scholarly journals The Relationship between Economic Growth, Energy Consumption and CO2 Emission in the Middle East and North Africa (MENA)

2021 ◽  
Vol 21 (2) ◽  
pp. 132-147
Author(s):  
Mohammed Touitou

Abstract Research background: CO2 emissions are considered to be the main reason for global warming, and for this reason, their regulation is a very important issue for governments. Due to the increasing use of energy, carbon dioxide emissions have increased dramatically over the past century, with a direct link to economic growth and development. The relationship between CO2 emissions, growth and energy consumption is therefore at the heart of current economic issues. Purpose: This study aimed at examining the relationship among economic growth, carbon dioxide (CO2) emissions and energy consumption in selected MENA countries, in the period 1995–2017. Research methodology: To prove these relations, a stationary data panel methodology is used supported by unitary root and cointegration tests. Results: The results indicated that there is a long-term relationship between CO2 emissions, energy consumption and GDP. In addition, it is found that the elasticity of CO2 emissions with respect to energy consumption is less than one (inelastic), and the elasticity of CO2 emissions with respect to GDP suggests the existence of an Environmental Kuznets Curve. An important finding is that energy consumption has a positive but relatively low effect on CO2 emissions. To reduce CO2 emissions, the countries of the MENA region are being called upon to increase significantly the use of renewable energies and the establishment of a more efficient energy policy.

2020 ◽  
Vol 8 (2) ◽  
pp. 1 ◽  
Author(s):  
Nur Hafizah Mohammad Ismail

Southeast Asia countries have experienced rapid economic growth within past decades with significant increase in energy dependency and carbon dioxide (CO2) emissions. Continuous development in urban area has stimulated rise in energy consumption in many Southeast Asia countries which resulted in an improvement of citizen’s lifestyles and living standards due to increasing income and population. Understanding the relationship between economic growth, energy consumption and carbon dioxide emissions helps economies in formulating energy policies, enhancing energy security and developing a sustainability of energy resources. Therefore, this study focuses on the economic growth, energy consumption and carbon dioxide emissions evolved in Southeast Asia by using Environment Kuznets Curve theory. This paper could be useful and beneficial for the Southeast Asia countries to form appropriate environment policies in order to maintain the balance of energy demand and supply and dealing with environmental quality issues.   


2020 ◽  
Vol 66 (No. 4) ◽  
pp. 183-192 ◽  
Author(s):  
Abrham Tezera Gessesse ◽  
Ge He

This study examines the nexus of carbon dioxide (CO2) emissions, energy consumption (EC) and gross domestic products (GDP), using an Autoregressive Distributed Lag (ARDL) bounds test approach of co-integration and error-correction model (ECM) for the period 1971–2015. The aim of the research is to i) examine the relationship between CO2 and GDP as “cross-coupling, relative decoupling, or absolute decoupling,” and validate the existence of the Environmental Kuznets Curve (EKC) hypothesis; ii) detect causality between CO2 emissions, EC, and GDP, and scrutinize their impacts. The ARDL results confirm a long-run and short-run co-integration relationship between the variables. The relationship between CO2 emissions and GDP is “relatively decoupling,” and the EKC exists in China. Its CO2 emissions are more explained by EC and contribute twofold of GDP. In the long run, there was significant negative causality from CO2 emission and GDP to EC. This indicates Chinese economic development structure should be re-designed towards energy-saving and decarbonized economic structure. Moreover, the central and provincial governments of China should synchronize optimal energy utilization and green economic structure to mitigate environmental deterioration and climate change.


2021 ◽  
Vol 2021 (68) ◽  
pp. 42-58
Author(s):  
Essa Alhannom ◽  
Ghaleb Mushabab

Abstract This study investigates the validity of the Environmental Kuznets Curve hypothesis in Yemen and the causal relationships between Carbon dioxide emissions, per capita income, energy consumption, trade openness, and industrial share to GDP. ARDL bounds testing approach to cointegration, Error Correction Model, and Toda-Yamamoto procedure to Granger causality techniques were employed on annual data covering the period from 1990 to 2010. long run relationship between CO2 emissions and its determinants with significant effects for per capita GDP and trade openness, whereas, energy consumption and trade openness appear to be important determinants of CO2 emissions in the short run. Besides, based on Narayan and Narayan (2010) approach, it is found that the EKC hypothesis does not hold in Yemen and therefore the effect of per capita income on CO2 emissions is monotonically increasing. Toda-Yamamoto causality test proved the existence of bidirectional causal relationships between economic growth and CO2 emissions, between energy consumption and economic growth, and between trade openness and energy consumption


Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3144
Author(s):  
Anh-Tu Nguyen ◽  
Shih-Hao Lu ◽  
Phuc Thanh Thien Nguyen

This paper examines the environmental Kuznets curve (EKC) in Vietnam between 1977 and 2019. Using the autoregressive distributed lag (ARDL) approach, we find an inverted N-shaped relation between economic growth and carbon dioxide emissions in both the long- and short-run. The econometric results also reveal that energy consumption and urbanization statistically positively impact pollution. The long-run Granger causality test shows a unidirectional causality from energy consumption and economic growth to pollution while there is no causal relationship between energy consumption and economic growth. These suggest some crucial policies for curtailing emissions without harming economic development. In the second step, we also employed the back-propagation neural networks (BPN) to compare the work of econometrics in carbon dioxide emissions forecasting. A 5-4-1 multi-layer perceptron with BPN and learning rate was set at 0.1, which outperforms the ARDL’s outputs. Our findings suggest the potential application of machine learning to notably improve the econometric method’s forecasting results in the literature.


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