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.
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.
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