The Potency of Eco-Innovation, Natural Resource and Financial Development on Ecological Footprint: A Quantile-ARDL Based Evidence from China

Given the alarming deterioration of the environment, the present analysis investigates the role of 38 eco-innovation, natural resources and financial development in influencing the environmental 39 degradation of China. Applying the novel method of Quantile-ARDL, the current research is 40 beneficial in portraying the dependence patterns of the variables with special emphasis on the 41 nexus of eco-innovation and ecological footprint across numerous quantiles of the distribution 42 which has not been examined so far in the literature. The empirical findings reveal that in the long 43 run, eco-innovation reduces the level of ecological deterioration in China across all quantiles. On 44 the other hand, the results suggest that the increase in credit to the private sector and natural 45 resource rents augment environmental degradation. The outcomes imply that the over-dependence 46 on natural resources and financial development can worsen the goals of sustainable development 47 in China if the strategies of conservation and management are ignored. Moreover, witnessing the 48 favourable role of eco-innovation, competent policies and regulations can be made towards 49 sustainable efficient technologies and eco-friendly energy sources to halt global warming. Graphical Abstract


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The emission of the green-house gases is cumulating every day, results in the rise of global 62 warming that ultimately responsible for environmental degradation on earth. Among the many 63 other global encounters, dreadful environment is one of the principal challenges of this century 64 (Li, 2016). In compliance to increasing global competition, many countries are urging to increase the Chinese economy. China has been successful in maintaining the crucial global position being 101 the fastest growing nation and largest manufacturing and exporting economy. However, despite 102 the substantial growth driven policies, the country is considered as the prime carbon emitter in the 103 World (Guo et al. 2019). Given its huge population, China also tops in terms of total ecological 104 footprint around the World. Hence, the current study is significant to analyze the environmental 105 degradation in China since the country is augmenting its focus on innovation and Made-in-China 106 narrative, for which economic and environmental sustainability play significant part. Also, it gives 107 more attention to strong and stable financial structure in order to strengthen the association 108 between real and financial sector of the economy which is prime to resource management and 109 technology innovation. 110 The current study is novel in many ways. First, it seeks to expand EKC theory by incorporating 111 the fundamental aspect of eco-innovation. To the best of our knowledge, the present study is resources, in terms of long-run and short-run dynamics, Quantile ARDL provides the best 137 parameter estimation method for several quantiles of ecological footprint. In order to access the 138 behavior of fat-tail dependent variable by taking its conditional distribution and explore its 139 association with explanatory variables by capturing its asymmetric effects, Quantile ARDL 140 technique is best suited. Lahiani (2018) asserts the significance of Quantile ARDL in the 141 framework of co integration as it empowers the parameters of co integrated vector to vary across 142 the quantiles of ecological footprint arises from structural changes in the time series variable.

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Furthermore in making policy strategies this technique provides us an opportunity to observe the behavior of innovation at low as well as high quantiles in detail. Due to such benefits QARDL considers one of the sophisticated methodologies to explore the association among the variables 146 in the frame work of co integration in depth.  The comparative study between symmetric and asymmetric ARDL by Ahmed et al. (2021) 182 also explored the link between economic globalization, economic growth, financial development Furthermore, utilizing the delta approximations, the additive short-term influence of

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To fulfil the required objective of the present study, preliminarily analysis of the data by 314 descriptive statistics and unit root testing methods has been employed followed by Q-ARDL 315 model. Table 1    The evidence of highly skewed data points and confirmation of I (1) variables leads the 335 analysis towards Q-ARDL framework. Table 3 reports the empirical findings of the model.

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Looking towards the error correction terms at each quantile it founds to be negative and highly 337 significant with uniform speed of adjustment i.e. around 40% rate to maintain its equilibrium It is also noteworthy that financial development is seems to be positive and significant at all    Note: The t-statistics are between brackets. ***, ** and * indicate significance at the 1%, 5% and 10% levels, respectively. Source: Author Estimations Table 4 reports the parameter constancy outcomes accessed through Wald test. The null hypothesis 406 of linearity in error correction term is rejected at 5% level of significance in the scenario of China.

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Similarly the long-term integrating parameter βEIN has been tested for the parameter constancy for 408 all quantiles and it found to be significant. This result may assert that the long term relationship