Therefore, the present research evaluates the impact of oil consumption, hydro energy use, population density, and economic growth on ecological footprint in Turkey for the period from 1965QI to 2018Q4. This paper uses the BDS test to assess the nonlinearity of the variables in the pre-estimation analysis. The results of the test reveal that non-linearity occurs in all of the variables used in this study. As a consequence, using traditional linear methodologies would produce erroneous results. Our research uses the quantile techniques (quantile cointegration, quantile causality, quantile-on-quantile regression), which are recently developed nonlinear estimate methodologies to assess these associations. The results from the study reveal that oil consumption, hydro energy use, population density, and economic growth contribute to environmental degradation in Turkey in majority of the quantiles. The Granger Causality in Quantiles result also gives credence to the results. The study proposes policy recommendation based on these results.