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.


Introduction
In the current economic era, the revolutionary boom in industrial developments raises countries' economic competitiveness but also causes ecological degradation due to the heavy consumption of resources and toxic energies (Zhang et al. 2022). At one point, the extreme utilization of energy-related resources surges the pressure on the natural habitats; on the other hand, businesses' attraction towards globalization and financial gains neglects the consequences of substantial resource depletion (Joof et al. 2022). Over time, this escalating consumption is expected to deteriorate the environment more rapidly (Bibi et al. 2021). As per the ecological footprint network, since 1971, the world has been the debtor of its earthly resources and living in a natural deficit because the ratio exceeds the biocapacity of generating the natural resources (Miller and Mössner 2020). This situation results in environmental degradation, global warming, climatic change, and resource scarcity (Murshed 2021). Figure 1 depicts increasing global ecological footprints.
Therefore, countries are trying hard to find the best possible solutions to minimize the overconsumption of resources and fossil-based fuels to abetting the escalation in environmental degradation. Among the most impactful methods in acquiring a pollution-free environment, Zeng et al. (2022a) proposed the concept of green finance to alleviate the environmental downfall as eco-friendly financial advancements are considered the spine of countries transition towards sustainable development.
The notion of green finance arises from going green, including green banks, green funds and bonds, green mega-projects, community base green investment, and other institutional green supporting campaigns to accommodate green financing (Meo and Karim 2022). In addition, green financial policies in a broader context aimed towards mitigating land, air, and water contamination, reducing the production of carbon dioxide, balanced the utilization of natural resources while improving energy efficiency and procuring solutions for vindicating climate diversities . Apart from rising commercial and domestic awareness, governments could also play an essential role in appropriately ruling financial and ecological policies while flourishing the economy and living standards through reassuring environmental quality (Guild 2020). Figure 2 shows growth of green bonds which is a major product of green finance.
Accordingly, green investments are positively integrated with actions of financial developments and ecologically balanced resources that can contribute ideas for sustainable growth patterns through encouraging innovations and boosting practices of transitioning from nonrenewable to renewable energies (Chien et al. 2021;Falcone et al. 2018). To address the adverse ecological consequences, ecological innovation is also considered an efficient, ecofriendly method that reduces the environmental burden . The notion is based on the ideology initiated by Fussler and James (1996) that supported the relationship between sustainability and innovation. It is believed that businesses could generate higher revenues and stabilize economic growth through innovative technical creations that can reduce ecological burden by aiding eco-sustainable production, processes, and strategies (Geng et al. 2021). Ecologically motivated innovations embrace the production of clean energies, lessen wastage of raw materials, minimal air pollution, and adequate utilization of natural resources such as land, water, forest, and sea (Jin et al. 2021). Figure 3 shows the growth of environmental-related technology.
Moreover, green technological advancement proves beneficial in subsiding the deficit ratio of the ecological footprint and preserving the green environment (Suki et al. 2022a;Suki et al. 2022b). However, rigorous environmental regulations and stringent policies must be needed to ensure advancements in production and operational methods that correspond to countries' growth's lucrative objectives while preserving a green ecosystem.
In this regard, the concept of environmental policy stringency (EPS) is gaining acceptance for publicizing the laws of monitoring ecological quality through the maneuvers of limiting resource consumption, emission of toxic gases, chemicals, oil and waste disposals, water, land, and wildlife safety, etc. The positive impact of executing the environmental policy stringency is determined by Galeotti et al. (2020), stressing the government spectators to enforce stringent laws on the industrial, service, and trade sectors to manufacture products via innovative processes and avail financing plans of green investments to attain the economic sustainability (Murshed 2021). Moreover, Porter's hypothesis also claimed that environmental policies' significant impact on ecological innovation led to improving the environmental condition. Figure 4 indicates increasing EPS.
It suggested that the harmful consequences of pollution are reduced when the rise in governmental regulations in preserving environmental degradation innovation is implemented in industrial areas. The concept is particularly gaining attention in emerging economies that struggle limitlessly to explore approaches to transform traditional innovation techniques into eco-innovation strategies accompanied by suitable eco-regulations (Walton et al. 2020). However, the inefficient articulation of environmental policies and the inability to enforce such policies could lead to the increased emission of carbon dioxide gas and heavy resource consumption in the infrastructures (Nathaniel et al. 2021). Hence, the stringency of environmental policies holds a significant place in mitigating the harmful impact of ecological degradation and motivates organizations to adopt the practice of technical innovations, which significantly improves the increasing ecological deficits. Consequently, to enforce these critical factors, it is noteworthy to embark on the economies such as China, which possesses the fastest emerging economy with massive trade and evolving political and economic sectors' prominence in the global community.
Therefore, China's economy is selected in this particular investigation since recently; the country has been placed under global attention for seeking environmental improvement targets in 2025 instead of 2030 owing to its massive economic and environmental impact (Akadiri et al. 2022). Due to the incredible territory advancements in recent years, the country has been declared the second most significant GDP contributor (Worlds bank, 2020), the highest hi-tech manufacturer, and the top exporter in the world. On the other hand, this has resulted in extended ecological pressure evident from the rising ecological deficit of the country, along with the increased air pollution of being the leading emitter of greenhouse gases (Vennemo et al. 2020). Another reason is population growth. According to the world meter elaboration of the United Nations, as of April 2022, the population of China is 1,449,084,337, which makes it 18.47% of the total world population. Therefore, having an enormous population impact, the scarcity of natural resources is evident, which hurts the ecological footprint of China (Ke et al. 2021). The repercussions of environmental degradation from China influence the globe via agricultural, political, industrial, tourism, and trade operations (Zhu et al. 2019), urging the need for ecological solutions for sustainable development in the country. Hence, overviewing the existing circumstances, the objective of the present analysis is to examine the role of green finance, eco-innovation, and environmental policy stringency to leverage sustainability in China.
There are many contributions of the current study-first, the adoption of an ecological footprint as an indicator of environmental degradation. Recently, there has been a discussion on the extensive use of carbon dioxide as an indicator of ecological deterioration owing to rising economic and financial pursuits (Akadiri et al. 2022). Numerous studies asserted the importance of the indicator; however, they found it inadequate since it only considers deterioration brought about by the economic exercises and its associated influence on the globe (Alola et al. 2022;Sharif et al. 2019). Moreover, it is not regarded as an ideal measure of remnants resulting from industrial and financial growth, given the perspective of sustainable development for not accounting for land and water pollution. In addition to air contamination, water, soil, forestry, etc., persist vulnerable conditions, thereby needing sufficient consideration. Therefore, an inclusive measure is ascended recently that can also account for land and water quality to provide appropriate policy implications to curtail ecological downfall. In this regard, the ecological footprint measure is considered unique for incorporating the good aspects of ecological deterioration (Suki et al. 2020). The indicator reflects six features of people's demand from the natural habitat. These involve carbon demand, forestry area, agricultural land, grazing fields, build-up land, and fishing grounds. Also, from the policy point of view, an ecological footprint seems ideal for a more holistic approach to resource sustainability and depletion while identifying the Earth's consequences from peoples' actions, hence stands out for reflecting ecological sustainability (Akadiri et al. 2022). Second, the current  Demiral et al. (2021) investigation is unique for evaluating the sustainable measures of green finance, eco-innovation, and environmental policy stringency in attaining environmental sustainability and offers pioneer evaluation. China has surpassed its biocapacity and persistent deficit in ecological footprint for more than two decades, making it the country with the most significant global aggregate ecological footprint.
The country's economic activities are linked to extensive production, prominent for having the most significant industrial sectors of manufacturing and chemical involving energy-intensive procedures that resulted in higher ecological degradation since coal pertain the primary energy source (Ali et al. 2022c, a, b). Therefore, the assessment of innovative green measures to curb the country's ecological deficits would offer viable solutions for curtailing its rising ecological deficits. Additionally, the methodological novelty pertains to assessing the quantile-based empirical analysis. The current study aims to identify the crucial relationships among the variables with the help of quantile-ARDL estimation. Through this estimation method, a subdivision in lower, middle, and higher quantiles accumulated to present the asymmetric impact of green finance, ecoinnovation and policy stringency on the ecological footprint via giving short-run and long-run equilibrium. Hence, the significance of the adopted method lies in estimating econometrics issues concerning the novel median of the approximation ) against the orthodox average econometric values adopted in earlier studies (Sharif & Afshan 2018;Qureshi et al. 2018). Similarly, through the quantile technique, the results of time series data are correctly detected while providing influence that can be generalized as a whole notable for concerning fat-tail dependent cointegration .
Finally, the present investigation is outlaid in five sections. The "Introduction" section provides the conceptual introduction and the contribution of the variables under study, along with the current environmental situation in China. The "Literature reviews" section reviews existing environmental studies in relevance to assumed variables. The "Data description and methodology" section demonstrates the model and concepts of the adopted methodologies. The "Empirical results and discussions" section delivers empirical outcomes and their explanations. Finally, the "Conclusion and policy implications" section concludes the present study's findings and policy implications.

Literature reviews
The influential work on environmental degradation was found abundantly in the studies of past scholars but still increasing severity of this cause attracts forthcoming researchers to investigate the origins of these difficult circumstances, which distresses the fresh aura of the cosmos Ahmed et al. 2020;li et al. 2021). Hence, conceptualizing the past literature, especially from the zone of developing countries, related to green finance, eco-innovation, environmental policy stringency, and ecological footprint, the current section aims to stimulate a better understanding of the existing environmental condition.

Green finance and ecological footprint
Various aspects of green finance and ecological footprint have been reported previously per specific nations' internal and external factors. Still, mainly articles reflect the affirmative influence of green finance in mitigating resource consumption by motivating the use of nonrenewables while addressing the fundamental causes of rising environmental pressure (Falcone et al. 2018;Murshed 2021). Also, the environmental Kuznets (EKC) theory visualizes the substantial role of green finance in environmental stability (Udemba 2021). The theory facilitates the significance of gradual augmentation in the efficiency and effectiveness of business regulations and imposing the actual concept of sponsoring green funds. Also, during the last two years, the influx of swift green projects, especially in offshore winds and solar PV to attain requirements suggested by SDGs goals highlighted that financial developments via green strategical approaches lead toward decarbonizing economies and facilitates sustainability (Rafique et al. 2021;Ali and Seraj;2022). Based on this notion, Khan et al. (2019) examined the impact of financial developments and investments on BRI nations over the time frame of 2009 to 2016 by applying the methods of an augmented mean group (AMG) and correlated effect mean group (CEMG) on the panel data. The empirical explorations supported the view of EKC theory and showed the significant relationship between financial advancements and investments in the ecological footprint. Similar results are reported by Ali et al. (2022c, a, b), suggesting the negative association of sustainable finance with China's environmental footprint.
Likewise, Majeed and Mazar (2019) extracted the panel data from 131 countries to determine the influence of financial growth on the ecological footprint by employing the GMM and OLS methods under the theory of EKC. Their empirical findings showed the significant impact of financial growth in mitigating the ecological footprint because of domestic credit to the private sector by banks and financial institutes while stressing the innovative incentives of green funding projects. Whereas the EKC hypothesis is not valid in terms of BRICST (Brazil, Russia, India, China, South Africa, and Turkey) nations from the panel data  as demonstrated by Dogan et al. (2020) while using the ecological footprint as the leading indicator. The study projected the usefulness of energy transition in lessening environmental pollution. Similarly, Ali et al. (2022c, a, b) studied the impact of the financial inclusion index on the ecological footprint of ECOWAS nations and concluded that it contributes to harming biodiversity. Aydin and Turan (2020) also elaborated an identical view while investigating the influence of economic stability, financial openness, and trade regulations on the ecological footprint of BRICS regions under the EKC framework. Unlike Majeed and Mazar (2019), their results illustrated the non-significant impact of financial openness while enduring the theory of EKC.
Correspondingly, Sinha et al. (2021) scrutinize the significance of green financing via green projects by using the technique of MMQR from 2010 to 2020. Their suggested conclusions showed the positive contribution of nonrenewables to renewables by implementing solar and energy transition plans to minimize the ecological burden and upgrade environmental performance. Another study by Saud et al. (2020) determines the role of facilitating financial funds and globalization concerning the ecological foot of OBOR countries. The panel estimation technique was applied to data, showing the inverse relationship between financial development and an ecological footprint. Moreover, the additional effect was demonstrated by Ren et al. (2020) on green finance, non-fossil energy use, and carbon intensity by vector error correlation model using the data from 2000 to 2018 for China. The study focused on four green activities: green credit, securities, insurance, and investments. The findings confirmed the positive influence of these strategies in mitigating the emission of harmful gas from the environment. However, fewer developments in green tactics could also become the reason for environmental unsustainability (Youssef et al. 2020). This perception is also supported by Destek and Sarkodie (2019).
Overall, the theoretical findings represented the imperative role of green finance in nourishing the sustainability of the economies like BRICS (Ahmed et al. 2020), G-7 (Uddin et al. 2017), OECD ) and showed a positive association in decreasing the ecological footprint. However, some literature showed limited growth toward green finance, especially in emerging countries that commonly concentrate on nonrenewables (Tan et al. 2021;Kumar et al. 2021), but as per Krushelnytska (2019), green finance has broader aspects like recycling, water purification, control over organizational wastage and pollution, and biodiversity protection. Surprisingly, the EKC model was declared non-valid in most of the studies while employing the variable of green finance concerning the ecological footprint (Idress and Majeed, 2022); thus present study conducts the analyses considering the EKC theory on China's economic sustainability to provide more innovative methods to promote resource efficiency and de-carbonization. The factor of green finance is fruitful in diminishing the consequences of environmental pollution. Still, irrespective of that, fierce competition to achieve economic growth in a minimal timeframe increases the proportionality of the ecological footprint.

Eco-innovation and ecological footprint
Ecological innovation is considered one of the prevalent factors in boosting the quality of the environment since it focuses on achieving sustainable advancement goals (Sun et al. 2021). Moreover, environmentally friendly innovations also ensure the protection of nature by facilitating a green energy transition from fossil-based toxic energies that escalate the severity of environmental pollution . Therefore, the advancements in the technology sector underlie the potential to raise the economic statuses of realms as they engross innovative green techniques in their business procedures. In this regard, considering the crucial role of eco-innovation in a sustainable environment, Ahmad et al. (2021) explored the dynamic connection between ecoinnovation and urbanization on the ecological footprint of G-7 countries from 1980 to 2016. The findings from the panel data highlighted the positive influence of eco-innovation on the environmental footprint while supporting the EKC hypothesis indicating the inverted U-shaped structures. In terms of the OECD nations, Jainguo et al. (2022) reveal that if financial development is augmented with technological innovation, then the quality of the environment will be improved in the region. Moreover, for China, Jin et al. (2021) also reported a similar result while exploring the effects of human capital and eco-innovation by applying the statistical technique of the quantile ARDL. In addition, Chien et al. (2021) also demonstrate the causes of the growing deficit ratio of ecological footprint by using the variables of ecoinnovation, green energy, and environmental taxes. These measures represent a significant and positive association with the ecological footprint of Asian countries.
On the other hand, Wurlod and Noailly (2018) examined the negative association of eco-innovation with energy intensity in 17 OCED countries from 1975 to 2005. The positive harm to the ecological footprint is predicted as the utilization of natural resources is abundant. Moreover, Tao et al. (2021) portray the direct effect of eco-innovation on the growth of the E7 economies to mitigate the carbon emission and flourish the ecological footprint. At the same time, Sun et al. (2021) analyze the impact of globalization and ecoinnovation on environmental pollution in the economy of the USA through the estimation of QARDL. The outcomes showed the significant negative impact of eco-innovation on carbon emissions. Applying similar estimations, Afshan and Yaqoob (2022) studied the effectiveness of eco-innovation on the ecological footprint of China. Their estimation reveals the reduction in ecological footprint by implementing ecoinnovation strategies in the long run.
In a nutshell, recent research indicated that eco-innovation is a significant factor in upgrading economic growth and sustainability (Chien et al. 2021;Ren et al. 2020). Even though implementing eco-innovative techniques in service, agriculture, and industrial sectors diminishes the utilization of harmful gases to a great extent, that positively affects the country's ecological footprint (Ghita et al. 2018;Burek et al. 2022). However, inconsistent outcomes are recognized while implementing the strategical approach of eco-innovation since the difference in the environmental setting of the economies varies in terms of income levels, skill sets, and infrastructure. Significantly, the criteria for imposing technical innovations are typical and tiring for emerging countries as their capital reserves are limited to funding ecologically supported facilities and equipment (Yirong 2022). Hence, the current study aims to provide a detailed examination of the Chinese economy by adopting advanced strategic approaches which can pinpoint the current status of ecological degradation of the population in intensive emerging countries like China.

Environmental policy stringency and ecological footprint
Stringent environmental policies portray the opportunities and accomplishments in the execution of regulations concerning the environment. It elucidates the determination of the economies in about the ecological targets in comparison to the average standards of the nations in enforcing such policies. In this regard, Kongbuamai et al. (2021) stated that the predominant role of environmental policy stringency is crucial in implementing sustainable development goals while safeguarding ecological quality. Out of many administrative implications, the regulation of EPS sustains the elite significance in deteriorating environmental pollution via maneuvering and executing deliberate environmental policies and regulations (Yirong 2022). Among the recent studies, Chu and Tran (2022) investigated the impact of environmental regulation and ecological footprint in 27 OCDE countries utilizing the advanced empirics of MMQR. The statistical exploration highlights the environmental law's substantial effect in the 8th quantile to diminish the harmful impact of environmental depletion. Moreover, the policies suggested imposing more appropriate stringent regulations concerning the manufacturers to retain the excessive usage of natural resources to limit the deficit ratio of ecological footprint. These outcomes are similar to the studies of Murshed (2021) and Sohag et al. (2021) that evaluated the beneficial outcomes of normalizing the environmental policy stringency in the industrial sectors as these units are directly interlinked with the energy-consuming products and produce a negative impact on the ecological footprint of the world. Furthermore, for nineteen OECD economies, Galeotti et al. (2020) analyzed the significance of policies indicators on environmental quality from 1995 to 2009 while utilizing diverse measures of ecological regulations. The findings suggested the crucial role of environmental policies in diminishing ecological degradation. The outcomes reported that regarding the within-nations and betweennations differences, a greater consensus exists for utilizing composite environmental index and emanations-based policy measures. However, indicators concerning strategic pollution reduction offered disparity in the empirical outcomes. Hence, the study suggested that different policy indicators yield diverse findings about their environmental influence.
Moreover, in the five emerging BRICS nations, Kongbuamai et al. (2021) found that environmental policy stringency declines ecological burden. The results proved that renewable or nonrenewable energy consumption, industries, and environmental policies' stringency positively influence ecological footprints. Likewise, another study by Rafique et al. (2022) also showed the short-term benefit of employing stringent environmental policies in improving ecological conditions. However, the contradictory view is explained in the study of Nathaniel et al. (2021) when they explored the nexus between international trade, economic growth, and the role of environmental regulation in N-11 countries between the time scales of 1990 to 2016. Their results indicate the ineffective outcome of EPS in N11 countries in falling the ecological footprint while EKC theory is proven authenticated for these studied nations. Kampas et al. (2021) also declared a similar standpoint.
For more elaboration, the summary of a few existing pieces of literature is presented in Table 1.
Overall literary work identified the significant explorations of employing environmental policy stringency in several economies. However, the practicalities of implementing the EPS system are critical for developing countries as proper regulation of EPS requires a highly mechanized industrial system, and emerging countries are not entirely up-to-date (Demiral et al. 2021;Choi and Cho 2021;Corrocher and Mancusi 2021). Also, the use of existing environmental policies is considered insufficient to make the most of changing emerging nations' political, technological, and financial regimes (Su et al. 2021). Hence, in practice, many emerging economies are considered responsible for increasing the ratio of the ecological deficit by practicing the traditional methods of achieving economic progression due to their inability to enforce ecological policies. Therefore, the present study highlights the importance of EPS at the governmental level and its potential role in reducing environmental degradation to achieve environmental and economic sustainability.

Data description and methodology
Taking the yearly data from 2000 to 2017, the current study explores the nexus of eco-innovation, green finance, and environmental policy stringency with the environmental degradation of China. Ecological footprint has been taken to indicate the quality of the environment in China and obtained through the online source of Global Footprint Network. Due to the non-availability of the data of EFP after 2017, the overall time frame of data is limited to 2017 only. The covariate eco-innovation is retrieved from the website of OECD, indicating the number of patents aligns with the atmosphere of China. The rest of the variables, i.e., green finance, represents the investment in renewable energy; environmental policy stringency is the index that signifies the level of stringent environmental policies. Both variables are taken from International Renewable Energy Agency (IRENA). The variable depiction is also presented in Table 2.
Likewise, Ahmed (2021), the present study utilizes the quadratic-match sum mechanism to convert the yearly data into a quarterly basis to increase the frequency of records. The author highlights the significance of the quadratic match sum method as the procedure circumvents the endwise deviations and adjusts the seasonal deviations of the data points. Furthermore, the empirical analysis is carried out through GAUSS, MATLAB, and E-views software.
The modeling procedures associated with cointegration have been widely discussed in the literature of time series and econometrics (Cho et al. 2015). In the earlier stage, the parametric approach of Engle and Granger (1987) was based on two variables, and various academicians comprehensively documented Johansen's (1988) cointegration method. Later on, the autoregressive distributed lag (ARDL) model of Pesaran and Shin (1998) allows for investigating the data series' short-and long-run dynamics, holding different orders of integration. Similarly, Pesaran et al. (2001)   used the bounds-testing framework to identify long-run relationships among the variables. Keeping in view, the above methods are all parametric and based on conditional means and are unable to portray the comprehensive picture of the conditional distribution of the dependent variable. The seminal work of Xio (2004, 2006) enhanced the discussion of quantile time series regression as quantile estimators are more robust due to their semi-parametric properties (Cho et al. 2015). As mentioned by Koenker and Basset (1978), Kim and White (2003) establish the nonlinear relationship among the regressors possessing heavy tail characteristics and explanatory variables by keeping its asymmetric effects. Furthermore, the quantile-based regression models are built free of statistical assumptions, thus providing a friendly estimation procedure. Xio (2009) extends the concept of quantile cointegration and proposes a novel estimation technique far better than the traditional mean-dependent cointegration methods. Thus, to understand the importance of quantile-dependent relationships, the present study employed the quantile cointegration under the ARDL proposed by Cho et al. (2015), as ecological footprint seems to behave differently at various quantiles. The QARDL method of estimation in accessing the quantile-dependent relationship is appropriate and efficient with robust estimates as compared to standard OLS regression (Zhu et al. 2019;Lahiani 2018).
Before embarking on the QARDL, let us understand the ARDL model of Pesaran and Shin (1998), which can be presented as follows.
where Y t is the outcome variable, X t ∈ B p and t is the residual, i.e., the difference between the estimated dependent variable and the conditional mean of the explanatory variables, m, and n are lag orders identified through any model selection criterion i.e., AIC or Schwarz criterion. Taking the initial from of the model from Eq. (1), the QARDL model for the current study can be written as; More specifically, it can be written as where Q Y t presents the quantiles of ecological footprint lies between 0 and 1. The theoretical quantiles vary from {0.05, 0.95}, and the residual term t ( ) = Y t − Q Y t | t−1 as reported by Kim and White (2003). X1, X2, and X3 are green innovation, environmental policy stringency, and green finance respectively. Analyzing the QARDL process, the model concerning short and long-run dynamics can be rewritten as; (1) where ( ) = ∑ p k=1 k ( )X , R t = ΔX t and k ( ) = − ∑ p−1 v=k+11 k ( ) . The parameters of the above model present the short-run estimates, while the given long-run quantile process obtains the long-run estimates through the plug-in principle. following Zho et al. (2015), below is the model for estimation purposes with a broader picture including the error correction term: where Y and X are the dependent variable and covariates of the study, respectively. is the speed of adjustment required to be significantly negative (Lahiani 2018). Moreover, the short-term effect of past ecological footprints on the current level will be obtained by ∑ m−1 k=1 k ( ) While short-term effect of current and previous levels of eco-innovation (EIN), environmental policy stringency (EPS), and green finance (GFI) on the present level of the ecological footprint will be computed through the estimates of � k ( ) . The notable factor in the above model is that both long-run and shortrun parameters depend on their quantiles showing that the outcome of the model varies across the quantiles, and they are pretentious by the time series realizations, i.e., t ( ).
The QARDL estimates' consistency is further validated through the Wald test of parameter constancy. Furthermore, the granger causality test is employed to investigate bi-direction causality among the variables.

Empirical results and discussions
Starting with the descriptive analysis of the variables (Table 3), it has been shown that EIN holds the highest average mean value, i.e., 4.329, among all the other variables; secondly, EFP and GFI possess the smallest mean effect on China's economy, i.e., 0.36 and 0.345, respectively, while the mean value of EPS is found to be 1.621. Table 3 also reports the variation of the variables, and EFP was found as less discrepancy, but EIN and GFI keep the highest standard deviation as judged against the other variables. Moving towards normality, it has been tested through the JB statistic; likewise, all the estimates are significant at a 1% significance level, with positive kurtosis predicting the non-normal behavior. This is also in line with the study of Suki et al. (2020). (4) The quantile unit root test has been employed to check the stationarity of the data set. Table 4 presents the outcomes of nonlinear quantile unit root for all variables. The dependent variable ecological footprint sounds stationary at first, especially at extreme lower and middle quantiles. Concerning eco-innovation, stationarity is evident at lower and upper quantiles, while green finance shows stationarity at lower quantiles. Furthermore, environmental policy stringency portrays significance at extreme upper quantiles. Overall, the variables are stationary at first difference permitting to move forward the empirical analysis. The non-symmetric nature of the data set urges us to employ the QARDL method for exploring the required objectives. Table 5 reports the long-and short-run estimates obtained through the QARDL method. The error correction term is found to be negative and significant with a constant speed of adjustment at higher quantiles. It has been observed that the rate at which the long-run equilibrium will be maintained is around 35% at significantly higher quantiles, while the term is also showing significance at a 5% level at lower and middle quantiles. As far as eco-innovation is concerned in the long run, it possesses negative and highly significant estimates indicating a strong relationship with an ecological footprint in China. Eco-innovation is positively impacting China as technological advancements in the manufacturing process lead to a healthy atmosphere. These findings are similar to Ahmad et al. (2021), who urge to implement ecoinnovation in the development process as it leaves positive marks on the surroundings.
Looking at green finance in China, the long-run estimates are negative and significant, showing that a 1% upsurge in green technology may decrease the ecological footprints by 1 to 4% at lower quantiles and almost 7% at extremely high quantiles. This outcome is predominant since green finance increases the strength of monetary resources for the financial situation in China as it is an indicator that is beneficial for providing services in the domain of economic development and employing various business models such as banking, investment, and insurance. These results are similar to the findings of Zeng et al. (2022b) and Wang et al. (2021a, b) in the context of China. Furthermore, green finance can be undertaken to decrease the level of ecological footprint, which is also consistent with the outcomes of QARDL. Thus, estimates are put forward that nations have abridged the environmental hazards by moving towards green finance (Chen andChen 2021, Wang et al. 2021a, b;Ali et al. 2021).
Moreover, the long-run estimates for the environmental policy stringency are negative and significant at all the quantiles of the ecological footprint. The impact of the coefficient at lower quantiles is less as compared to the high quantiles, while at the middle quantiles, the coefficients are stable. The 1% increase in the environmental policy stringency leads to a decrease between 5% to 8% at high conditional quantiles of the ecological footprint. The study of Wolde-Rufael and Mulat-Weldemeskel (2021) disclosed that the environmental policy stringency has a U-shape inverted relationship with the ecosystem of 7 emerging economies with the uni-directional causality that is somehow consistent with the present study. The parameter constancy has been obtained through Wald test estimation, and the outcomes are presented in Table 6. All the variables are significant at a 1% significance level; thus, it has been evident that the error correction term is supposed to be nonlinear for the proposed estimation method. βE IN is the long-term integrating parameter found to be highly significant, indicating the rejection of the null hypothesis of parameter constancy. This result leads to the decision that eco-innovation is behaving dynamically at various conditional quantiles of the ecological footprint.
Moving towards the outcome of the granger causality test formerly suggested by Troster et al. (2018) in Table 7. This test has been utilized to explore the causality among the variables under study. It can be seen that there is bi-direction causality among all the variables at various quantiles. It is also evident from the results that ecological footprint has a causal association with eco-innovation, green finance, and environmental policy stringency, while vice versa is also true.
The study outcomes signifies that various efforts have been created to combat environmental pollution in the country through innovative and green infrastructure while spreading green culture in business operations because of its financial reputation . Well, the findings urged

Conclusion and policy implications
Before now, the financial industry overlooked the ecosystem, resulting in environmental issues such as climate change, pollution, loss of natural habitat, natural resource depletion, etc. (Meo and Karim 2022). Due to these issues, the financial industry decided to take action to protect the environment by introducing financial products that protect the environment. Hence, the study's prime objective is to examine the role of green finance, eco-innovation empirically, and environmental policy stringency to leverage sustainability in China. We use time series data from 2000 to 2017 using the QARDL approach introduced by Cho et al. (2015), and Causality-in-Quantiles introduced by Troster et al. (2018) to examine the asymmetric relationship between proposed variables. Based on the QARDL approach, we confirm that there is an asymmetric relationship between proposed variables which is highly quantile dependent; ignoring nonlinearities among series may provide misleading inferences, and traditional models in the presence of asymmetries may provide invalid outcomes. The QARDL approach findings show a negative relationship between Eco-innovation and ecological footprints; however, the size of magnitude is quantile dependent. We also find an asymmetric negative and significant relationship between green finance and ecological footprints. We also find similar asymmetric outcomes for environmental policy stringency and ecological footprints through the Wald test. We confirmed that increasing environmental policy stringency at high quantiles leads to decreased ecological footprints. Furthermore, the findings based on causality-in-quantiles confirm bidirectional causality between eco-innovation, green finance environmental policy stringency, and ecological footprints. Based on the empirical findings of the study, the following are the policy recommendations: 1. Public policies should include funding for technical innovation initiatives, particularly those aimed at developing suitable technologies to provide synergy between more robust economic growth and less environmental deterioration. According to IEA (2022), global electrolyzing capacity recently stands at 0.3 GW using grid electricity to produce hydrogen. Still, commencements of green projects in such economies could help to raise the production of hydrogen through the electrolyzed capacity to around 17 GW by 2026 leading to reduce environmental deterioration. China can play a crucial role in such commencements due to its vast infrastructure and economic skill set. 2. The government should emphasize improving the ecofinancial system, giving eco-friendly endeavors higher priority during approvals, and streamlining application procedures for eco-friendly projects. This requires both public and private sector cohesion in financially integrating the eco-innovation plans with sustainable goals to ensure long-lasting economic sustainability. 3. The empirical findings further indicate that more onerous environmental regulations are effective in China at maintaining the ecosystem; thus, the government should ensure rigorous regulations to address the growing environmental deterioration. Furthermore, there is a vast body of literature on the relationship between macroeconomic factors and environmental degradation. As a result, the literature on ecological footprints can be expanded by investigating the effect of artificial intelligence on ecological footprints. Indeed, the current study elaborates on the various aspect of economic complexity, green finance, and environmental policy stringency on the ecological footprint of China. Yet, there are several limitations of the current study. Due to data scarcity, the frequency of the data is limited; future studies can extend the data range and analyze it in a broader form. Likewise, the study only focuses on China and can be extended to other emerging countries in a single or panel data framework. More sophisticated econometric techniques can be utilized to accomplish the similar objective of the studies. Lastly, the variables augmented with green can also open the venue for future research.

Author contribution
We acknowledge that all the authors participated equally in this paper. Sahar Afshan worked on introduction. Tanzeela Yaqoob worked on analysis and grammar. Muhammad Saeed Meo worked on interpretation and policy recommendation. Bushra Hamid worked on conclusion, policies, and grammar.
Data availability Data will be available upon the request to corresponding author.

Declarations
Ethical approval We verify that we have followed all the ethical standard for the publication.

Consent for publication
We are all agree to get publish this paper in ESPR.

Competing interests
The authors declare no competing interests.