This research measures the relationship between green innovation and the performance of financial development by using an econometric estimation during the year of 2000 to 2018 in 28 Chinese provinces. It is intended to explore the relative role of green technological innovation in driving green financial development in the west and central China, as well as how it influences economic growth in these regions. Ordinary least square (OLS) framework was utilized in mainland China to perform empirical studies by using an econometric estimation. This study claims that China has adopted research-based education system, while those for economic growth and expenditure in the regions while the innovation parts results shows that the tertiary education were 12.42% and 13.53% versus the 10.50% and 10.6% in the eastern area. The research-based education increases the patents in green innovation and boosts the environmental policy. The financial development led to green technological development and innovation. Green innovation and financial development decrease the emissions, and it is apparent that as environmental regulations stimulate technical development, the superiority of human resources increases. The findings indicate that green financing reduces short-term lending, thus limiting clean energy overinvestment, while the long-term loans have little impact on renewable energy overinvestment, and the intermediary effect is unmaintainable. Meanwhile, the green financial growth will reduce renewable energy overinvestment and increase renewable energy investment productivity to certain amount.

The economic and environmental aspects of energy production have become important due to the increasing complexity energy sector and envoirnmental pollution, warranting to test the connection between financial imbalances, energy prices and carbon emission. The study aims to test the impact of vertical fiscal imbalances (VFI) on energy prices and carbon emission trends by considering the dual-perspectives of environmental regulation and industrial structure. The empirical outcomes indicated that vertical fiscal imbalances limited the environmental quality of Pakistan. Furthermore, VFI also caused environmental degradation by affecting industrial structure. VFI inhibits the intensity of environmental regulation, promotes the upgrade of industrial structures, both of which cause additional carbon emissions. The study suggest to energy ministries and energy regulation offices to revisit the machinism of energy prices determination and revised machanisim should provide a user-friendly assessment to understand the actual costs associated with the rising concern of environmental pollution. By this, envoirnmental protection maximization and optimal energy conservation is expacted to increase. Based on empirical findings, the study extends the suggestion that vertical fiscal imbalances should be considered an active indicator by the key policy makers and other stakeholders for energy prices determination and environmental quality upgradation.

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The study estimates the long-run dynamics of a cleaner environment in promoting the gross domestic product of E7 and G7 countries. The recent study intends to estimate the climate change mitigation factor for a cleaner environment with the GDP of E7 countries and G7 countries from 2010 to 2018. For long-run estimation, second-generation panel data techniques including augmented Dickey-Fuller (ADF), Phillip-Peron technique and fully modified ordinary least square (FMOLS) techniques are applied to draw the long-run inference. The results of the study are robust with VECM technique. The outcomes of the study revealed that climate change mitigation indicators significantly affect the GDP of G7 countries than that of E7 countries. The GDP of both E7 and G7 countries is found depleting due to less clean environment. However, green financing techniques helps to clean the environment and reinforce the confidence of policymakers on the elevation of green economic growth in G7 and E7 countries. Furthermore, study results shown that a 1% rise in green financing index improves the environmental quality by 0.375% in G7 countries, while it purifies 0.3920% environment in E7 countries. There is a need to reduce environmental pollution, shift energy generation sources towards alternative, innovative and green sources.The study also provides different policy implications for the stakeholders guiding to actively promote financial hedging for green financing. So that climate change and envoirnmental pollution reduction could be achieved effectively. The novelty of the study lies in study framework.

This study aims to examine the nexus between green growth and carbon neutrality targets in the context of the USA while observing the role of ecological innovation, environmental taxes, and green energy. For this purpose, data were collected from 1970 to 2015 for all the variables of interest. This research utilized the quantile autoregressive distributed lag (QARDL) method due to its various benefits, such as depicting the causality patterns based on different quantiles for different variables like green growth, ecological innovation, environmental taxes, and renewable energy. The findings through the QARDL method showed that the error correction coefficient was significant and negative with the expected negative sign for the different quantiles. The findings showed a significant and negative impact of green growth, square of green growth, ecological innovation, and environmental taxes in determining the carbon dioxide (CO 2 ) emissions for the USA's economy under the longrun estimation. Meanwhile, the outcome for the short-term estimation confirmed that the past and lagged values of CO 2 emission were significantly and negatively linked with the current and lagged values of CO 2 emission. On the other hand, it was found that green growth and square of green growth, ecological innovation, environmental taxes, and renewable energy played their vital role in reducing haze pollution like PM2.5. Besides, this research also covers the limitations and policy implications.

Due to their different abilities to improve financial growth and improve social development, small and medium enterprises (SMEs) have been referred to as the economy's backbone. Small-and medium-sized enterprises are crucial for both high-and low-income nations' financial development. Customers grow more conscious of their purchase choices, preferences, and envi-ronmental consequences. The financial opportunities for SMEs in the United Arab Emirates to use green innovation methods to address potential obstacles for increasing green goods, processes, and management are examined in this paper; as a result, it is critical to reduce clean technology adoption constraints in small-and medium-sized businesses. To identify significant hurdles, sub-barriers, and ways to overcome impediments to green innovation in the United Arab Emirates, we apply an integrated decision process. Following a detailed literature analysis and the assistance of twelve experts, six primary obstacles, twenty-five sub-obstacles, and strategies to reduce the barriers were identified. Primary and sub-barriers were assessed using the FAHP. The (FTOPSIS) approach was used to rank the strategies. Five SMEs in the United Arab Emirates are putting the suggested integrated decision model to the test. "Financial investment levels 0.646 to 11 percent growth level," according to the FAHP, are the most significant hurdles to SMEs adopting green practices. This research demonstrated a considerable beneficial association between SMEs and financial development and funding in the United Arab Emirates. According to this study, using research methodologies to provide green innovation in SMEs is the best strategy to overcome green innovation and adoption hurdles in small and medium firms and increasing their economics.

This study measures the environmental regulation effect and pattern of carbon emission and energy efficiency through data envelopment analysis and econometric estimation. One of the most important ways to achieve a green transition is promoting technical progress through environmental regulation. Though China has witnessed rapid economic growth over the last two decades, the country can improve it further through adopting sustainable green energy and establishing more energy-efficient industries to strike a good balance between economic and social developments. The oil and carbon dioxide emission perfor-mances form the most important metrics. This study uses panel data from 30 Chinese provinces from 2008 to 2017 to assess the effect of environmental regulation on energy production. The nonradial directional distance function (NDDF) is used to measure the total factor energy efficiency index (TFEEI). The panel system GMM model, which can effectively address endogenous problems and regional variability, is utilized to research the nonlinear relationship between environmental regulations and EEI under various environmental regulations to study it. The findings reveal a considerably modest total average EEI amount for energy-intensive industries, averaging between 0.55 and 0.58, which is way below the ideal value (i.e., 1). Furthermore, the results of the dynamic panel data model revealed a significant U-shaped relationship between China'sEEI andenvironmental regulation. The results show that as the values of market-based environmental regulations (MERs) and command and control environmental regulations (CCERs) exceed the corresponding levels, the impact of environmental regulation on the TFEEI increases gradually. This study will aid policymakers in better understanding the efficacy of different levels of environmental regulations to make more educated decisions.

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