Title: A cross-country analysis of the role of service sector in the relationship between CO₂ emissions and economic growth using machine learning techniques

Authors: C. Karthikeyan; R. Murugesan

Addresses: Department of Humanities and Social Sciences, National Institute of Technology, Tiruchirappalli-620015, India ' Department of Humanities and Social Sciences, National Institute of Technology, Tiruchirappalli-620015, India

Abstract: The study aims to explore the relationship between CO₂ emissions per capita, service sector share in GDP and GDP per capita using decision tree, and multiple ridge and lasso regression techniques on cross-sectional data of 175 countries. GDP per capita is a better determinant of the CO₂ emissions of a country than the share of services in GDP. The fit between emissions and income improves on account of service sector share in GDP. The study finds that an increase in service sector share in high income countries leads to decrease in emissions while in low income countries it leads to an increase in emissions. An N-shaped relationship is found between CO₂ emissions and income across the countries. Service sector share acts as a moderator in this relationship.

Keywords: service sector; CO₂ emissions; economic growth; decision tree; lasso regression; ridge regression.

DOI: 10.1504/IJSE.2022.125979

International Journal of Sustainable Economy, 2022 Vol.14 No.4, pp.399 - 410

Received: 13 Aug 2021
Accepted: 10 Oct 2021
Published online: 05 Oct 2022 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article