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

Impact of sustainable energy, fossil fuels and green finance on ecosystem: Evidence from China

The adoption of sustainable energy has increased as a substitute for petroleum derivatives due to growing concerns about environmental degradation caused by pollution and non-renewable energy sources. This study aims to investigate the impact of sustainable energy, green finance, and fossil fuels on the ecology of China. Instead of using traditional intermediaries like CO2 and EF, we employed the ecosystem habitat index to evaluate the conservation of terrestrial ecosystems. This index measures the extent of habitat destruction, deterioration, and fragmentation. The research demonstrated that implementing ecological power and green finance in China has enhanced the country's ability to safeguard and enhance its ecosystem in the short and long term. Furthermore, the findings suggest that using non-renewable energy sources in China has heightened the risk to biodiversity and the ecosystem. The analysis indicates that prioritizing green funding and renewable energy sources is crucial for policymakers, legislators, and investors to safeguard and enhance ecosystem diversity.

Harnessing the power of AI and IoT for real-time CO2 emission monitoring

Global CO2 emissions have been an essential topic of the environmental discussion. Still, empirical data is needed to support arguments that high-quality government actions could reduce these emissions. By analyzing data from 137 nations from 2000 to 2020, we offer strong evidence that state policies focused on promoting healthy ecosystems, sustainable economic growth, and transcendent legislative changes are capable of decreasing CO2 emissions. Based on our findings, there are essentially three critical institutional factors that need to be improved for environmental policies to be efficient: the concept of law, which protects citizens' intellectual property rights; citizens' speech, which allows them to participate in elections and represent themselves freely, and the management of corruption. Policies aimed at promoting economic growth, lowering oil and gas use, enhancing the usage of green energy by the public and private sectors, and enhancing such institutional factors are all necessary components of a climate-friendly financial strategy.

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.

Can green finance, green technologies, and environmental policy stringency leverage sustainability in China: evidence from quantile-ARDL estimation

Environmental sustainability is an umbrella approach depending on various climatic and economic policies. In doing so, the current study empirically evaluates the role of green finance, eco-innovation, and environmental policy stringency on the ecological footprint in China. To meet the objectives, the novel quantile autoregressive distributed lag (QARDL) approach was employed from 2000 to 2017. The outcomes reveal heterogeneous associations between the proposed variables. Manifestly, the QARDL estimation results demonstrate a positive impact between eco-innovation, green finance, and environmental policy stringency with the ecological footprints of China; however, the extent of the relationship is quantile dependent. The outcomes are further validated through the Wald test of parameter constancy. The bi-direction causality is observed among all variables at several quantiles. The current study offers policymakers helpful suggestions on enhancing the positive effects of environmentally supported innovation, green finance, and stringent environmental policies on the ecosystem.

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.

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.