Climate change poses a significant threat to sustainable development, prompting global concerns about environmental degradation and the need for sustainable economic growth. The rise in greenhouse gas emissions, particularly CO2, is linked to increased fossil fuel use driven by industrialization. Technological innovation (TIN) and information and communication technology (ICT) play crucial roles, with potential for both increasing and decreasing energy consumption and emissions. Malaysia, aiming for a 45% reduction in GHG emissions intensity by 2030 and carbon neutrality by 2050, faces challenges in balancing economic growth with environmental sustainability, particularly given its shift from agriculture to industry and the growing energy-intensive services sector. While existing research has explored environmental degradation in Malaysia, few studies have combined the impacts of sustainable EG, TON, ICT, and TIN on CO2 emissions using both symmetric and asymmetric methodologies. This study aims to fill this gap by examining the complex interplay of these factors in Malaysia, offering a holistic understanding of their combined effects and providing policy recommendations for emissions mitigation.

The literature review examines existing research on the relationship between technological innovation, economic growth, trade openness, ICT, and CO2 emissions. Regarding technological innovation, studies show mixed results, with some indicating a negative correlation between TIN and CO2 emissions due to increased resource efficiency and cleaner technologies, while others suggest a positive correlation due to increased energy consumption. The relationship between economic growth and CO2 emissions is widely documented, often exhibiting an environmental Kuznets curve (EKC). Trade openness displays a dual effect, potentially reducing emissions through technological changes but increasing them due to increased economic activity and production. ICT's impact is also complex, with potential for both emissions reduction (through improved energy efficiency and environmental management) and increase (due to increased energy demand from devices and infrastructure). The review highlights the need for a comprehensive analysis incorporating both symmetric and asymmetric relationships to fully understand the dynamic interaction of these factors.

This study employs both the Autoregressive Distributed Lag (ARDL) model and the Nonlinear ARDL (NARDL) model to analyze the relationship between CO2 emissions (dependent variable) and EG, TON, ICT, and TIN (independent variables) in Malaysia from 1985 to 2021. Data was sourced from the World Development Indicators (WDI). The ARDL model allows for examination of both short-run and long-run relationships, while the NARDL model further explores asymmetric effects by distinguishing between positive and negative changes in the independent variables. The study employed several econometric tests including unit root tests (ADF, DF-GLS, PP), cointegration tests (ARDL bounds test), nonlinearity tests (BDS test), and diagnostic tests to assess the validity and reliability of the models. The NARDL model was developed by decomposing changes in EG, ICT, and TIN into positive and negative components. The study also employs causality tests (Granger causality test) and robustness checks (FMOLS, DOLS, CCR) to further strengthen the findings.

The symmetric ARDL analysis reveals a positive and significant relationship between EG, TON, and ICT and CO2 emissions in both the short and long run. Technological innovation (TIN), however, shows a significant negative impact on CO2 emissions only in the short run. The asymmetric NARDL analysis demonstrates that the long-term effects are asymmetric. Positive shocks to EG significantly increase CO2 emissions, while negative shocks have a less significant impact. Positive shocks to ICT also increase CO2 emissions, but negative shocks have a larger negative impact. Positive shocks to TIN significantly reduce CO2 emissions, whereas negative shocks have a less significant negative or even slightly positive effect. The long-run causality test shows bidirectional causality between TON, TIN and CO2 emissions, and a unidirectional relationship from ICT to CO2. Robustness checks using FMOLS, DOLS, and CCR estimations confirm the long-run findings of the ARDL model for EG, TON, and ICT.

The findings highlight the complex and multifaceted relationship between economic development, technological progress, trade, ICT, and environmental sustainability in Malaysia. While economic growth and trade openness contribute significantly to CO2 emissions, technological innovation plays a critical role in mitigating these emissions, particularly in the short run. The asymmetric effects underscore the importance of considering the direction and magnitude of changes in these factors. The positive relationship between ICT and CO2 emissions might be attributed to the energy-intensive nature of ICT production and use, suggesting a need for sustainable ICT practices. The causality analysis further solidifies the crucial role of policy interventions in influencing the emission levels and achieving sustainability goals. The robustness checks support the overall findings, lending confidence to the interpretation and reliability of the results.

This study provides valuable insights into the dynamic relationships between technological innovation, economic growth, trade openness, ICT and CO2 emissions in Malaysia. The findings highlight the need for a balanced approach to economic development and technological advancement, emphasizing the crucial role of clean technologies and sustainable ICT practices. Policy interventions to incentivize cleaner technologies, implement carbon pricing mechanisms, improve energy efficiency and foster public awareness are recommended. Future research could explore the role of specific policy instruments, examine the impact of different types of technological innovation, and conduct a comparative analysis across different countries and regions.

This study has some limitations. Firstly, the analysis focuses solely on Malaysia, limiting the generalizability of the findings. Secondly, the study only considers a specific set of variables; inclusion of other relevant factors, like renewable energy consumption and environmental regulations, might offer a more complete picture. Thirdly, the analysis focuses on two specific econometric techniques. The use of alternative models could provide additional insights. Finally, data limitations might influence the results and interpretation.