Economic growth, carbon dioxide emissions and energy consumption in Algeria: a wavelet coherence approach. Issue 2 (3rd March 2021)

• Record Type: Journal Article
• Authors: Chekouri, Sidi Mohammed; Chibi, Abderrahim; Benbouziane, Mohamed
• Is Part Of: World journal of science, technology and sustainable development. Volume 18:Issue 2(2021)
• Page Start: 172
• Page End: 189
• Publication Date: 2021-03-03
• Subjects: Energy consumption -- CO2 emissions -- Economic growth -- Wavelet coherence -- Partial wavelet coherence -- Algeria; C5 -- J11 -- O4 -- Q5; Sustainable development -- Periodicals; Appropriate technology -- Periodicals; Technology transfer -- Periodicals; Globalization -- Periodicals; 338.92705
• DOI: 10.1108/WJSTSD-12-2020-0097
• Languages: English
• ISSNs: 2042-5945

Abstract

Abstract : Purpose: The world is nowadays facing major environmental damage and climate change everywhere. Carbon dioxide emissions are major causes of such change. It is in this respect that the current study provides a fresh insight into the dynamic nexus between energy consumption (EC), economic growth (EG) and CO2 emissions in Algeria, as it is considered as one of the top CO2 emitters in Africa. Design/methodology/approach: The authors use the wavelet approaches and Breitung and Candelon (2006) causality test to gauge the association between EC, EG and CO2 emissions over the period 1971–2018. Specifically, this study implements the wavelet power spectrum (WPS) to identify the power and variability of each variable at different time scales. The wavelet coherence, phase differences and partial wavelet coherence are also used to assess the co-movement and lead lag relationship between economic growth, energy consumption and CO2 emissions over different time scale. Finally, Breitung and Candelon (2006) causality test is used to find the causality among variables. Findings: The wavelet power spectrum results indicate that economic growth, energy consumption and CO2 emissions share common strong variance in the medium and long run. Furthermore, the wavelet coherence results suggest that there is a significant co-movement between EG and CO2 emissions, and EG is the leading variable for CO2 emissions and EC. The results also unveil that both EG and EC cause CO2 emissions both in short and long run. The results suggest that Algeria should take suitable measures towards the promotion of renewable energy sources. Originality/value: The present empirical study filled the literature gap of applying the wavelet approach and frequency domain spectral causality test to examine this relevant issue for Algeria.