Deciphering the interconnections: a panel vector autoregressive analysis of economic growth, renewable energy use, trade openness and CO2 emissions in OECD countries Online publication date: Fri, 28-Jun-2024
by Mohd Afjal; Chitra Devi
International Journal of Green Economics (IJGE), Vol. 18, No. 2, 2024
Abstract: This study investigates the impact of economic growth, renewable energy, and trade openness on CO2 emissions in OECD countries from 1995 to 2020, categorised by GDP growth into low (>1%), moderate (1%-3%), and high (>3%). Using panel vector autoregression models, it finds an inverse relationship between GDP and CO2 emissions in low-growth economies, and a positive correlation in moderate and high-growth economies. Renewable energy positively impacts CO2 emissions in moderate and high-growth economies but reduces them in low-growth contexts. The Hausmann test supports using a fixed effect model, and the Granger causality test reveals a unidirectional relationship from GDP and renewable energy to CO2 emissions across all growth levels. These discoveries highlight the connection between economic growth and carbon emissions, thus stressing the necessity for nations with advanced economic statuses to implement measures aimed at curbing carbon emissions through the promotion of renewable energy sources.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Green Economics (IJGE):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook