Macroeconomic Determinants of Carbon Emissions in Kenya: An ARDL Approach

Abstract

Environmentally sustainable economic growth portends numerous benefits to developing economies. However, development of energy sources whereas maintaining environmental quality presents diverse challenges. Nevertheless, stakeholders concur on the decisiveness and urgency on adoption of renewable resources and environmentally affable powering of the economy. The primary objective of this study was to examine the macroeconomic determinants of CO2 emissions in Kenya. Specific objectives included determining the effect of economic indicators such as; gross domestic product, population growth and trade openness on carbon emissions in Kenya. The study also analysed the effect of energy mix such as; Energy generated from renewable sources, fossil fuel sources, Alternative and Nuclear Energy sources and Imported Energy on carbon emissions in Kenya. The study spanned from 1970 to 2015, relying on data from Energy Information Administration database and World Bank’s World Development Indicators database. The study utilized the Autoregressive Distributed Lag (ARDL) model to analyse the dynamic interactions and to estimate the long-run and short-run relationships amongst the variables under study from the ECM. The Augmented Dickey Fuller and Philip Perron determined that gross domestic product was stationary at level with the rest of the variables stationary at first difference. The models did not exhibit multicollinearity and normality assumptions which were tested by VIF test and Lomnicki-Jarque-Bera test for normality respectively. The results established that in the long run, changes in population growth (p – value 0.001 < 0.05), gross domestic product (p – value 0.031 < 0.05) and trade openness (p – value 0.001 < 0.05) have significant effect on CO2 emissions. Further, results indicated that except renewable energy (p – value 0.326 > 0.05), fossil fuel (p – value 0.001 < 0.05), alternative and nuclear energy (p – value 0.042 < 0.05), imported energy (p – value 0.012 < 0.05) have significant effect on CO2 emissions in Kenya. In the short run carbon IV oxide, fossil fuels, imported energy, alternative and nuclear energy had coefficients of 0.3600, 0.9907, 0.6753, and 0.0899 all significant at 5% level of significance respectively. Gross domestic product, population growth and trade openness had coefficients of 0.034934, 12.8319 and -0.5133 significant at 5% level of significance. Except for trade openness with a negative coefficient all other variables had positive coefficient hence contribute to increase in carbon emissions. The adjustment coefficients were -0.62482 and -0.40046 significant at 5% level of significance indicating presence of short run adjustments and a long run equilibrium. The study proposes adoption of trade policies restricting high carbon emitting products and more tax incentives to products with less carbon emissions. Adoption of energy sources with low carbon IV emissions such as solar and wind will reduce the use of fossil fuels consequently reducing carbon emissions.