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This study utilizes the Autoregressive Distributed Lag (ARDL) method to investigate the impact of electricity intensity (EINT), renewable energy in electricity generation (ERE), and gross domestic product (GDP) on Malaysia's environmental quality, spanning from 1985 to 2020.The research employs carbon emissions (CO 2 emissions) and ecological footprint (EF) as proxies for environmental degradation.The results indicate a signi cant impact of these variables on both CO 2 emissions and EF over the long run.Notably, the study also identi es an inverted U-shaped relationship in both cases (CO 2 emissions and EF) between GDP and environmental degradation, thereby validating the existence of Environmental Kuznets Curve (EKC) hypothesis.The ndings also imply that while electricity intensity is associated with increased emissions, the use of renewable energy (RE) sources for electricity generation may contribute to emission reduction.But the results for both variables show reversal signs on EF.By adopting the fully modi ed ordinary least square (FMOLS) method, the study also showed the same results, thus, justifying the cointegrating relationship between studied variables.Drawing from these outcomes, the study proposes policy recommendations to foster environmental sustainability and economic growth, emphasizing the need for strategic interventions in Malaysia's electricity generation mix and energy policies.
Mohamed et al. (Wed,) studied this question.