Economic growth, carbon dioxide emissions and energy consumption in Algeria: a wavelet coherence approach

Abstract

PurposeThe 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/approachThe 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.FindingsThe 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/valueThe 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.

Nexus between renewable energy consumption, economic growth, and CO2 emissions in Algeria: New evidence from the Fourier‐Bootstrap ARDL approach

“…They show unidirectional causality from renewable energy to CO 2 emissions in the long term. Chekouri et al (2021) use a causality test to give new insight into the dynamic nexus between energy consumption, economic growth, and CO 2 emissions in Algeria from 1971 to 2018. They found that energy consumption causes CO 2 emissions both in the short and long run and suggest that Algeria should take appropriate steps to encourage renewable energy sources.…”

“…In contrast, Amri (2017a) shows an insignificant impact on environmental improvement. Further, Mehdi and Slim (2017), Sari Hassoun et al (2019), and Chekouri et al (2021) reveal that there is a unidirectional causality running from renewable energy consumption to CO 2 emissions. In comparison, Rahmane et al (2021) find a two‐way causal relationship.…”

The Economic Value of Water Ecology in Sponge City Construction Based on a Ternary Interactive System

“…The impact factor of sponge city speed on economic growth in lag three is also positive, with a coefficient of 0.2160; this is significant at a 5% confidence level, thus proving that sponge city construction also contributes significantly to economic growth, mainly because of the scale effect of urban industry and the modernization of agriculture in the countryside. Moreover, this contributes significantly to the economic development of the northern region [ 57 , 58 , 59 , 60 , 61 , 62 , 63 ].…”

CO2 emissions and economic growth: Assessing the heterogeneous effects across climate regimes in Africa

“…In the STD region, growth in Co2 per capita is negative (-1.29%), yet its growth in GDP per capita (3.55%) is higher than that of WTM (3.17%). Despite the existence of different climate regimes in Africa, existing studies on the nexus between climate change and economic growth (Abid, 2016;Chekouri et al, 2021;Olubusoye & Musa, 2020;Omotor, 2016;Yusuf et al, 2020) have ignored the heterogeneous effects of climate regimes and indeed temperature variations. Attempts to account for specific conditions are restricted to the country's levels of development (Olubusoye & Musa, 2020), oil-producing countries (Yusuf et al, 2020), and geographical regions (Demissew Beyene & Kotosz, 2020;Omotor, 2016).…”

“…To capture the heterogeneous effects based on climate regime criterium, we utilise the wavelet methods. Contrary to several empirical studies in Africa (see, for example, Abid, 2016;Chekouri et al, 2021;Olubusoye & Musa, 2020;Omotor, 2016;Yusuf et al, 2020), in this study, we adopt the wavelet coherence transform, multiple wavelets and the partial wavelet analysis for decomposing the time in different time scales. The wavelet method has a consistent set of advantages compared to classical time domains.…”