Role of income in pollution and growth across Belt and Road Initiative countries: new insights from dynamic functional regression model

被引：0
|
作者：
Hael, Mohanned Abduljabbar [1 ,2 ]
Ma, Haiqiang [1 ]
Al-Selwi, Fahmi [2 ]
Mohammed, Mushref [3 ,4 ]
Myint, Khin Sandi [1 ]
Al-Kuhali, Hamas A. [5 ]
机构：
[1] Jiangxi Univ Finance & Econ, Sch Stat & Data Sci, Nanchang 330013, Peoples R China
[2] Taiz Univ, Dept Data Sci & Informat Technol, Taizi, Yemen
[3] Hohai Univ, Business Sch, Nanjing, Peoples R China
[4] Taiz Univ, Coll Adm Sci, Taizi, Yemen
[5] Wuhan Univ Technol, Sch Comp & Artificial Intelligence, Wuhan 430070, Peoples R China
来源：
INTERNATIONAL JOURNAL OF GLOBAL WARMING | 2024年 / 33卷 / 04期
关键词：
function-on-scalar regression; FOSR; penalised least square estimator; dynamic modelling; economic growth; carbon emissions; income level; Belt and Road Initiative; BRI; INEQUALITY;
D O I：
10.1504/IJGW.2024.139903
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
This study employed function-on-scalar regression (FOSR) to model the complex nexus and spatial-temporal dynamic impact of income distribution on carbon dioxide emissions (CO2) and economic growth (EG) for 80 Belt and Road Initiative (BRI) countries (1990-2021). Results discovered a robust positive nexus between income, CO2, and EG across the spatial-temporal BRI domain. Increased income levels are associated with heightened EG, subsequently driving higher CO2. Decreased income levels were linked to reduced EG and a corresponding decline in CO2 intensity. Accordingly, we suggested policy implications to guide BRI towards a balanced and sustainable development pattern.
引用
收藏
页码：315 / 329
页数：16
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