RJOAS February 2025
by Hardana Andrean Eka, Jishun Zhou (School of Economics, Huazhong University of Science of Science and Technology, Wuhan, People's Republic of China)
The main objective of this empirical research is to examine the asymmetric effects of green finance on environmental degradation in selected countries using the Quantile-on-Quantile approach. The current study empirically examines the asymmetric ties between green finance on environmental degradation for the top ten green finance countries by applying a quantile approach on quarterly data from 1990Q1 to 2020Q4. The study applies the latest and advanced methodology and provides a more comprehensive picture of the cross-dependence between green finance and CO2 emissions than conventional regression and time series modeling as it captures the quantiles effect of green finance on quantiles of CO2 emissions. The empirical findings provide quite heterogeneous results across different areas of the syndicate formed by quantum green finance and CO2 emissions, exhibiting asymmetric behavior as predicted by QQR and quantum Granger causality. Green finance improves environmental quality in most of the sample countries except Kazakhstan, Egypt, and Chile. On the other hand, China and India show an overall U-shaped effect of green finance and CO2 emissions. Policy makers and environmental agencies should design effective and urgent strategic responses to address the problem of increasing environmental degradation. There is an urgent need to improve the existing infrastructure by making it more energy efficient and eco-friendly to improve the standard of living which can be a major cause of environmental degradation. However, the overall degrading effect of has been observed in most of the countries, which calls for more stringent and serious efforts to make the city infrastructure more efficient by relying on cleaner energy and balancing the ecological environment.
One of the most relevant environmental upheavals in recent decades is global warming, which characterizes global climate change. Through the contribution of labor, capital resources, and other production inputs, increased human activity is largely responsible for the world's economic growth (Bai et al., 2022). However, competition for natural resources and sustainability among organisms, particularly humans, has been associated with environmental degradation. So far, carbon emissions remain the largest contributor to the decline in environmental sustainability. The concentration of carbon dioxide (CO2) emissions is reported to have increased by about 45% in the past 130 years (Hailiang et al., 2023).
In addition to carbon dioxide emissions from plants, animals, and other sources, the common byproducts of using energy sources are largely attributed to carbon emissions. Unfortunately, CO2 emissions remain inhospitable to environmental sustainability and are a major factor in the global debate on climate change. Therefore, the concept of mitigating carbon dioxide emissions, which is largely an anthropogenic greenhouse gas (about 81% of greenhouse gases), has consistently been a priority of the world's developed economies (Owusu and Asumadu-Sarkodie, 2016). This is because CO2 emissions remain the world's most threatening problem facing natural ecosystems and human development. According to the Intergovernmental Panel on Climate Change 5th assessment report, gas emissions increased undesirably from 9434.4 million tons in 1961 to 34,649.4 million tons in 2011. The faster the economic growth, the more resource goods are needed in the production process, which in turn will reduce the availability of natural resources on earth (Jun et al., 2020; Liu et al., 2023). Production activities are characterized by a certain intensity in the use of natural resources as factors of production (fossil fuels, water, and renewable sources), as well as pollutants and waste produced. High economic growth will encourage environmental pollution (Ma & Chang, 2023).
Extraction of natural resources for production activities without strict environmental regulations will produce greenhouse gases, one of which is CO2. CO2 is a by-product that is produced accidentally and cannot be avoided by the production process (Kutan et al., 2018; Munir & Ameer, 2018). However, excessive, and uncontrolled greenhouse gas emissions will cause depletion of the atmospheric layer and increase the earth's temperature, which has an impact on increasing sea level due to the expansion of sea water, melting glaciers, and accelerating the melting of eternal ice at the north and south poles (Sadiq et al., 2023). This is the cause of global climate disruption which is irreversible.
The Sustainable Development Goals (SDGs), which were approved by both developing and developed UN member states in 2015, are a global call to action to guarantee that by 2030, everyone can live in peace and prosperity, according to Li & Jia, (2017) The SDGs are made up of 17 objectives that promote environmental, social, and economic sustainability. SDG 7 of the 17 goals highlights the need for affordable, clean energy for environmental sustainability. According to Kasman & Duman, (2015), supplying the globe with cleaner, more effective energy would ultimately aid in environmental preservation, which will support future economic growth.Historical records show that environmental disasters related to humans are not a rare phenomenon. For example, in 800 BC in China, soil conservation activities with terracing for rice fields resulted in deforestation. In addition, in the heyday of the Roman Empire, the land and water around Rome were contaminated by human activities. Economic growth should not rule out environmental variables, because without a decent living environment, in the end humans will find it difficult to meet their needs. Reduced environmental quality can reduce economic growth, caused by decreased community productivity due to health factors and additional expenditures on health (Khan et al., 2018).
Several theoretical explanations have been provided in previous literature to explain the relationship between green finance and environmental pollution (Koçak & Ulucak, 2019; Shen et al., 2021). Green finance increases environmental degradation in the early stages of development, but the effect becomes negative and environmental quality improves after reaching a certain threshold. The global monetary crisis significantly affected the trajectory of green finance, presenting both challenges and opportunities for sustainable economic development. The link between financial instability and environmental degradation became apparent, prompting discussions on the need to integrate green initiatives into recovery strategies. The concept can be applied at the national level and illustrates economic transformation and social transformation, but the empirical findings are mixed and inconclusive. For example, some studies verify an inverted U-shape of the effect of green finance on environmental degradation (Usman et al., 2022; Richardsen, 2024).
The environmental transition theory (ETT) assumes that the population initially increases in a developing environment due to higher demand for residential energy consumption, infrastructure development and transportation (Shao & Huang, 2023). In their empirical study, Yang et al. (2023) reported that green finance has not been fully proportional in addressing environmental degradation. In addition, the concepts of smart cities and compactness have many sophisticated features and attributes, and previous literature has provided mixed results on the effect of green finance on pollution (Ahmed et al., 2019; Cetin et al., 2018). Therefore, the findings from previous studies are inconclusive and cannot be generalized and there is no unanimous agreement on the exact nature of the relationship between environmental degradation pathways as the complexity of this relationship is highly dependent on factors such as industrial growth rate, urbanization rate, use of energy efficient technologies, regional variations, sample characteristics, variations in urban features and attributes and econometric techniques (Ahmed et al., 2019; Du & Xia, 2018; Hickmann, 2021).
Our study contributes to the existing literature in the following ways. First, to the best of our knowledge, this is a pioneering study to investigate green finance on carbon emissions using a unique sample and special case of the world's top ten countries with green finance contributions. This study utilizes the recent and innovative methodology of quantile-on-quantile regression (QQR) proposed by Sim and Zhou (2015) to study the relationship between urban agglomeration and environmental degradation across ten countries. The main motivation behind the adoption of this unique approach is its advanced capabilities as it is a blend of quantile regression and non-parametric approaches (Arain et al., 2019). As such, it allows for capturing the asymmetric effects of green finance quantiles on carbon emission quantiles and vice versa, which is not possible with conventional econometric regression methods (Chang et al., 2020). Third, we have also applied the recently developed method of non-linear quantile Granger causality estimation developed by Troster et al. (2018). This approach not only aligns with the QQR methodology but also determines the causality relationship between green finance and carbon emissions at the median, lower tail, and upper tail of the distribution. The empirical findings obtained from this asymmetric causality in quantiles approach provide further support and validity to the QQR results.
Future research needs to apply more advanced spatial analysis and non-linear econometric techniques as the existing literature provides contradictory results. The findings of most previous studies are driven by conventional time series modeling which may not only fail to capture the true relationship between green finance and environmental degradation, but also lack in examining the asymmetric relationship between the variables (Hanif et al., 2019; Ibrahim, 2023; Jian & Afshan, 2023). The prevailing scenario of controversial and inconclusive findings, unsophisticated and primary utilization of conventional methodologies motivated us to apply an innovative and more advanced approach. Moreover, previous literature has largely documented the relationship between environmental degradation with mixed findings. However, the issue of green finance has been relatively neglected in previous studies. Therefore, the main objective of this empirical study is to examine the asymmetric effect of green finance on environmental degradation in selected countries using the Quantile-on-Quantile approach.
To investigate the non-linear relationship between green finance and CO2 emissions, this study has selected twenty countries based on the following criteria. First, the top ten countries were selected, as an initial sample, based on the highest green finance ratio in the World Bank's 2022 country rankings; these represent the majority of countries. In addition, this study aims to in our selected sample countries improve or degrade environmental quality across a wide range. Thus, our top ten countries include Türkiye, India, Brazil, China, Egypt, Italy, South Africa, Vietnam, Kazakhstan, and Chile, after satisfying all the above-mentioned data availability and econometric issues. Table 1 provides full details on the sample selection criteria and the final set of countries.
The data used in this study consists of two variables: green finance and CO2 emissions, according to IRENA. CO2 emissions have been used for environmental degradation. All data on these two annual time series are taken from the IRENA database for the period ranging from 1990 to 2020. We have converted the annual data into quarterly data in Eviews9 by using the sum quadratic transformation method by following closely the work of Shahbaz et al. (2018). This conversion from low- to high-frequency series reduces the problem of seasonal variation by excluding the seasonality by excluding data that correspond to appropriate deviations (Arain et al., 2019). Thus, our final dataset data set contains quarterly variables of economic agglomerations from 1990Q1 to 2020Q4.
This study uses quantile-to-quantile regression (QQR) as proposed by Sim and Zhou (2015) to investigate the asymmetric relationship between green finance and CO2 emissions across twenty major countries in the world. The QQR approach combines the properties of non-parametric and quantile regression approaches. It regresses green finance quantiles on CO2 emissions, and vice versa, to capture the asymmetric and spatially asymmetric characteristics of the model over time (Ihsan et al., 2022). Shahbaz et al. (2016) argue that the QQR technique offers richer information and comprehensive findings compared to ordinary least squares and traditional quantile regression and is performed in the following three steps. First, classical quantile regression is applied to evaluate the effect of a predictor, e.g. green finance, on various quantiles of the criterion variable, i.e. CO2 emissions. Second, the classical linear regression technique was also applied to examine the impact of green finance on CO2 emissions at the tail quantile and head quantile of the data distribution and vice versa. Thirdly, local linear regression has been performed to assess the impact of certain quantiles of green finance on CO2 emissions and vice versa to address the issue of dimensionality by giving more weight to values around adjacent quantiles. We start with the following nonparametric quantile-to-quantile regression equation from the quantile-to-quantile approach.
We have applied QQR to investigate the relationship between green finance and CO2 emissions for the top 10 green finance countries in the world. The derived coefficient of QQR presented in Figure 1 represents a three-dimensional graph by means of countries in two columns. The first column captures the effect of the τth quantile of green finance on the θth equidistant quantum of CO2 emissions, as represented by β1(θ, τ), for all the ten countries. Similarly, the second set of graphs in column 2 represents the slope parameter 𝜆 1(θ, τ) measuring the impact of the τth equidistant quantile of CO2 emissions on the θth equidistant quantum of green finance development. The graphical presentation of the slope parameters of the QQR approximation clearly shows that the relationship between green finance and CO2 emissions is not only symmetrical, but the shape of this quantum relational curve varies greatly across countries and time periods. Therefore, individual country-by-country debates have been provided for each country for better understanding following the research conducted by Troster et al (2018).
In Türkiye, the impact of green finance on CO2 emissions appears as an increasing S-curve with a relatively flat peak. During the initial environmental management, there is a strong negative effect of green finance on CO2 emissions at all quantiles for the lowest quantiles of green finance (i.e. 0.02-0.10). However, the negative effect has a decreasing rate of slope coefficient β 1 (θ, τ) up to the middle quantum of green finance across all equally spaced CO2 emission quantum. However, green finance has a relatively weak positive effect on CO2 for the middle quantum (i.e. 0.40-0.10) across all quantum CO2 emissions. Moderately high levels of green finance (i.e. 0.60-0.80) can reduce CO2 emissions across all quantum, but these negative effects are weaker than those from the lower tail. The effect of green finance on CO2 emissions becomes very strong and positive for the upper quantile (0.80-0.85) which implies that the impossibly higher pressure from green finance reduces CO2 emissions.
On the other hand, the effect of low and middle quantum (i.e. 0.02-0.10) CO2 emissions is negative but very weak on green finance across its lower quantum. This effect becomes weak but positive for the upper-middle green finance quantum, which implies that relative CO2 emissions induce green finance. Moreover, this positive effect of CO2 emissions is strongly expressed in the upper quantiles of both variables, suggesting that higher environmental degradation is associated with greater green finance in Türkiye. This illustrates that excessive levels of green finance in Türkiye can substantially improve environmental quality. There is an overall upward trend of this effect over the years. The results from Türkiye are consistent with the previous study of Zhang et al. (2023). which documented that higher levels of green finance emit more pollution.
India in a flat M-shaped curve of green finance on CO2 emissions with a plateau-type peak. The slope coefficient of this effect is negative across all CO2 quantiles for the lowest quantile of green finance (i.e. 0.06). However, the effect of green finance becomes strongly positive as the size of the slope parameter increases for the below-average quantile of green finance (0.12-0.20) across the entire spread of CO2 emissions. Green finance's positive impact can be seen across all quantum CO2 emissions in the upper green finance quantum spread (i.e. 0.55-0.90); it implies that higher levels of green finance create environmental quality. However, this positive effect of green finance, in the highest quantity, becomes weaker across the CO2 emission space, which brings an improvement in environmental quality. The effect of CO2 emissions on green finance is positive overall across all quantiles of green finance, but the size of this effect is relatively weak when compared to green finance on CO2. This relatively weak but positive effect of environmental degradation is particularly pronounced in higher quantiles of CO2 emissions (0.50-0.70); this strongly positive slope parameter implies that higher levels of CO2 emissions trigger higher levels of environmental degradation in India. Our findings also support previous studies that have also verified the U-shaped inverter effect of green finance (Jinru et al., 2022; Kemfert & Schmalz, 2019). Haq et al. (2023) showed that the rapid growth of green finance is improving the environment in the long run. In addition, India has large investments in renewable energy, which has improved environmental quality.
The case of Brazil also explains the overall positive effect of green finance, on CO2 emissions over the quantum spread space in Figure 1 for Green Finance has a reduced negative effect for the lowest quantum (0.04-0.10) on carbon emissions across all its quantum. However, this effect became positive for inducing environmental degradation until the 90s. Quantiles of green finance across the corresponding space of CO2, including all its quantiles. Higher quantiles of green finance (0.75-0.95) have risen sharply and have a highly elastic positive effect on increasing CO2 emissions. These findings suggest that green finance, over time and space, has a more enhancing effect on environmental quality in Brazil. The effect of CO2 emissions on green finance is weak but heterogeneous across different quantum regions of both variables. For example, low quantiles of carbon emissions (0.02-0.15) have a weak negative effect on the upper quantiles of green finance (0.40-0.80). The negative sign of this effect of CO2 emissions is relatively weak but similar to green finance, as discussed earlier. The positive effect of carbon emissions is more prominent in the accumulation syndicate region of the low-medium quantile (0.40-0.60) of CO2 and the upper and high quantiles (0.50-0.75).
Based on the overall results, Brazil has the most devastating impact of green finance on the environment in our selected sample. This is quite common in developing countries that pose serious challenges in environmental sustainability due to lack of planning for excessive use of fossil fuel energy, etc. (Hanif et al., 2019). Brazil's findings are in line with Ibrahim et al. (2023) who reported that countries with problems can cause more environmental degradation in developing countries.
Kazakhstan follows a sharper U-shaped effect of green finance and CO2 emissions over their respective equal distance quantum spreads. The lowest quantile of green finance (0.06-0.20) has a strong and highly elastic positive effect on CO2 emissions across all its quantiles. However, this positive effect of green finance becomes weakly positive on CO2 across the entire quantum spread. Despite the positive effect of green finance development across the CO2 quantum, it increases for the rest of the green finance quantum space and becomes highly elastic again (0.90-0.95). This finding suggests that green finance initially reduces environmental degradation at a higher rate for its lower quantum range. It becomes relatively leaner for mid-range quantum which lowers the speed of environmental degradation. The impact of CO2 emissions on green finance tends to be weak and gives mixed results about the sign of the slope parameter. The effect of carbon emissions is weak and positive for its lower quantum (0.10-0.25) which induces green finance, very weak and negative for its low-middle quantile. (0.50-0.30), and a traceable positive effect for its higher and higher quantiles (0.50-0.80).
Based on Kazakhstan results reveal interesting empirical results about the condition of green finance. These findings are consistent with those of Shahbaz et al. (2017) for Malaysia and (Khan et al., 2018) in the case of China. Therefore, green finance leads to better environmental quality in Kazakhstan after reaching a certain threshold. Extensive immigration policy, large flow of foreign immigrants and changes in social and demographic structure in Kazakhstan can be attributed to environmental degradation.
In Egypt, the effect of green finance on carbon emissions tends to peak and decline across the syndicate area formed by the respective quantum. The effect of green finance and positive but has a decreasing rate for its lower quantiles (i.e. 0.02-0.50) across all quantum of CO2 emissions. This positive effect is highly elastic, which implies that the development of green finance on environmental degradation is greater across the syndicate region. The positive effect of green finance for its mid-range quantum (0.40-0.85) becomes weak but positively inelastic across the spread of CO2 emission quantum. However, the slope coefficient of green finance becomes negative and inelastic for higher level quantum. (0.700.85). For the highest quantile of green finance (0.90-0.95), this negative effect is highly elastic across the quantum space of carbon emissions.
Based on these conditions, it shows that higher levels of green finance reduce environmental degradation in Egypt. The effect of carbon emissions on green finance in Egypt follows an overall increasing trend. The lowest quantum of CO2 emissions (0.05) has a trivial positive effect on the entire quantum of green finance. However, for the following low average quantum carbon emissions have a marginal negative impact across the agglomeration quantum spread of green finance. However, this effect of environmental degradation on green finance becomes positive and stronger for medium and higher quantum of CO2 emissions (0.50-0.95) against all quantum of green finance. These results suggest that higher carbon emissions led to environmental degradation in Egypt.
Based on these conditions, it shows that higher levels of green finance reduce environmental degradation in Egypt. The effect of carbon emissions on green finance in Egypt follows an overall increasing trend. The lowest quantum of CO2 emissions (0.05) has a trivial positive effect on the entire quantum of green finance. However, for the following low average quantum carbon emissions have a marginal negative impact across the agglomeration quantum spread of green finance. However, this effect of environmental degradation on green finance becomes positive and stronger for medium and higher quantum of CO2 emissions (0.50-0.95) against all quantum of green finance. These results suggest that higher carbon emissions led to environmental degradation in Egypt.
The effect of green finance on CO2 emissions in China follows a flatter U-shaped spatial curve over the quantum syndicate region of both variables. The lowest quantile of green finance (i.e., 0.05) has a relatively weak and positive effect on CO2 emissions. However, the sign of the slope coefficient becomes negative for lower average quantum (0.10-0.30) of green finance and has a highly elastic impact on all quantum of CO2 emissions. These results suggest that green finance reduces environmental degradation for this region at relatively higher levels. However, the effect of green finance becomes negatively inelastic for its lower and upper-middle dispersion of quantiles (0.35-0.65) across all quantiles of CO2 emissions whereas for higher quantiles of green finance (0.70-0.95), the sign of the coefficient is very strong and positively elastic. The effect of CO2 emissions on green finance is relatively week for the combined space of low and medium quantiles of CO2 emissions (0.05-0.50) compared to the majority of quantiles (0.05-0.60) associated with green finance. These results suggest that environmental degradation negatively causes green finance in synchronized areas. On the other hand, high levels and high quantiles of urban CO2 (0.55-0.80) have positive marginal effects over lower quantiles of carbon emissions (0.05-0.25). However, the positive effect of environmental degradation is more manageable and significant in the area synchronized by the top quantiles of both variables.
The results reject the existence, and our findings are in line with Shahbaz et al. (2017) who also reported a U-shaped effect on CO2 emissions. Asian cities such as Mongolia, which are mostly developing countries, have been facing greater environmental pressures due to over-concentration in large metropolitan cities, ineffective urban planning and inefficient urban design, etc. (Liu et al., 2023).
In South Africa, the angular parameter, β 1(θ, τ) shows a smoother S-shaped effect, like Türkiye, of green finance on carbon emissions. The smallest quantile of green finance (i.e. 0.01-0.06) has a very strong and negative effect on all quantiles of CO2 emissions. The negative inelastic effect of green finance on carbon emissions is related to the joint space of the lower quantiles and all quantiles of CO2 emissions. After the 30th quantile of green finance, this effect becomes positively elastic, which is more traceable to the upper-middle and higher quantiles and the corresponding spread of CO2 emissions. These results have the interesting finding that higher levels of green finance in south africa have substantially increased environmental degradation, especially at very high levels near the upper edge of the space curve. The effect of CO2 emissions is relatively trivial, and the sign of the slope parameter is negative for the area formed by low quantum (0.05-0.10) of green finance against all carbon emission quantum spreads. Environmental degradation negatively affects green finance in this syndicate region. The effect of CO2 emissions is also negatively inelastic near the low quantum (0.05-0.15) of carbon emissions and the lower, middle and upper middle quantum of green finance. However, the enhanced peaks generated by the middle and upper average quantum of carbon emissions (0.500.70) against most of the green finance quantum space indicate a positive effect of environmental degradation.
This finding is in line with some previous studies such as Li & Jia, (2017) who identified a kind of high relationship between green finance and CO2 emissions in China. Due to extensive use of fossil fuel energy and relaxed environmental policies, Saudi Arabia has produced severe environmental problems, and excessive levels of CO2 emissions cause air, water and underground pollution.
Vietnam's empirical results reveal an interesting trend regarding the impact of green finance on CO2 emissions. The results show an overall decreasing impact of green finance on environmental degradation in the country. The lowest quantile of green finance affects CO2 emissions negatively across its quantiles, but this effect becomes positively inelastic at the location of the lower-than-average quantile (0.20-0.30) and all quantum of carbon emissions. However, the impact of green finance is negatively inelastic for the range of 0.25 and 0.45 quantum, and highly elastic for the upper and upper quantum against all carbon emission distributions of the quantum. These findings suggest that higher levels of green finance improve the environment in Vietnam at a relatively higher rate. This is more pronounced in the highest quantum. The effect of CO2 emissions on green finance in the adjacent spatial curves follows the same downward trend except near the upper and middle quantum, which are. The positive impact of carbon emissions is highly inelastic in the syndicate region created by its lower, middle, and upper quantum (0.05-0.10). These findings are synchronized with the impact of green finance and suggest that higher levels of carbon emissions have a negative impact on green finance in Vietnam.
Vietnam's findings explain higher green finance has a decreasing effect on CO2 emissions. Our results are consistent with those of Li & Gan, (2021) for Japanese Cities and Su et al. (2018) in the case of Chinese cities; these studies empirically verify the role of urban concentration pollution reduction in larger cities. They attribute these positive results to efficient transportation mechanisms, cleaner technologies and energy savings for compact city design. In addition, Italy has greater access to fresh water and its population is less exposed to air pollution due to a better ecological and natural environment.
The effect of quantum green finance on quantum CO2 emissions in Italy shows an overall increasing trend across the same quantum space. The effect of the lowest quantile (0.05-0.10) of green finance on all quantiles of carbon emissions is positively inelastic, has a downward trend, and finally becomes negative for the next two quantiles of green finance. After the 25th quantile of green finance, the sign of the slope parameter becomes positive and strong, indicating that green finance induces environmental degradation in this syndicate region. However, this positive effect on green finance increases, especially for higher quantum of carbon emissions (0.70-0.80). However, in the highest carbon emission quantum, this positive effect (0.85-0.95) has a downward trend implying that excessive amounts of CO2 emissions inhibit green finance in all its quantum. These findings are with in Italy as the country is facing increasing pollution, which is mainly contributed by industrial production, construction, transportation, energy production and wood burning. A recent report shows that Canadian companies produce 75% more environmental pollution than American companies, which is an alarming signal for the Canadian government to design appropriate environmental and urban policies (Okibe, 2019).
Our QQR results show heterogeneous results on the effects of green finance and CO2 emissions across space and time due to the different nature of country growth and spatial variation. Most of the sample countries such as Türkiye, India, Brazil, China, Italy, South Africa, and Chile have positive effects on green finance and environmental degradation and these positive effects are more pronounced in higher quantum of both variables. The positive relationship between green finance and CO2 emissions suggests that the level of environmental degradation. This finding implies that this may be due to excessive use of non-renewable energy and overdevelopment projects (Apergis & Ozturk, 2015; Cho et al., 2014). In this case, it is China that has the highest positive effect of green finance on CO2 emissions and this positive effect is amplified by the rate of increasing domestic production to accommodate the surge in exports, which increases pollution and worsens environmental quality if green technologies are not adopted. Likewise, India is the second top country in terms of green finance's worsening effect on the environment.
Brazil revealed a U-shaped effect of green finance on CO2 emissions, which can be attributed to increased fuel oil consumption and substantial changes in the social and demographic structure of the economy. These findings are quite synchronous with Shahbaz et al. (2017), who found similar results in the case of Malaysia. On the other hand, China shows an Inverted U Nexus between green finance and environmental degradation. France being a developed country, has seen a rising trend of green finance, and such huge growth initially puts excessive pressure on environmental sustainability. However, the trend seems to be reversed in the quantum of green finance and environmental pollution, which can be attributed to the sustainability of environmental sustainability.
The presence of wave-shaped asymmetric nexus in China is supported by Donglan et al. (2010) who argue that energy use in the form of fuel oil is increasing in China. On the other hand, some countries such as Kazakhstan, Egypt, and Chile have also shown a negative effect of green finance on CO2 emissions especially in the higher quantum tails, which is quite contrary to the findings of most of our sample countries. Empirical results from these countries suggest that higher levels of green finance improve the environment. The inverse relationship between green finance and CO2 emissions suggests that these countries may not have reached excessive levels of green finance. However, the case of Chile reveals a quite diverted and unique pattern, which warrants further investigation.
Our quantitative Granger causality results confirm the previous findings of the QQR and verify a mainly bidirectional causal relationship between green finance and environmental degradation in most of the lower, middle and upper quantum in all countries except South Africa, which fails to document significant causality. One plausible explanation for the insignificant results for South Africa is the relatively little variation in green finance trends from 1990 to 2020 as depicted in Figure 1. While other countries comparatively have shown much greater variation over time, and their causal relationships between green finance and CO2 emissions vary substantially across different quantum. Therefore, a one-way relationship between green finance and the environment has also been observed in very low, medium and very high data distributions, the Granger causal results act as a robustness measure for our mainstream findings from the QQR approach. Bidirectional causal nexus has also been observed in many previous studies (Zhao et al., 2023).
The bilateral feedback relationship between green finance and CO2 emissions confirms previous QQR results, indicating that the two variables influence each other. These findings suggest that green finance and environmental degradation in these countries are strongly linked, and any environmental policy designed to design and implement city infrastructure will affect environmental quality. Then, environmental degradation as in the case of a polluted environment can significantly influence planning decisions, restructuring of infrastructure and transportation systems, the search for better and environmentally friendly technologies, production and use of cleaner energy.
The current study empirically examines the asymmetric tie between green finance on environmental degradation for the top ten green finance countries by applying a quantitative approach to quarterly data from 1990Q1 to 2020Q4. The study applies the latest and advanced methodology and provides a more comprehensive picture of the cross-dependence between green finance and CO2 emissions than conventional regression and time series modeling as it captures the quantiles effect of green finance on quantiles of CO2 emissions. The asymmetric impact of green finance on CO2 emissions provides nonlinearity across multiple quantities. The current study also applies nonlinear quantum Granger causality to investigate the causal relationship between green finance and environmental degradation to confirm the previous findings of the QQR approach. The empirical findings provide quite heterogeneous results across different areas of the syndicate formed by quantum green finance and CO2 emissions, showing asymmetric behavior as predicted by QQR and quantum Granger causality. The empirical findings suggest that green finance improves environmental quality in most of the sample countries except Kazakhstan, Egypt, and Chile. On the other hand, China and India show an overall U-shaped effect of green finance and CO2 emissions. These countries produce more pollution which is not a healthy sign for their sustainable development. Our quantum causal tests further confirm these findings with heterogeneous results across quantum. The results largely verify the bidirectional causal relationship between green finance and CO2 emissions in almost all countries. This feedback relationship implies a strong relationship between green finance and environmental pollution, and any establishment of environmental protection policies should be taken seriously.
The current research study empirically verifies green finance is a complex and interrelated phenomenon as indicated by quantitative methods, and any policy formulation should be designed by considering the varying degree of trends in the green finance emission nexus as conventional approaches provide monotonous or symmetrical behavior that can have a drastic impact on policy design and implementation. For policy makers, environmental agencies must design effective and urgent strategic responses to address the problem of increasing environmental degradation. There is an urgent need to improve the existing infrastructure by making it more energy efficient and eco-friendly to improve the standard of living. The problem that traffic pressure at extreme levels in metros can be a major cause of environmental degradation.
Rethinking more efficient and compact is an all-time challenge for these countries, and an efficient public transportation system should be launched as implemented in China to reduce the pollution burden of private transportation, which relies heavily on fossil fuel energy consumption. The inverted U-shaped effect of green finance on CO2 emissions in Japan suggests that China is adopting renewable and cleaner energy sources to repair environmental damage caused by increasing demand for energy consumption. However, the overall decreasing effect of has been observed in most countries, which requires more rigorous and serious efforts to make city infrastructure more efficient by relying on cleaner energy and balancing the ecological environment.
Original paper, i.e. Figures, Tables, References, and Authors' Contacts available at http://rjoas.com/issue-2025-02/article_05.pdf