Decomposition analysis of electricity generation on carbon dioxide emissions in Ghana

Abstract

This study analyses the factors driving CO2 emissions from electricity generation in Ghana from 1990 to 2020. Employing Logarithmic Mean Divisia Index (LMDI) and Autoregressive Distributed Lag (ARDL) techniques, the research decomposes electricity generation into different factors and assesses their impact on CO2 emissions, considering both short and long-run effects. The LMDI analysis reveals that the total CO2 emissions from electricity generation amount to 3.33%, with all factors contributing positively in each subperiod. Notably, fossil fuel intensity, production, and transformation factors exhibit substantial contributions of about 1.16%, 0.49%, and 0.48%, respectively. Contrastingly, the ARDL results highlight that only electricity intensity and production factors significantly increase CO2 emissions by about 0.20% and 0.09% (0.38% and 0.10%) in the short-run (long-run), while other factors contribute to a reduction in electricity generation emissions. Overall, we conclude that electricity intensity and production factors are the primary drivers of CO2 emissions from electricity generation in Ghana. Nevertheless, effective measures to address all decomposition factors is crucial for effective mitigation of electricity generation CO2 emissions.

Keywords

• Electricity generation
• CO2 emission
• ARDL technique
• Decomposition analysis
• Logarithmic mean divisia index