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The development of a country is inseparable from the material guarantee mainly based on energy, but energy is limited, which may restrict the sustainable development of the country. It is very necessary to accelerate the adoption of programs aimed at switching non-renewable energy sources to ones that are, and giving priority to improving renewable energy consumption and storage capabilities. From the experience of the G7 economies, the development of renewable energy (RE) is inevitable and urgent. The China Banking Regulatory Commission has recently issued a number of directives, such as the "Directives for Green Credit" and "Instructions for Granting Credit to Support Energy Conservation and Emission Reduction," to help businesses that use "renewable energy expand". This article firstly discussed the definition of the "green institutional environment" (GIE) and the construction of the index system. Then, on the basis of clarifying the relationship between the GIE, and RE investment theory, a semi-parametric regression model was constructed to empirically analyze the mode and effect of the GIE. Considering the balance between improving model accuracy and reducing computational complexity, the number of hidden nodes opted in this study is 300 so as to lower the time needed to predict the model. Finally, from the perspective of enterprise scale, the level of GIE played a significant role in promoting RE investment in small and medium-sized enterprises, with a coefficient of 1.8276, while the impact on RE investment in large enterprises had not passed the significance test. Based on the conclusions, the government should focus on building a GIE dominated by green regulatory systems, supplemented by green disclosure and supervision systems, and green accounting systems, and should make reasonable plans for releasing various policy directives. At the same time, while offering full play to the guiding role of the policy, its rationality should also be paid attention to, and the excessive implementation of the policy should be avoided, so that an orderly, and good GIE can be created.

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The growth of green finance is a multifaceted system, including the interaction of three spheres: the economy, the environment, and the finance sector. Spending on education is a singular intellectual contribution to a society's attempts to achieve sustainability through the application of skills, the provision of consultancies, the delivery of training, and the dissemination of knowledge. University scientists sound the first warnings about environmental problems and help lead the charge toward transdisciplinary technological solutions. Researchers are compelled to look into the environmental crisis because it has become a worldwide concern that needs regular examination. In this research, we examine how the GDP per capita, green financing, health expenditure, educational expenditure, and technology in the G7 economies affect the growth of renewable energy (Canada, Japan, Germany, France, Italy, UK, and the USA). The research makes use of panel data from the year 2000 through the year 2020. Long-term correlations between the variables are estimated using the CC-EMG in this study. The study's trustworthy results were determined using a combination of AMG and MG regression calculations. The research shows that the growth of renewable energy is positively affected by green finance, educational spending, and technology but negatively affected by GDP per capita and health expenditure. The growth of renewable energy is also positively affected by the influence of the term "green financing" on such variables as GDP per capita, health expenditure, educational expenditure, and technological advancement. The estimated outcomes also provide significant policy implications for the chosen and other developing economies in scheming a suitable route to a sustainable environment.

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Environmental sustainability is one of the most critical issues that require efficient environmental and economic policies in modern times. Advancements in renewables and green technologies contribute significantly to sustained long-term development without affecting environmental quality. Several studies focus on the association of carbon dioxide emissions (CO2e) with economic variables. However, they ignored the impact of technological innovations and renewable energy consumption on CO2e in developed countries. Therefore, this study examines the relationship between CO2e, energy consumption, gross domestic product (GDP), renewable energy consumption, and technology innovations in G-7 countries by employing cross-sectionally augmented autoregressive distributed (CS-ARDL) lag and wavelet coherence techniques during 1990-2020. The results depict that GDP and renewable energy consumption are inversely related to CO2e. A 1% increase in CO2e will decrease GDP and renewable energy consumption by 0.459 and 0.172% in the long run and by 0.471 and 0.183% in the short run in G7 countries. Technology innovations negatively impact CO2e in the short run while positively influencing it in the long run. Considering the advancements in green technologies in different energy-dependent and manufacturing sectors is crucial for a sustainable environment in the long run. Such initiatives ensure the effective use of energy sources by limiting CO2e in the atmosphere. Moreover, the dynamic common correlated effects mean group model confirms the reliability and effectiveness of the CS-ARDL. The wavelet coherence approach revealed a causality relation between CO2e and technology innovation in Italy, Japan, the UK, and the USA during the study period.

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In the contemporary era, it is evident that consumption-based carbon emissions (CCO2e), adjusted for international trade, are a more accurate and robust measure of environmental pollution than production-based emissions. Therefore, many studies have focused on exploring the determinants of CCO2e; however, the literature could not yet discern environment-related R&D budget (ERRD) and political risk index (PRI) as a new driver. To fill this gap, the current paper aims to divulge the dynamic effects of ERRD and PRI on CCO2e while taking imports, exports, and GDP as control regressors. To do so, the G7 nations' data from 1990 to 2020 is utilized, and several advanced econometric tests and techniques are deployed to tackle the advanced issues (i.e., cross-section dependence, heterogeneity, and endogeneity) in econometrics. The CS-ARDL estimates suggest that PRI and ERRD significantly lessen the environmental quality by disrupting the detrimental effects of CCO2e. Likewise, the rise in exports possesses a negative association with the ratio of CCO2e. However, CCO2e significantly tends to surge on account of an increase in GDP and imports. GDP squared exhibits the negative link with CCO2e, confirming the EKC hypothesis in G7 nations. Besides, the AMG technique and causality test validate the robustness of our findings. In addition, the policies related to CCO2e by authorities will take approximately more than a year to absorb their effects.

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This study probes the environmental consequences of income inequality (INQ) in G7 economies from 1971 to 2015. INQ is captured by four indicators comprising GINI coefficients, Palma ratio, Theil index, and Atkinson index on per capita carbon emission as a proxy for environmental degradation using both fully modified OLS (FM-OLS) and dynamic OLS (D-OLS). The empirical data are subjected to pre-test using cross-sectional dependence (CSD) test and panel unit root and panel cointegration tests. The following results are established. First, the absence of CSD and presence of cointegration is confirmed. Second, positive effects of INQ indices are reported for the panel analyses. Third, the results of country-specific analyses are divergent and mixed among the G7 economies. For instance, positive impacts are reported for Canada, Japan, and the USA and negative for France and Germany; and insignificant impacts are evident in the case of Italy and the UK. Fourth, the effects of other covariates emerge from two directions entailing both positive and negative. While per capita GDP (LGDPPC) and trade openness (OPN) are aligned with the former a prior, per energy use (PEU) and inflation (INF) satisfied the latter. Consequently, embarking on pro-poor programs such as social welfare funds, private initiative support fund, and state intervention aimed at checkmating the excesses of the capitalists is seen as sacrosanct to solving the INQ-pco2 nexus disharmony.

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A genuine concern faced by the present world is global warming. Millions of human and animal lives are at risk due to global warming. Therefore, the subject has gained enormous attention from research and academia around the world. Literature shows that the primary cause of global climate change or global warming is carbon (CO2) emissions. Hence, the role of a reliable carbon emission measurement is important for devising a relevant climate policy to deal with environmental problems. Based on trade-adjusted statistics of carbon emissions, a relevant climate policy response can be provided. Unlike the previous studies, this study examines the asymmetric impact of international trade on consumption-based carbon emissions from 1990 to 2017 in the G7 economies. To get empirical estimates, the study applies second-generation co-integration technique and nonlinear panel autoregressive distributive lag (NPARDL) model for estimating the relevant coefficients. The empirical results show that positive growth of exports significantly decreases consumption-based carbon emissions both in the short and long run, whereas the impact of negative growth of exports is insignificant. For imports, the results show that, over time, positive growth of imports significantly increases consumption-based carbon emissions in the long run, while the impact of negative growth of imports is insignificant. Finally, it is recommended for the policymakers to target the export industries for relevant policy interventions, which are less polluting and can generate other economic benefits as well.

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The debate on ecological matters that relate to the biomass emissions nexus has gained prominence and different scholars have suggested various forms of policy directions to tackle the menace. This study seeks to contribute to this subject by examining the impact of biomass energy use on carbon dioxide pollution in the G7 economies context. Thus, to this end, we employed energy usage and GDP measured as economic growth which adds factors that can influence pollution for annual time-frequency between1995 and 2016 for the case of G7 economies. The present study adds to the extant literature by the adoption of the novel econometric techniques such as the panel cross-section augment ARDL and common correlated estimate mean group (CCEMG) to evaluate the impact of biomass energy on pollutants. The empirical results from all the techniques show that biomass energy consumption significantly and negatively correlates to CO2 emissions meaning that it helps to reduce pollution in the long run. On the other hand, there is a significant positive relationship between energy use and pollutants implying that the primary energy use is not favorable for environmental sustainability over the sampled period. Finally, the results proved that GDP increases CO2 emissions in the long run with respect to the G7 context. Thus, validating the growth-induced pollution hypothesis in G7 blocs. On causality relationship, we observe a unidirectional causal relationship between these variables: biomass and pollutants, pollutants and output, biomass and output, biomass and energy use, and output and energy use. While there was a bidirectional causality between energy use and pollutant, these results suggest policy implication for the G7 countries which indicates that stakeholders should give much attention to technological know-how and energy mix particularly biomass energy which is environmentally friendly as well as more paradigm shift to renewables.

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