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

Arvind Goswami, Harmanpreet Singh Kapoor, Rajesh Kumar Jangir, Caspar Njoroge Ngigi, Behdin Nowrouzi-Kia () and Vijay Kumar Chattu ()
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Arvind Goswami: Department of Economic Studies, Central University of Punjab, Ghudda, Bathinda 151401, India
Harmanpreet Singh Kapoor: Department of Mathematics and Statistics, Central University of Punjab, Ghudda, Bathinda 151401, India
Rajesh Kumar Jangir: Department of Economic Studies, Central University of Punjab, Ghudda, Bathinda 151401, India
Caspar Njoroge Ngigi: Department of Economic Studies, Central University of Punjab, Ghudda, Bathinda 151401, India
Behdin Nowrouzi-Kia: Department of Occupational Science and Occupational Therapy, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5G 1V7, Canada
Vijay Kumar Chattu: Department of Occupational Science and Occupational Therapy, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5G 1V7, Canada

Sustainability, 2023, vol. 15, issue 11, 1-19

Abstract: (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, CO 2 emissions at previous lag, economic growth, and trade openness negatively correlated with CO 2 emissions, while energy consumption and urbanization exhibited a positive correlation. In the long run, energy consumption, urbanization, and trade openness positively correlated with CO 2 emissions, while economic growth and CO 2 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.

Keywords: climate change; economic growth; urbanization; carbon emissions; environment; greenhouse gases (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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