Reinvestigating the EKC hypothesis: Does renewable energy in power generation reduce carbon emissions and ecological footprint?

Abstract

For a developing nation such as Malaysia with a significant reliance on fossil fuels for electricity, understanding the environmental consequences of this dependency is crucial. Thus, this study utilizes the Autoregressive Distributed Lag (ARDL) method to explore the impact of electricity intensity (EINT), renewable energy in electricity generation (ERE), and gross domestic product (GDP) on Malaysia's environmental quality, from 1985 to 2020. By using carbon emissions (CO2 emissions) and ecological footprint (EF) as proxies, the study finds a significant long-run impact of these factors on environmental degradation. Notably, the study also observed an inverted U-shaped relationship between GDP and environmental degradation, validating the existence of Environmental Kuznets Curve (EKC) hypothesis. The findings 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. The study's adoption of the fully ordinary least square (FMOLS) method reinforces the same results, thus, justifying the cointegrating relationship between studied variables. Drawing from these outcomes, the study advocates for a comprehensive approach to renewable energy management, emphasizing both its utilization and waste in order to improve ecological footprint. Moreover, the pressing need to enact legislation on energy efficiency and conservation is crucial in ensuring decoupling and securing sustainable development in Malaysia.