Skip to main content

Does renewable energy consumption affect ecological footprints in Saudi Arabia? A bootstrap causality test

Author name : Zouheyr . . Gheraya
Publication Date : 2022-03-02
Journal Name : Renewable Energy Volume 189, April 2022, Pages 813-821

Abstract

This paper investigates the relationship between renewable energy consumption and ecological footprint in Saudi Arabia by considering the important role of economic growth in the environmental function during 1980–2017 periods. Capital and trade openness are determinants of environmental degradation. To determine the cointegration between the variables, we relied on the bootstrap autoregressive distributed lag (ARDL) bound test. We also used the Granger causality based on the bootstrap ARDL approach to identify causal relationships between the factors of environmental degradation in the presence of structural break. The empirical results show the presence of cointegration between variables with a structural break. Furthermore, the results of the ARDL model state that an increase in human capital and renewable energy consumption improves environmental quality (decreasing the ecological footprint), while an increase in trade openness and GDP deteriorates environmental quality (increasing the ecological footprint). In the short run, the results of the VECM model show the existence of a bidirectional causal relationship between human capital and trade openness. GDP causes the ecological footprint, while human capital causes renewable energy consumption. Moreover, there is a causal relationship from GDP and renewable energy consumption to trade openness. In the long run, all variables cause renewable energy consumption on the one hand, and trade openness on the other. In view of these results, policy makers have an interest in implementing favorable measures that reduce the ecological footprint and improve the quality of the environment by using renewable energy consumption as an economic tool.

Keywords

renewable energy consumption

Publication Link

https://doi.org/10.1016/j.renene.2022.03.043

Block_researches_list_suggestions

Suggestions to read

HIDS-IoMT: A Deep Learning-Based Intelligent Intrusion Detection System for the Internet of Medical Things
Ahlem . Harchy Ep Berguiga
“Synthesis and Characterization study of SnO2/α-Fe2O3, In2O3/α-Fe2O3 and ZnO/α-Fe2O3 thin films and its application as transparent conducting electrode in silicon heterojunction solar cell”
Asma Arfaoui
Frequency and voltage dependent of electrical and dielectric properties of 14 nm Fully Depleted Silicon-On-Insulator (FD-SOI)
MOHAMMED OMAR MOHAMMEDAHMED IBRAHIM
Strengths Mindset as a Mediator in the Relationship Between Paradoxical Leadership and Nurses' Positive Attitudes Towards Artificial Intelligence: A Cross-Sectional Study
MOHAMED ELSAYED MOHAMED ZAKY
Contact