Impact of Economic Growth, Trade Openness, Urbanization and Energy Consumption on Carbon Emissions: A Study of India

被引:10
作者
Goswami, Arvind [1 ]
Kapoor, Harmanpreet Singh [2 ]
Jangir, Rajesh Kumar [1 ]
Ngigi, Caspar Njoroge [1 ]
Nowrouzi-Kia, Behdin [3 ]
Chattu, Vijay Kumar [3 ,4 ,5 ]
机构
[1] Cent Univ Punjab, Dept Econ Studies, Bathinda 151401, India
[2] Cent Univ Punjab, Dept Math & Stat, Bathinda 151401, India
[3] Univ Toronto, Temerty Fac Med, Dept Occupat Sci & Occupat Therapy, Toronto, ON M5G 1V7, Canada
[4] Saveetha Univ, Saveetha Inst Med & Tech Sci, Saveetha Dent Coll, Ctr Transdisciplinary Res, Chennai 600077, India
[5] Datta Meghe Inst Med Sci DMIMS, Fac Med, Dept Community Med, Wardha 442107, India
关键词
climate change; economic growth; urbanization; carbon emissions; environment; greenhouse gases; ENVIRONMENTAL KUZNETS CURVE; CO2; EMISSIONS; DYNAMIC RELATIONSHIP; NONRENEWABLE ENERGY; EMPIRICAL-EVIDENCE; INDUSTRIALIZATION; DETERMINANTS; NEXUS;
D O I
10.3390/su15119025
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
(1) Background: Global warming is one of the most severe environmental problems humans are facing now. This study aims to assess the impacts of economic growth, trade openness, urbanization, and energy consumption on carbon emissions in India; (2) Methodology: In this longitudinal study, data have been collected from World Development Indicators and Our World in Data from 1980 to 2021. Two models have been used in this study, which are ARDL and the random forest model, which is a machine learning algorithm that uses the aggregated prediction for final prediction; (3) Results: The ARDL model revealed that the variables were cointegrated. In the short run, CO2 emissions at previous lag, economic growth, and trade openness negatively correlated with CO2 emissions, while energy consumption and urbanization exhibited a positive correlation. In the long run, energy consumption, urbanization, and trade openness positively correlated with CO2 emissions, while economic growth and CO2 emissions at previous lag demonstrated a negative correlation. The high value of the R-2 and low values of RMSE and M.A.E. in the Random Forest model shows the model's fitness; (4) Conclusions: The study's findings have been briefly discussed, and a few suggestions have been provided based on the results.
引用
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页数:19
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