DETERMINANTS OF RENEWABLE ENERGY CONSUMPTION IN AFRICA

Abstract

Increasing global demand for energy security and sustainable development has necessitated the need for a paradigm shift from fossil fuel energy sources to renewable energy sources in Africa. A sizeable number of African countries have set targets for the share of their electricity generation from renewable energy sources between 2020 and 2030. However, there is a dearth of information on the current pattern of renewable energy consumption as well as its key drivers in Africa. This study was therefore designed to investigate the determinants of renewable energy consumption in Africa, with a view to understanding the current pattern and its potential determinants.

The study employed panel data analysis involving five most populous and biggest economies in each of the five regions of Africa namely; Nigeria (West), Egypt (North), Ethiopia (East), DR Congo (Central) and South Africa (Southern) with annual data from 1990 – 2015 using REit = β0 + EIitβ1 + ORit β2+ CRit β3+ NGRit β4 +CIit β5 + 𝞮it. Carbon intensity (kilogram per kilogram of oil equivalent energy use), oil rents (percentage of GDP), gas rents (percentage of GDP), coal rents (percentage of GDP) and energy intensity (mega joules per unit of GDP) were considered as potential drivers of renewable energy consumption. Empirical analysis involved the estimation of both fixed effects and random effects models, while the Hausman test was employed for selecting the appropriate panel model and was significant at p ≤ 0.05 with R-squared of 0.2311.

The renewable energy consumption in the five countries combined represents 60.2% of total African consumption. The variances across countries are ZERO for the null hypothesis and there is no evidence of any significant differences across the countries which mean that there is no panel effect. The key drivers of consumption were found to be carbon intensity, oil rents, coal rents, natural gas rents and energy intensity. The variables were all stationary at levels, they were integrated of I(0). The random effect model could not be accepted indicating that the appropriate model that fits the data was the fixed effect model. From the result, the F-Statistics test value of 94.15 implies that the determinants jointly account for the variation in renewable energy consumption in the selected African countries. The adjusted R-squared value of 0.6227 implies a good fitness of the model and that all the explanatory variables can explain for about 62.3% variation in renewable energy consumption. Energy intensity is inversely related with renewable energy consumption. Oil rent, Coal rent and Carbon intensity yields a significant and negative relationship with renewable energy consumption. However, natural gas rent revealed a positive and a significant relationship with renewable energy use in Africa.

These countries should charge higher tax rate for fossil fuels and thereby subsidize the development and use of renewable energies as a result of carbon intensity which was found to be a key determinant of renewable energy consumption in Africa . Similarly, for oil and coal rents, African countries need to diversify fossil fuels price risk and support the funding of renewable energy development.