Abstract
This study investigates the impact of green technological innovation, environmental policy stringency, and fintech on the ecological footprint in highly emerging economies. Utilizing a balanced panel dataset covering the period 2000–2022, we employ the method of moments quantile regression (MMQR) complemented by FMOLS, DOLS, and FE-OLS robustness estimators to analyze how these relationships vary across different levels of ecological performance. Our findings reveal that both green technological innovation and environmental policy stringency are robust drivers of environmental improvement. Environmental policy stringency consistently reduces the ecological footprint across all quantiles, underscoring its universal efficacy as a policy tool. The impact of green technological innovation is also significant across all quantiles but is most pronounced in economies positioned at the upper quantiles of the ecological footprint distribution, supporting the leapfrogging hypothesis. The role of FinTech is conditional as it significantly reduces the environmental policy stringency in economies with low-to-middle quantiles of the environmental policy stringency distribution, but its effect becomes insignificant at upper quantiles. This suggests a boundary effect where the benefits of FinTech for sustainability are contingent on a sufficiently developed environmental and regulatory framework. Among the control variables, GDP per capita exerts a positive and significant effect on ecological footprint across all quantiles, reflecting incomplete decoupling between economic growth and ecological pressure, while urbanization is associated with a lower ecological footprint, consistent with agglomeration efficiencies and structural shifts in production and consumption. These empirical results present policy implications, highlighting the significance of combining stringent environmental policy with targeted support for green innovation and well-directed digital finance for ecological sustainability in highly emerging economies.