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.

Renewable Energy, ARDL, ECM, CO₂ Emissions

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