Malaysia's Renewable Energy and CO₂ Emissions: ARDL-ECM Evidence with Policy and Managerial Implications

This study investigates whether renewable energy (RE) adoption reduces carbon dioxide (CO₂) emissions in Malaysia and under what conditions the effect is durable. We focus on translating empirical results into decisions for Malaysian firms and policymakers, given continuing reliance on coal-fired power and accelerating-but uneven-RE deployment. A quantitative, time-series design is employed using annual national data. An autoregressive distributed lag (ARDL) model and its error-correction representation (ECM) are used to separate short-run dynamics from long-run equilibrium relationships. The dependent variable is CO₂ emissions, with RE, GDP growth (economic scale/EKC context), foreign direct investment (FDI), and forest cover as regressors. Model diagnostics address integration properties, lag selection, and stability. Results show that RE has a negative and statistically significant short-run effect on CO₂-consistent with dispatch substitution in which incremental RE output crowds out marginal coal/gas generation. Long-run elasticities for RE and forest cover are directionally negative but statistically imprecise in the baseline specification, while GDP remains emissions-increasing. The ECM coefficient is negative and significant, indicating relatively fast adjustment toward long-run equilibrium. These findings imply that Malaysia can realise near-term abatement via RE procurement and efficiency measures, but durable decarbonisation requires policy sequences that convert substitution into structural displacement-specifically, competitive RE auctions paired with storage and scheduled coal retirements, complemented by green-halo FDI and credible forest governance. The study contributes Malaysia-specific, horizon-separated evidence that informs both managerial energy procurement choices and the state's transition planning.