Digital inclusion and environmental taxes: A dynamic duo for energy transition in green economies

Transitioning to sustainable energy is a global imperative for countries to develop policies to achieve Sustainable Development Goals (SDGs), particularly SDG 7 and 13. Given the possible association between digital inclusion (DIGI) and the energy transition (EGTN), we examined the impact of DIGI on the EGTN while controlling for environmental taxes (ENTX) in the top-5 greenest economies in the world using quarterly data from 2001 to 2021. We examined the association at short-, medium-, and long-term frequencies using comprehensive approaches such as the Method of Moments Quantile Regression (MMQR) for panel analysis and Wavelet techniques, i.e., wavelet coherence, multiple wavelet, and partial wavelet for country-specific assessment. According to the MMQR results, DIGI has a significant and positive effect on EGTN, with a coefficient value ranging from 10.95 to 5.980 while moving from lower (0.25) to higher (0.95) quantiles. Similarly, ENTX has a positive and significant effect on EGTN, with a coefficient value ranging from 1.770 to 3.132 as the quantiles increase. In addition, the results of wavelet coherence expose a strong and positive connectedness between DIGI and EGTN in each sample country. Furthermore, multiple wavelet results for each country demonstrated that ENTX significantly strengthens the interaction between DIGI and EGTN. Our findings result in developing SDGs-oriented policy guidelines, specifically the policy strategy for addressing SDG-7 and SDG-13. The study endorses that the sample countries take initiatives to accelerate the EGTN process by improving digital inclusion and implementing an effective environmental taxation system. •We evaluated the role of digital inclusion on energy transition.•The study also considers the role of environmental taxes.•The study employed panel data from 2001 to 2020 for the greenest economies.•Digital inclusion and environmental taxes promote energy transition.•The panel results are validated by the wavelet analysis.