Leveraging Machine Learning to Assess the Impact of Energy Consumption on Global GDP Growth: What Actions should be taken Globally toward Environmental Concerns?

Mohamed F. Abd El-Aal, Hasan Amin Mohamed Mahmoud, Abdelsamiea Tahsin Abdelsamiea and Marwa Samir Hegazy
Additional contact information
Mohamed F. Abd El-Aal: Department of Economics, Faculty of Commerce, Arish University, North Sinai, Egypt
Hasan Amin Mohamed Mahmoud: Department of Economics, Faculty of Commerce, Aswan University, Egypt
Abdelsamiea Tahsin Abdelsamiea: Department of Economics, Faculty of Commerce, Mansoura University, Egypt
Marwa Samir Hegazy: Department of Economics, Faculty of Commerce, Mansoura University, Egypt

International Journal of Energy Economics and Policy, 2024, vol. 14, issue 4, 108-115

Abstract: The study aims to explore the impact of renewable, nonrenewable, and nuclear energy consumption on global gross domestic product (GDP) growth through machine learning algorithms. The findings reveal that renewable energy consumption is the most influential variable, contributing to a predicted 67.5% global GDP growth. In contrast, nuclear energy consumption contributes 17.8%, and non-renewable energy consumption contributes 14.6%. Notably, the relationship between nuclear energy consumption and global economic growth is positive; there is a negative relation in conjunction with renewable energy consumption. However, the association with non-renewable energy is consistently fixed. These results suggest that an increased reliance on renewable energy may necessitate a trade-off, potentially leading to a reduction in global GDP growth despite the positive contributions from renewable sources.

Keywords: Machine Learning; Renewable Energy; Nonrenewable Energy; Nuclear Energy; Global Gross Domestic Product (search for similar items in EconPapers)
JEL-codes: C63 C80 C81 C87 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econjournals.com/index.php/ijeep/article/download/15833/7972 (application/pdf)
https://www.econjournals.com/index.php/ijeep/article/view/15833 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eco:journ2:2024-04-10

Access Statistics for this article

International Journal of Energy Economics and Policy is currently edited by Ilhan Ozturk

More articles in International Journal of Energy Economics and Policy from Econjournals
Bibliographic data for series maintained by Ilhan Ozturk ().