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DOI10.1080/00036846.2024.2326040
Nonlinear analysis of tertiary industry on trade globalization-environment nexus in Yellow River Basin in China: evidence from panel smooth transition regression
发表日期2024
ISSN0003-6846
EISSN1466-4283
英文摘要Trade globalization has broken down barriers between countries and has also brought opportunities and challenges to the global environment. This paper examines whether tertiary industry improves the nexus between globalization and the environment in the Yellow River Basin (YRB) in China. This is done by using panel smooth transition regression (PSTR) covering 30 years, from 1992 to 2021. The results confirm that emissions reduction benefits from the development of tertiary industry, while tertiary industry contributes to the global response to the increase of carbon emissions and to the fight against climate change. The development of the tertiary sector has deepened the influence of urbanization on emissions. Although economic growth means emissions keep increasing, the rapid development of tertiary industry alleviates the negative influence of the economy on CO2 emissions. Some implications are proposed, based on the findings.
英文关键词tertiary industry; trade globalization; emissions; Yellow River Basin; panel smooth transition regression; O44; Q56; P48
语种英语
WOS研究方向Business & Economics
WOS类目Economics
WOS记录号WOS:001177596100001
来源期刊APPLIED ECONOMICS
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/292860
作者单位Luoyang Normal University; Luoyang Normal University
推荐引用方式
GB/T 7714
. Nonlinear analysis of tertiary industry on trade globalization-environment nexus in Yellow River Basin in China: evidence from panel smooth transition regression[J],2024.
APA (2024).Nonlinear analysis of tertiary industry on trade globalization-environment nexus in Yellow River Basin in China: evidence from panel smooth transition regression.APPLIED ECONOMICS.
MLA "Nonlinear analysis of tertiary industry on trade globalization-environment nexus in Yellow River Basin in China: evidence from panel smooth transition regression".APPLIED ECONOMICS (2024).
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