ECONOMIC GROWTH, ENERGY UTILISATION AND CARBON DIOXIDE EMISSIONS

Abstract

Upon scientific investigation, this research fits into the concepts of rational thinking and mathematical intuition. The study focuses on Economic Growth, Energy utilisation and Carbon dioxide Emissions of Sub-Saharan African and North African regions. The crux of the study is to identify the inflection points and also shows the Carbon dioxide or the CO₂ saturation levels (at maximum or minimum) through the Weibull growth model for fifteen (15) middle-low income African nations. The study adopts a stratified sampling technique for the 15 economies;3 each from the aforementioned regions.Secondary sourced material was retrieved mainly from the World Bank Development Indicator dataset (2023), from 1990 through to 2022. Employed variables for empirical evaluations are the dependent variable;CO₂ emissions per capita (proxy for Greenhouse gas pollution and environmental pollution), and the independent variables; Gross Domestic Product per capita (economic growth proxy), fossil fuel usage , energy use of oil equivalent, electric power consumption and renewable energy consumption (proxies for energy). The panel unit root test at first and second difference revealed a level of stationarity within the model (for each African region under review). Panel Kao co-integration also revealed the existence of a long run equilibrium relationship between the dependent and independent variables in the series. Results from Panel Ordinary Least Squares (Long-run) shows the non-existence of the Environmental Kuznets Curve relationship for nations tested under the Northern and Southern African regions. Hausman diagnostics approves the fixed effects model as a result of a less than (<) 5% significance in Chi-square probability value. Judging by the outcome, the pooled Ordinary Least Squares and random effects model were dismissed, while result of the fixed effects availed in the test of hypothesis. Based on our findings from the fixed effects test, the independent variable; energy use (oil equivalent per capita) at a p- value of  71%,and the controlled variable; agricultural value added (% of GDP) at a p-value of 9.5% > 5% significance level, contributes negatively to the Carbon dioxide emissions of SSA and North African regions.Panel Wald statistics admits the absence of short run causality in the regions running from the independent variables to the dependent variable in the model and respective Chi-square p-values at 0.000 < 0.05 level, implies a sequence of statistical significance in the model. The WGM at inflection point reveals that SSA and a NA nation under Group A, emits the least carbon dioxide. Group B, suggests the most carbon emitters are from SSA and a North African nation. This led to the non acceptance of the null hypothesis (H₀6), for the Weibull system. In conclusion, WGM is an alternative and adaptable tool to identify the inflection or turning points of any given nation, especially where there is evidence of environmental pollution being linked to industrial and economic growth. Highlights of our recommendations include; institutionalisation of green energy that can integrate key private and public activity sectors for  better livelihood of Africans, abolishment of deforestation practices and preservation of natural agricultural resources for future gains, promoting low carbon products in African countries recording the most CO₂ emissions and prime investments in renewable energy to tackle environmental decay, achieve net zero emission target and econological development in the dark continent.