Factorial decomposition of CO2 emissions: A generalized Divisia index approach

- A generalized Divisia index method (GDIM) is introduced.
- The generalization allows for the inclusion of the interconnected factors.
- Applied as a tool of factorial analysis of the CO2 emissions
- Factors: GDP, energy, population, carbon intensities, GDP/Population, Energy/GDP
- The suggested model extends the Kaya identity as well.

This paper introduces a novel approach to estimating the impact of the major factors driving CO2 emissions: GDP, energy consumption, population, their carbon intensities, and other related indicators that may be chosen arbitrarily. The suggested approach is based on the generalization of the Divisia index to interconnected factors. The approach also extends the Kaya identity by explicitly including Gross Domestic Product and energy consumption. A computer program in R language aimed at automating the calculations is supplied. Factorial analysis of the United States' and China's CO2 emissions is provided as an example of application.