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

JEL CLASSIFICATION:

• C5
• J11
• O4
• Q5

Disclosure statement

No potential conflict of interest was reported by the author(s).