Modelling the asymmetric effects of renewable and nonrenewable energy consumption and financial development on CO2 emissions in India: Empirical findings from the NARDL and Wavelet Coherence Approach.

A major challenge for humans in the twenty-first century is devising a way to minimize environmental pollution while fostering economic growth that will not deplete the planet's resources. Despite increased awareness of climate change and efforts to combat it, the amount of pollution emissions on the Earth continues to drop significantly. This study employs cutting-edge econometric methods to examine the long- and short-term asymmetric and causal impacts of renewable and non-renewable energy consumption and financial development on CO 2 emissions in India at both aggregate and disaggregated levels. Thus, this work fills a significant gap in research. A time series from 1965 to 2020 was used for this study. Wavelet coherence was employed to investigate causal effects among the variables, while the NARDL model addressed long-run and short-run asymmetry effects. Our findings indicate that (i) REC, NREC, FD, and CO 2 emissions are all interconnected in the long run, (ii) NREC and FD significantly trigger CO 2 emissions in India in the long run, and (iii) the results of a wavelet coherence-based causality test support the long-term estimates of this study.