The role of energy efficiency in income inequality dynamics in developing Asia: Evidence from artificial neural networks

被引:2
作者
Wei, Xun [1 ]
Pal, Shreya [2 ]
Mahalik, Mantu Kumar [3 ]
Liu, Weibai [4 ]
机构
[1] Cent South Univ, Sch Business, Changsha, Peoples R China
[2] Christ Univ, Sch Business & Management, Bengaluru, Karnataka, India
[3] Indian Inst Technol Kharagpur, Dept Humanities & Social Sci, Kharagpur 721302, West Bengal, India
[4] Hunan Univ Finance & Econ, Sch Econ Geog, Changsha, Peoples R China
关键词
Income inequality; Energy efficiency; Artificial neural network; Machine learning estimations; Developing Asian economies; ECONOMIC-GROWTH; GLOBALIZATION; CONSUMPTION; GOVERNANCE; FINANCE;
D O I
10.1016/j.eneco.2024.107747
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study investigates the drivers of income inequality trends in seven developing Asian countries between 1990 and 2022, exploring the effects of energy efficiency, government spending, economic growth, globalization, and human development. The study investigates how these variables affect income inequality using various statistical methods, including long-run machine learning and prediction models. The findings indicate a negative impact of energy efficiency on income inequality, highlighting the potential of energy-saving measures in narrowing the income gaps between the rich and poor. Government spending, economic growth, globalization, and human development are also crucial in alleviating income inequality in developing Asian countries. This study underscores the importance of tailored policies, advocating for investments in energy efficiency, targeted government spending, larger economic integration, and inclusive growth strategies to address income inequality in developing Asia.
引用
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页数:11
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