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Exploring how economic growth, renewable energy, internet usage, and mineral rents influence CO2 emissions: A panel quantile regression analysis for 27 OECD countries      
Yazarlar
Cem Işık
Anadolu Üniversitesi, Türkiye
Prof. Dr. Ümit BULUT Prof. Dr. Ümit BULUT
Kırşehir Ahi Evran Üniversitesi, Türkiye
Serdar Ongan
Türkiye
Hasibul Islam
Muhammad Irfan
Özet
This study aims to investigate the impacts of renewable energy consumption, internet usage, mineral rent, and economic growth on CO2 emissions across 27 OECD nations between 2001 and 2020. We employ a panel quantile regression technique to discover the heterogeneous effects of these variables for the various quantile levels of environmental destruction. The panel quantile regression approach found the Environmental Kuznets curve dominated countries in which CO2 emissions were low. Additionally, the negative relationship between renewable energy consumption and CO2 emissions yielded in the paper suggests the potential benefits of incentivizing and investing in renewable sources. Internet usage demonstrates a negative impact on CO2 emissions, showcasing the role of digital technologies in promoting sustainability. Accordingly, internet use improves environmental quality due to more efficient, sustainable, and eco-friendly practices, which increase productivity. However, a positive association between mineral rents and environmental deterioration emphasizes the necessity of strategic policies to balance economic benefits with environmental preservation. Our study provides policymakers with valuable insights into tailoring effective strategies for sustainable development, renewable energy adoption, digitalization, and natural resource utilization while addressing environmental degradation.
Anahtar Kelimeler
CO emissions 2 | Environmental degradation | Renewable energy consumption | The Environmental Kuznets curve | WWW
Makale Türü Özgün Makale
Makale Alt Türü SSCI, AHCI, SCI, SCI-Exp dergilerinde yayımlanan tam makale
Dergi Adı Resources Policy
Dergi ISSN 0301-4207
Dergi Tarandığı Indeksler SSCI
Dergi Grubu Q1
Makale Dili Türkçe
Basım Tarihi 05-2024
Cilt No 92
Sayı 1
Sayfalar 1 / 9
Doi Numarası 10.1016/j.resourpol.2024.105025
Makale Linki http://dx.doi.org/10.1016/j.resourpol.2024.105025