The troika of energy consumption, economic growth, and CO2 emission: Quantile regression evidences for five Asian economies

• 出版年: Geographical Journal
• 第一著者: 2-s2.0-85180894527
• フォーマット: 論文
• 言語: English
• 出版事項: John Wiley and Sons Inc 2024
• オンライン･アクセス: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180894527&doi=10.1111%2fgeoj.12573&partnerID=40&md5=8cf1a6f190ebb1ffa67b99f14e661813

This study examined the quadratic role of renewable energy and economic growth on environment quality in Asia's five most populous countries: China, India, Indonesia, Pakistan, and Bangladesh. Previous literature has scarcely addressed these economies and ignores the quadratic role of GDP per capita (GDPPC) and renewable energy (REN) together in a single study. Therefore, using STIRPAT model, we first added the quadratic term of GDPPC and then REN. In both cases, a quantile regression technique is utilised to identify the inclusive relationship between CO2 emissions and determining factors, considering different quantiles (0.25, 0.50, 0.75, 0.90, and 0.95) of CO2 emissions. The findings show that during the annual sample period of 1983–2019, urbanisation, GDPPC, non-renewable energy, and REN all have an impact on CO2 emissions. Urbanisation and REN have nominal effects, with a 1% change in these variables leading to a 0.19% and 0.05% change in CO2 emissions, respectively. Non-renewable energy and GDPPC are found to be main sources of CO2 emissions in the region. GDPPC is positively associated with CO2 emissions across all quantiles, but higher quantiles show a stronger correlation (i.e., GDPPC coefficients vary from 0.26 to 0.66). In addition, the results also revealed that the square term of GDPPC and REN significantly reduces CO2 emissions. This implies that our results support the environmental Kuznets curve (EKC) hypothesis; an inverted U-shaped is established for both GDPPC and REN. These results encourage policy makers to adopt renewable energy that is both growth and environment friendly. The information, practices and views in this article are those of the author(s) and do not necessarily reflect the opinion of the Royal Geographical Society (with IBG). © 2023 Royal Geographical Society (with the Institute of British Geographers).