Africa's carbon emissions: Probing the economic determinants, forecasting and proposing a roadmap towards carbon neutrality using a machine learning algorithm

Africa faces disproportionate climate impacts despite contributing minimally to global emissions, making effective carbon mitigation policies a developmental imperative. However, despite growing adoption of environmental taxes worldwide, their efficacy in reducing carbon dioxide emissions (CO 2 E) in African contexts remains underexplored, and existing forecasting models have ignored tax policies, rendering their forecasting and mitigation output ineffective for policy making. Thus, motivated by these gaps, this study examined the impact of environmental taxes on CO 2 E for 14 African countries while accounting for renewable energy consumption (REC), economic growth (EG), trade openness (TO), and population size (POP). Additionally, the study forecasted and proposed the CO 2 E mitigation pathways for the studied countries. Utilizing the panel autoregressive distributed lag model, the study found that environmental taxes reduce CO 2 E in Africa in the long run, while POP and EG increase CO 2 E. The results also showed that REC significantly reduces CO 2 E in the short run. Additionally, using the long-short-term memory algorithm, we found that CO 2 E in Africa has an increasing trend, with South Africa, Morocco, Tunisia, Ghana, and Cote D’Ivoire expected to emit the highest CO 2 E by 2030, while Burkina Faso, Mali, Togo, Niger, and Rwanda will emit the least CO 2 E. The study suggested that African policymakers leverage environmental taxes and boost renewable energy (RE) generation to attain a cleaner environment.