Examining the driving factors of CO2 emissions using the STIRPAT model: the case of Algeria

Abstract

In order to curb carbon emissions and develop a low carbon development plan in Algeria, it is crucial to shed light on influencing factors of carbon emissions. In view of this, a stochastic impact by regression on population, affluence, and technology model is conducted to identify the determinant factors driving CO2 emissions in Algeria during the period 1971–2016. The method of partial least squares regression is applied to eliminate multicollinearity problems. The results indicate that the population has a positive and significant effect on CO2 emission. The energy use is found to be the second most contributing factor to CO2 emissions followed by urbanisation and affluence (GDP per capita).

Keywords

• co2 emissions
• urbanisation
• stirpat model
• partial least squares regression (pls)
• variable importance in projection (vip)
• algeria