Green finance and carbon emissions in the EU: moderating role of biofuels and technology

Carbon emission reduction is critical to realizing China’s “Carbon Peak” and “Carbon Neutrality” goals. Green finance plays an essential role in accomplishing carbon emission reduction. Given the importance, this study builds and tests a causal model that specifies the direct and indirect interconnection of green finance and carbon emission reduction of the Yangtze River Economic Belt in China from 2006 to 2019. The received data reports are from national and local statistical offices. The unit root test and multicollinearity test proves the data are stationary and free from multicollinearity, which builds a foundation for constructing a regression model. The Hausman test provides the evidence for the selection of time and individuals double fixed effects. The stepwise regression model explains the mediation role of technological innovation in the green finance and carbon emission relationship which confirms the rationality of the theoretical assumptions. The spatial Durbin model (SDM) is applied using Stata version 16 for analysis purposes to measure the strength of the relationships which exist among the studied variables. Through the endogeneity test, the reliability of the model results has been demonstrated. The empirical outcomes indicate that it is the Yangtze River Economic Belt that has existed a significant spatial effect of reducing carbon emission, and the various provinces have shown mutual restraint effects of carbon emission. The findings show that green finance has a prominent adverse direct impact on carbon emission, but the spillover effect of green finance on neighboring provinces are seemingly insignificant. A green finance development alliance, green financial reform, and innovation pilot zone should be promoted. The generalizability of the study offers valuable insights for imminent researchers. The research findings could be beneficial for policymakers.

This study investigates the nexus between green financing (GB) and carbon emissions across 29 countries distributed worldwide with full data on green financing measured as the sum of bonds issued for the period 2018–2021. GDP per capita, population, and environmental expenditure (EP) are used as control variables in the study. An interaction term between GB and EP is also included in the study. This study utilized the Panel Robust Fixed Effect Model (PRFEM) to investigate the nexus between green financing and carbon emissions and how EP enhances the effectiveness of green financing in reducing carbon emissions. The study concludes that green finance is effective in reducing carbon emissions; this relationship remains the same regardless of country-specific factors such as the GDP per capita, EP, and population. Increases in environmental protection (EP) expenditure promote the effectiveness of green financing in reducing carbon emissions. This study recommends policies that promote the green transition including tax exemptions for investors in green bonds, the enactment of rules and regulations that require companies and institutions to provide information about their green projects, and lastly, the establishment of standards that help in measuring the impacts of the projects that are being funded through green bonds. The synergic potential between EP and green financing justifies the need for policies supporting the collaboration of public and private collaboration in attracting green capital flows from the private sectors. By enhancing the green bond market, these steps will contribute toward realizing low carbon economy goals by channeling funds to sustainable and environmentally friendly projects.

The driving force of carbon emissions reduction in China: Does green finance work

As an important way for China to achieve its dual-carbon goal, green finance has become the foundation for promoting high-quality economic development in China. In order to clarify the mechanism of green finance on carbon emissions, this paper puts green finance into the economic model and deduces the relationship between green finance and carbon emission reduction. This paper is based on the panel data of 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2008 to 2019, using the individual fixed effect model, dynamical model, mediator model, and SDM model to study the impact of green finance on carbon emissions and its impact path of upgrading of the industrial structure and the development of science and technology based on the measurement of the green finance development index of each province by the entropy method. The findings show that the development of green finance can reduce carbon emission significantly, which can be sustained until at least the third phase and generates spatial spillover effects; regional heterogeneity analysis finds that the development of green finance shows geographical discrepancies: compared with the eastern and western regions, the development of green finance in central region can reduce carbon emissions more significantly; not only can the development of green finance directly reduce carbon emission, but also through the upgrading of industrial structure and technological innovation. The research not only provides a new perspective and supplementary empirical evidence for understanding the carbon emission reduction effect of green finance, but also offers some useful references for green finance to contribute to carbon emission reduction.

From the perspective of energy consumption optimization, this paper studies the impact of green finance on carbon emissions in China. Firstly, based on the theoretical perspective, this paper explores the mechanism and path by which green finance influences carbon emissions, and analyzes the role of energy consumption in this process. Then, this paper utilizes the STIRPAT model, chain multiple mediation effect model and panel threshold model to empirically analyze the influence of green finance on carbon emissions, using provincial data from China from 2005 to 2019. The results are as follows: (1) Green finance significantly reduces carbon emissions. After accounting for potential endogeneity, this conclusion is still valid. The heterogeneity test reveals that the inhibitory effect is more remarkable in northern regions, high-carbon emission regions and energy-rich regions. (2) The results of the bootstrap test reveal that at the national level, green finance decreases carbon emissions through three paths: green technological innovation, ecological evolution of the industrial structure and green technological innovation facilitating ecological evolution of the industrial structure. Furthermore, in energy-rich regions, green finance significantly inhibits carbon emissions through all three paths, while in energy-poor regions, green finance reduces carbon emissions only through green technological innovation. (3) There is a nonlinear relationship between green finance and carbon emissions. Specifically, regardless of energy intensity or energy consumption structure, only when it is below the threshold can green finance significantly inhibit carbon emissions. Thus, realizing energy consumption optimization is an effective way to ensure the carbon emission reduction effect of green finance.

The study was aimed at investigating the dynamic relationship between environmental taxes, green financing, and carbon dioxide (CO2) emissions in Brazil, China, India, and South Africa from 1994 to 2019. To thoroughly examine the proposed relationship, a family of robust econometric methods is used to get reliable and accurate results. Our evidence indicates that green finance and CO2 emissions are negatively connected with each other. Similarly, positive relationship is found between environmental taxes and CO2 emissions. Additionally, environmental taxes and green finance are positively related as well. Further, the results of the Method of Moments Quantile Regression estimator indicate that green finance and CO2 emissions decrease in countries with higher pollution compared to those with lower pollution. Interestingly, environmental taxes only contribute to pollution in countries with higher emissions, whereas CO2 emissions increase environmental taxes in all sample countries. Lastly, green finance has a mitigating effect only in countries with greater pollution, and CO2 emissions have a negative rebound effect on green finance in countries with greater CO2 emissions. According to the evidence, green financing can be an effective tool for promoting environmental quality. By allocating the funds collected from environmental taxes to green financing, environmental sustainability can be promoted in sample countries.

Green finance has been widely acknowledged as a pivotal instrument for mitigating carbon emissions. However, few studies have focused on the role of maturity mismatches in promoting carbon emission reduction through green finance. This study aims to develop a composite criterion for green finance and examine the mechanism of how green finance affects carbon emissions via the new perspective of maturity mismatch. It is accomplished by applying a two-way fixed effects model which incorporates provincial data spanning from 2010 to 2020. The empirical evidence suggests green finance plays a significant role in carbon emission reduction, a result that remains robust even after undergoing other tests such as using instrumental variables and alternating econometric models. Furthermore, this effect is particularly pronounced in regions with high degrees of green finance and low energy consumption. Mechanism analysis documents that green finance reduces carbon emissions by addressing maturity mismatch issues faced by green enterprises. Further research finds that green finance can promote the synergy of pollution and carbon reduction; in particular, the effect of maturity mismatch on SO2 reduction is more obvious. Consequently, this study offers practical recommendations for governments, financial institutions, and other relevant policymakers to further propel the advancement of green finance.

The aim of the paper is to apply the Environmental Kuznets Curve (EKC) model in order to explore the link between economic complexity index (ECI) and carbon emissions, in 25 selected European Union (EU) countries from 1995–2017. The study examines a cointegrating polynomial regression (CPR) for a panel data framework as well as for simple time series of individual countries. In the model is also included the variable ‘energy intensity’ as main determinant of carbon emissions. Depending on economic complexity, the CO2 emissions pattern was found to exhibit an inverted U-shaped curve: in the initial phase, pollution increases when countries augment the complexity of the products they export using and after a turning point the rise of economic complexity suppress the pollutant emissions. The panel cointegration test indicates a long-run relationship between economic complexity, energy intensity and carbon emissions. It was also found that a rise of 10% of energy intensity would lead to a 3.9% increase in CO2 emissions. The quadratic model incorporating ECI is validated for the whole panel as well as for six countries (Belgium, France, Italy, Finland, Sweden and the United Kingdom). The graphical representation of the EKC in these countries is discussed. Policy implications are also included.

Nexus among green finance, technological innovation, green fiscal policy and CO2 emissions: A conditional process analysis

Grounded in the theory of new economic geography, this research develops a comprehensive theoretical framework to examine the spatial interaction mechanisms between the Green Finance Index and carbon emissions. Employing a range of econometric techniques—including three-dimensional kernel density estimation, spatial quantile regression, bivariate spatial autocorrelation analysis, and the spatial linkage equation model—the dynamic evolution, spatial pattern shifts, and mutual influences of green finance and carbon emissions in the middle and lower reaches of the Yellow River from 2003 to 2022 are systematically assessed. The findings indicate that (1) both carbon emissions and the Green Finance Index have experienced a trajectory of continuous growth, phased decline, and structural optimization, accompanied by a gradual shift in the regional center of gravity from coastal economic zones towards resource-intensive and traditional industry-concentrated areas; (2) significant spatial clustering is evident for both green finance and carbon emissions, demonstrating a strong spatial correlation and regional synergy effects; (3) a persistent negative spatial correlation exists between green finance and carbon emissions; and (4) green finance exerts a stable negative spatial spillover effect on carbon emissions, suggesting that the influence of green finance extends beyond localities to adjacent regions through spatial externalities, manifesting pronounced spatial transmission and linkage characteristics. By unveiling the bidirectional spatial association between green finance and carbon emissions, this study highlights the pivotal role of green finance in driving regional low-carbon transitions. The results provide theoretical insights for optimizing green finance policies within the Yellow River Basin and offer valuable international references for similar regional low-carbon development initiatives.

This study aimed to understand green finance’s impact on fertilizer use and agricultural carbon emissions. We selected the macro panel data of 30 provinces (cities) in China from 2000 to 2019. The main research methods are standardized test framework (cross-sectional dependence, unit root and cointegration test), the latest causal test, impulse response, and variance decomposition analysis. Examined the long-term equilibrium relationship between green finance, fertilizer use, and agricultural carbon emissions. The results show: fertilizer consumption and agricultural carbon emissions have a positive correlation. However, green finance can significantly reduce agricultural carbon emissions. The causal test confirmed the bidirectional causal relationship between agricultural carbon emissions and fertilizer use. At the same time, verified one-way causality from green finance to both of them. Interpret the results of impulse response and variance decomposition analysis: among the changes in agricultural carbon emissions, chemical fertilizers contributed 2.45%, green finance contributed 4.34%. In addition, the contribution rate of green finance to chemical fertilizer changes reached 11.37%. Green finance will make a huge contribution to reducing fertilizer use and agricultural carbon emissions within a decade. The research conclusions provide an important scientific basis for China’s provinces (cities) to formulate carbon emission reduction policies. China has initially formed a policy system and market environment to support the development of green finance, in 2020, the “dual carbon” goal was formally proposed. In 2021, the national “14th Five-Year Plan” and the 2035 Vision Goals emphasized the importance of green finance. It plays an important supporting role in carbon emission reduction goals, and green finance has become an important pillar of national strategic goals.

This study investigates the impact of Internet use, financial development, economic growth, and trade openness on carbon dioxide (CO2) emissions in selected European Union (EU) countries. To this end, pooled mean group (PMG) estimator is utilized for panel data from 2001 to 2014. Empirical findings suggest that Internet use has long-run relationship with CO2 emissions and lowering the environmental quality in EU countries. Also, the electricity consumption has a positive and significant effect on CO2 emissions. Moreover, interestingly, economic growth and financial development have a diminishing negative impact on CO2 emission. Heterogeneous panel Granger causality results suggest unidirectional causality running from Internet use to CO2 emissions. The finding implies that the European Union countries did not achieve the level of green information and telecommunication (ICTs) consumption. Overall, the innovative findings indicate that Internet use is raising the threat to the sustainable development. Thus, to curb and mitigate CO2 emissions from Internet use and electricity consumption is the need of time to maintain the sustainable development in EU countries.

The decrease in the level of greenhouse gas (GHG) emissions from industry and agriculture is one of the biggest challenges that European Union (EU) countries have to face. Their economic development should occur under the conditions of limiting the pressure on the environment. The agricultural and industrial sectors play a key role in ensuring food security, technological progress, job security, social well-being, economic competitiveness, and sustainable development. The main purpose of this article was to identify and compare the level, trends, and variability in greenhouse gas emissions from industry and agriculture in EU countries in 2010–2019, to create classes of countries with similar gas emissions, and to analyze the average values of their economic conditions. The original contribution to the article was to investigate whether there is a relationship between the level of greenhouse gas emissions and the economic development of countries and other economic indicators characterizing the sectors of industry and agriculture. Empirical data were obtained from the Eurostat and Ilostat databases. Basic descriptive statistics, classification methods, multiple regression, and correlation methods were used in the study. The industrial and agricultural sectors in EU countries emit similar amounts of greenhouse gases into the environment. In the years 2010–2019, the percentage share of emissions from these sectors in total gas emissions was growing dynamically, but no evidence was found indicating that those countries that emitted the most greenhouse gases significantly reduced their emissions in the decade under review. Moreover, EU countries are still significantly and invariably differentiated in this respect. Greenhouse gas emissions from industry and agriculture are influenced by the economic characteristics of these sectors, such as the level of GDP per capita, the scale of investment by enterprises, the expenditure on research and development, as well as employment in these sectors. The findings of this study show that total greenhouse gas emissions from all sources increase with countries’ economic growth, while a higher level of support of EU countries for research and development, and a greater share of employment in both industry and agriculture, translate into higher greenhouse gas emissions from these sectors. These conclusions may be useful for decision makers in developed and developing countries, as well as those in the industrial and agricultural sectors, in controlling and verifying the possible causes of greenhouse gas emissions in terms of the need to reduce their negative role on the environment and human health.

This study examined the causal dynamics between circular economy (CE) and carbon dioxide (CO2) emissions in European Union (EU) countries. The selected CE indicators included the trade in recyclable raw materials (TRM) and the circular material use rate (CMR) in the secondary raw materials area, the generation of municipal waste per capita (GMWp) in the production and consumption area and the recycling rate of municipal waste (RMW) in the area of waste management. The coefficients of the panel cointegration equations showed that for every 1 percentage point increase in RMW, average CO2 emissions decreased by 0.5%, while for every 1 percentage point increase in GMWp and TRM, the average CO2 emissions increased by 0.263% and 0.101%, respectively. It also showed that the recycling volumes and recycling rate had a positive but very limited impact on the CMR. The panel vector error correction model result showed that there were long-run bidirectional causalities between CE indicators and carbon emissions, and the TRM had a short-run negative impact on waste generation. However, the short-run impact of CE indicators on carbon emissions was not significant, which may be because the European CE is still in its infancy. The finding suggests that policymakers should adopt multilateral policies such as reducing carbon emissions, improving the efficiency and productivity of resource management and waste recycling, and increasing investment and innovation in the secondary raw materials market to achieve resource decoupling and impact decoupling. The decoupling of these two types is a necessary condition for sustainable development.

PurposeThis study aims to explore the impact of green finance, economic growth (EG), innovation and energy intensity on carbon emissions in India. Due to the severe climate conditions, environmental protection has become a major concern worldwide which needs the attention of policymakers and researchers.Design/methodology/approachThis present study uses India’s time series data from 2000 to 2020. Auto regressive distributed lags cross-sectional autoregressive distributed lag (ARDL)-bound testing technique is used to study the association between key variables and carbon emissions. The Granger causality test is also applied to test the both-sided link between variables.FindingsThe ARDL-bound test confirms the long-run relationship between the selected variables. The empirical result of this study reveals that green finance and innovation enhance environmental quality through carbon emissions reduction as both variables show a significant negative result in the long run. However, EG and higher energy intensity contribute to environmental degradation as both variables show a significant and positive result in the long run. The Granger causality test showed unidirectional causality between carbon emission and green finance, EG and carbon emission, energy intensity and carbon emission and bidirectional causality between innovation and green finance.Originality/valueThis study’s results imply that a long-run relationship exists between the key variables and carbon emissions in India. Green finance and innovation can facilitate sustainable growth in India by reducing carbon emissions. Based on empirical findings this study provides recommendations to policymakers and industrial sectors.