Investigating the interrelationship among renewable energy consumption, green finance, agriculture, green technology, industry, and urbanization on CO2 Emissions: Evidence from BRICS-M-A countries

We propose a vector error correction model to explore the causal correlation between green finance, economic growth, and renewable energy consumption from both short- and long-run perspectives to empirically evaluate the efficacy of green finance policies. Based on time-series data from 2000 to 2020, we use the unit root test method to examine time-varying trends and cointegration for time-series data. We find that renewable energy consumption has a negative relationship with emissions but green finance is positively correlated with economic growth. Green finance is the driving factor behind the increasing utilization of renewable energy in China. CO 2 emissions per unit of GDP decreased by 1.077% for every 1% increase in green finance development. Although the share of renewable energy consumption increased by 1%, CO 2 emissions per unit of GDP decreased by 0.55%. Therefore, green finance is significant in decreasing CO 2 emissions; it has a negative impact on CO 2 emissions and the renewable energy sector and must be addressed by financial policy, stability, and long-run sustainability. We categorized green finance, which refers to carbon finance innovations such as trusteeship, to improve market demand and eventually develop industries to expand the number of emission-control industries.

As China transitions towards a green and low-carbon energy system, it is crucial to have the support of green finance. In this study, we explore the effects of synergy and spatial spillovers in the development of green finance and the consumption of renewable energy. By taking a synergistic perspective, we aim to provide new insights for energy structure reform.We use a spatial simultaneous equations model in combination with a three-stage generalized spatial least squares approach, our findings are the following: firstly, there is a positive synergy between the development of green finance and the consumption of renewable energy. Secondly, there are positive spatial spillovers in the development of green finance and the consumption of renewable energy, but the regional interaction effects of green finance development on renewable energy consumption are negative. Furthermore, we observe that the impact of renewable energy consumption on green finance development has been increasing since 2013. However, the reverse relationship is not true, indicating that the renewable energy industry has stabilized and is gaining appeal in financial markets. Our study highlights that the development of green finance can promote an increase in renewable energy consumption through the facilitation of economic growth, green technology innovation, and the upgrading of the industrial structure. We emphasize the importance of regional and industrial coordination to create synergy between green finance development and renewable energy consumption.

This study examines the impact of the digital ecosystem, technological innovations, renewable energy consumption, and financial development on CO₂ emissions in Pakistan. As environmental sustainability becomes a global priority, understanding the role of digital transformation and technological advancements in mitigating carbon emissions is crucial. Using time-series data of 30 years (1994 to 2023) and applying econometric techniques like ARDL, the study explores how digitalization and technological progress influence environmental quality, while also assessing the contribution of renewable energy adoption and financial development in reducing emissions. The findings reveal that a digital ecosystem enhances CO₂ emission in Pakistan due to enhanced energy consumption and production through traditional energy sources. Surprisingly technological innovations also have negative impact on CO₂ emission. In developed countries like Pakistan, technological innovations have positive impact on environment. The possible reason for this negative relation is low investment in R&D and green technologies. Additionally, increased renewable energy consumption significantly reduces environmental degradation. However, the relationship between financial development and emissions is complex, indicating that financial expansion must be aligned with green investment policies. The study highlights policy implications for fostering a sustainable economy through digitalization, clean energy transition, and green financing.

This study aims to reveal the impact of renewable and non-renewable energy consumption on CO2 emissions in Türkiye and the potential to reach the CO2 emission level targeted in the 2030 Paris Agreement. In the first stage, the cointegration relationship was analyzed with the AARDL model approach using annual data for 1965-2022. According to the results of the analysis, in the long run, non-renewable energy consumption increases CO2 emissions, while renewable energy consumption decreases CO2 emissions. In the second phase of the research, three scenarios were prepared for each of renewable and non-renewable energy consumption. For nine scenarios, including combinations of these scenarios, CO2 emissions that may occur until 2030 were estimated using the econometric simulation method. According to the estimation results, the low non-renewable energy consumption and high renewable energy consumption scenario was determined as the scenario that can reduce CO2 emissions the most until 2030. However, even in this case, it is understood that more investment in renewable energy will be required since the 2030 CO2 emission reduction target will not be achieved. Therefore, policymakers need to enact policies to increase incentives for renewable energy generation in both the public and private sectors and take steps to improve the necessary infrastructure.

Symmetric and asymmetric impact of economic growth, capital formation, renewable and non-renewable energy consumption on environment in OECD countries

Objective: The objective of this study is to examine the relationship between green finance and sustainable development in Morocco, focusing on its dual impact on economic growth and environmental preservation during the 2016–2022 perio[1]d. Theoretical Framework: The research is grounded in the theoretical frameworks of green growth and sustainable development, emphasizing the synergies between economic prosperity and environmental sustainability. The concepts of renewable energy consumption and green finance as catalysts for economic and ecological balance are central to the study. Method: A quantitative approach was adopted, employing a correlation matrix and the Granger causality test to analyze the interplay between green finance, GDP growth, and CO2 emissions. Data from 2016 to 2022 were used, capturing Morocco’s progress in renewable energy adoption and green finance initiatives. Results and Discussion: The findings highlight a significant positive correlation between renewable energy consumption, green finance, and economic growth, alongsFDI a reduction in CO2 emissions. The results underscore the strategic importance of green finance in fostering sustainable growth while mitigating environmental impacts. The discussion contextualizes these findings within Morocco’s sustainability agenda, emphasizing the potential for green finance to drive ecological and economic transformation in other emerging economies. Research Implications: This study provFDIs practical insights for policymakers and stakeholders, advocating for expanded green finance frameworks and renewable energy integration to support sustainable development. Originality/Value: By addressing the empirical gap in linking green finance with economic and environmental outcomes, this research contributes tothe literature and offers a roadmap for leveraging financial systems to achieve green growth.

Purpose Green finance aims to promote sustainable financial activities, environmental conservation and ecological balance. This study examines how renewable energy consumption (REN), technological innovation (TEC) and green finance (GRF) influence CO2 emissions in Vietnam from 2000 to 2022. Design/methodology/approach We utilize a novel three-stage methodology including quantile-on-quantile regression, wavelet coherence and wavelet-quantile regression to explore the relationship in the structure of intercorrelation in terms of quantile, time and frequency. Findings The findings show that Vietnam will increase environmental quality for higher green development. Specifically, there is a negative influence of TEC, REN and GRF on CO2 emissions across different quantiles and timescales. Practical implications The study recommends policies that support green development and reduce carbon emissions, such as increasing the use of renewable energy and conducting well-planned research to achieve a carbon-free, sustainable environment. Originality/value This article looks into the effects of GRF, TEC and REN on CO2 emissions in Vietnam. Some studies argue that green development in underdeveloped nations is insufficient to reduce CO2 emissions, thereby limiting the sample to a few advanced economies. Adopting diverse methodologies demonstrates the varied and intricate nature of understanding CO2 drivers. Additionally, our work makes detailed policy implications for Vietnam to meet its net-zero emission target and achieve sustainable development by 2050.

In this study, the relationship between Türkiye’s real gross domestic product, CO2 emission and renewable energy consumption is modelled using machine learning techniques. The data between 2003-2020, the period when renewable energy production and consumption have accelerated, are included in the modelling. First of all, it was tested whether there is a causal relationship between the real gross domestic product, CO2 emission and renewable energy consumption data. Afterwards, a deep learning model was developed in Python programming language by considering the real gross domestic product as the dependent variable while CO2 emission and renewable energy consumption are considered as independent variables. The developed deep learning model has two input nodes, three hidden layers consisting of 100 neurons each, and an output node. In addition, the rectified unit functions are used as nonlinear activation functions in the deep learning network. Based on the standard usage, seventy percent of the data was used as the training data and the remaining thirty percent were employed as the test data. The results of the developed deep learning network and actual gross domestic product data were compared, and it is shown that the developed deep learning network successfully models the relationship between the real gross domestic product, CO2 emission and the renewable energy consumption. The coefficient of determination of the developed model was calculated in Python environment as R2=0.986. This parameter value also indicates that the developed deep learning network model has a good performance for the modelling of the real gross domestic product dependent on the CO2 emission and renewable energy consumption.

Green finance, energy, technology, and fintech are essential drivers of a sustainable environment and the promotion of sustainable development. This study analyzes the causal relationships among green finance, green energy, green technology, and fintech indices. To ensure the reliability of our findings, we utilize daily data from reputable sources such as S&P Green Bond for green finance, S&P Global Clean Energy for green energy, Renewable Energy and Clean Technology for green technology, and S&P Kensho Future Payments for fintech indices. Following our objective, a Vector Autoregressive Regression (VAR) model is constructed first, followed by Granger causality and impulse response analysis. The causality results indicate bidirectional causal relationships between green finance and green energy and green technology, as well as one-way causal relationships from green finance to green technology and from green energy to green technology. Impulse response analysis shows that the green energy index is a significant shock transmitter to the green bond index. In contrast, the green technology index is a significant shock transmitter to the fintech index. The findings suggest that capital support for green finance is vital for promoting green energy and technology and supporting sustainable development.

This study investigates the role of informality in the relationship among renewable and nonrenewable energy consumption, economic growth, and CO2 emissions in a panel of 19 Eastern and South African countries. The empirical strategy exploits the panel generalized method of moments, panel fixed effects models using the Driscoll-Kraay standard errors, panel method of moments quantile regressions, and the Dumitrescu-Hurlin bootstrap panel Granger causality analysis. The results are fourfold. First, nonrenewable energy consumption is positively associated with CO2 emissions, while renewable energy consumption is not. Second, there is a nonlinear ∩ -shaped relationship between economic growth and CO2 emissions, consistent with the environmental Kuznets curve (EKC) hypothesis. Third, the results show a nonlinear ∪ -shaped relationship between informality and CO2 emissions, suggesting that higher informality is associated with lower CO2 emissions up to a certain critical point beyond which further increases in informality precipitate higher CO2 emissions. Fourth, the results show unidirectional causality from CO2 emissions to renewable energy, from CO2 emissions to nonrenewable energy, from informality to CO2 emissions, and feedback causality between GDP growth and CO2 emissions.

Do natural gas and renewable energy consumption lead to less CO2 emission? Empirical evidence from a panel of BRICS countries

Testing environmental Kuznets curve hypothesis: The role of renewable and non-renewable energy consumption and trade in OECD countries

After the Paris Climate Conference (COP21), carbon neutrality and environmental sustainability have become the consensus of many countries. Technological innovation and green finance are the essential factors that can help to realize clean energy transition, carbon emission reduction and climate change mitigation. To investigate the pathways for sustainable development, this study includes innovation and green finance into simultaneous equations models within energy-environment-climate nexus. We examine the dynamic relationships for a sample of 49 countries with green bonds issued for the period 2007–2019. The results confirm that there are bidirectional relationships among renewable energy consumption, environmental pollution and climate change. Innovation can significantly promote renewable energy consumption, reduce CO2 emissions and mitigate climate change. Green finance can effectively alleviate environmental pollution and climate change. Accelerating the development of green finance is the primary motivation for sustainable development. Green finance moderates the relationship between innovation and energy-environment-climate nexus. The positive impact of innovation on renewable energy consumption is enhanced by higher level of green finance. When the development of green finance is high, innovation has a greater negative influence on CO2 emissions, and the impact of innovation on climate change is weakened.

This study examines the relationship between renewable and nuclear energy consumption, carbon dioxide emissions and economic growth by using the Granger causality and non-linear impulse response function in a business cycle in Spain. We estimate the threshold vector autoregression (TVAR) model on the basis of annual data from the period 1970–2018, which are disaggregated into quarterly data to obtain robust empirical results through avoiding a sample size problem. Our analysis reveals that economic growth and CO2 emissions are positively correlated during expansions but not during recessions. Moreover, we find that rising nuclear energy consumption leads to decreased CO2 emissions during expansions, while the impact of increasing renewable energy consumption on emissions is negative but insignificant. In addition, there is a positive feedback between nuclear energy consumption and economic growth, but unidirectional positive causality running from renewable energy consumption to economic growth in upturns. Our findings do indicate that both nuclear and renewable energy consumption contribute to a reduction in emissions; however, the rise in economic activity, leading to a greater increase in emissions, offsets this positive impact of green energy. Therefore, a decoupling of economic growth from CO2 emissions is not observed. These results demand some crucial changes in legislation targeted at reducing emissions, as green energy alone is insufficient to reach this goal.

Exploring the effects of economic growth, and renewable and non-renewable energy consumption on China’s CO2 emissions: Evidence from a regional panel analysis