Carbon Dioxide Emissions, economic growth and energy mix: empirical evidence from 93 countries

This paper provides an empirical analysis of CO2 emissions and economic growth, based on a panel dataset covering 93 countries over the period 1960-2008, and examines the challenge of country selection for homogeneous and appropriates groups. We have proposed a no parametric hierarchic clustering approach, based on 17 categorical variables, used the Multiple Correspondence Analysis (MCA) and the Hierarchical Clustering on Principal Components (HCPC). We have began ecnometric modeling by some model specification tests: parameters’ homogeneity, the unit root (IPS procedure) and Pedroni's cointegration tests. Finally Dynamic Panel Data and WITHIN models were estimated to explain the growth rate of per capita CO2 emissions. The results of the clustering indicate the optimal partition of 93 countries into 7 groups, each with its own characteristics. The unit root and cointegration tests show that the long-run relationship does not exist for any clusters and the nature of stationary is different between and into the groups. It’s found that the growth rate of per capita CO2 emissions depends positively on the growth rate of per capita GDP (short-run elasticity is between 0.3 and 0.79) and negatively on the growth rate of energy mix (between -0.025 and -0.13).