Nelson Amowine

Achieving carbon neutrality is a tedious challenge confronting African countries that have witnessed mounting environmental degradation. Renewable energy consumption (REC) and forestation play a critical role in dealing with the situation. Therefore, to address this concern, this study assesses the dynamic energy or environmental efficiency of 43 sampled African countries by proffering a new dynamic meta-frontier DEA model from 2010 to 2018. The bootstrap truncation regression model investigates the influence of forestation and REC on environmental efficiency in Africa. The dynamic environmental efficiency of the 43 concerned African countries is low (0.59), indicating vast room for improvement. The heterogeneity of dynamic environmental efficiency across the income groups is evident. The upper-middle-income group (UMIG) had the best performance, followed by the low-middle-income group (LMIG) and the low-income group (LIG). The technology gap ratio also confirmed the existence of a huge gap across the income groups in Africa. The bootstrap truncation regression results confirmed a U-shaped relationship between economic growth and dynamic environmental efficiency in Africa. Forestation and REC positively correlate to dynamic CO₂ emission and energy efficiency in Africa. In contrast, financial development is negatively associated with CO₂ emissions and Africa’s energy efficiency. The study’s findings will aid the sampled African countries in their quest to attain carbon neutrality, thereby promoting sustainability on the African continent.

Ecological footprint (EF) and human development index (HDI) are two critical indicators for assessing sustainable development worldwide. Past studies in Africa have ignored dynamic sustainable total-factor ecological efficiency (DSTFEE) assessment. This present study proffers a novel dynamic sustainable total-factor ecological efficiency (DSTFEE) that comprehensively assesses the ecological efficiency among 44 sampled African economies from 2010 to 2016. Our study incorporates EF and HDI in the model. Second, the study evaluates regional DSTFEE heterogeneity efficiency as well as the technological gap efficiency in Africa. Further, projection analysis is done to offer a viable solution path to address the inefficient African countries. Third, the study investigates the determinants of ecological efficiency using the bootstrap truncation regression technique. The results from the implemented models are as follows: first, the DSTFEE for the 44 sampled African countries is very low (0.403), indicating enormous potential for improvement. Second, the heterogeneity of DSTFEE across the five Africa regional blocs is evident. The southern bloc had the highest efficiency score, followed by the northern, central, western, and eastern regions. The technology gap ratio also reveals a massive gap among the five Africa regional blocs. Third, the bootstrap truncation regression results established a U-shape nexus between growth and DSTFEE in Africa. REC and trade openness is positively corrected to DSTFEE for African countries. In contrast, financial development, foreign direct investment (FDI), and urbanization impede dynamic ecological efficiency in Africa. The study’s results equip African countries with adequate knowledge of their ecological efficiency situation and provide them a viable path to improve environmental efficiency, thereby boosting their ecological sustainability.