Rapid technological transformation has reshaped production systems and economic activities, creating new opportunities to improve environmental sustainability. The environmental impacts of Financial Technology (FinTech), Digitalization (Dgtl), Information and Communication Technology (ICT), and Green Technology (Gtech) are, however, not homogeneous and can differ significantly depending on the level of carbon intensity; therefore, existing average-effect estimates cannot fully represent the non-linear relationships. In this study, we examine the asymmetric and heterogeneous effects of FinTech, Dgtl, ICT, and Gtech on Carbon Intensity (CI) in China from 2000 to 2022, using annual data. For the empirical analysis, we employ Quantile on Quantile Regression (QQR), Multivariate QQR (MQQR), Wavelet Coherence (WC), and Wavelet Quantile Correlation (WQC) to measure coherence across short-, medium-, and long-run periods for the full sample period. Our results highlight that at lower quantiles, FinTech exhibits weaker and insignificant effects on CI. Furthermore, the results indicate that the effect of Dgtl is mostly negative on CI, especially at high emission quantiles. Concurrently, ICT exhibits a nonlinear, more complex pattern, unlike other variables. In comparison, Gtech shows the strongest and most stable negative effect among all explanatory variables across almost all quantiles of the CI. Moreover, findings from MQQR reveal that the overall effect of the technological ecosystem is more emission-reducing than the individual impact of these variables as found in the conventional QQR. Our study carries useful implications for policymakers and regulators. The results are quite consistent with several Sustainable Development Goals (SDGs), especially SDG 7: Affordable and Clean Energy, SDG 9: Industry, Innovation, and Infrastructure, SDG 12: Responsible Consumption and Production, and SDG 13: Climate Action. The findings underscore the significance of FinTech, Digitalization, ICT, and Green Technology in supporting the transition to energy-efficient and low-carbon economic systems in China.
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Tariq et al. (2026) studied this question.
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