A Decomposition Analysis of Carbon Emissions from Energy Use in Pakistan: The Application of Additive Logarithmic Mean Divisia Index and Tapio Decoupling Elasticity Approach

To reduce carbon emissions and mitigate their effects on climate change, it is essential to understand the sources that contribute to these emissions. This study aims at examining the factors driving carbon emissions in Pakistan from 1990 to 2019 by applying Additive Logarithmic Mean Divisia Index-1 decomposition approach. The results reveal that population size and affluence both contribute significantly to rising carbon emissions over time. This indicates that as the population grows and people become more affluent, they consume more energy, which results in increased carbon emissions. The aggregate impact of population size on carbon emissions increased to 12.92 Mtons from 1990-2019, far greater than the impact of other factors. Pakistan also experienced economic activity per person growth as a significant contributing factor to increasing emissions; the trend increased annually, and the cumulative effect reached 8.78 Mtons in 2019. Carbon intensity and renewable energy penetration contribute positively to carbon emissions, indicating a falling share of renewable energy. Contrary to this, the energy intensity effect is nearly stable during the period of analysis. The fuel-switching effect, however, is found to reduce carbon emissions. Moreover, Tapio¡¯s decoupling status reveals that Pakistan has faced four out of eight decoupling states during the period of analysis. The most notable among them is the expansive negative decoupling state (as > 1.2), which points towards a much faster increase in emissions than GDP growth. Carbon emissions due to the use of bituminous coal have increased significantly since 2013. Overall, the study suggests that if a country¡¯s GDP growth rate is low and carbon emissions are high, the country should pursue concessional international climate finance and sponsors to invest in green technologies and national capital restoration programs.