IDEAS home Printed from https://ideas.repec.org/a/ids/ijsuse/v14y2022i4p399-410.html
   My bibliography  Save this article

A cross-country analysis of the role of service sector in the relationship between CO 2 emissions and economic growth using machine learning techniques

Author

Listed:
  • C. Karthikeyan
  • R. Murugesan

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.

Suggested Citation

  • C. Karthikeyan & R. Murugesan, 2022. "A cross-country analysis of the role of service sector in the relationship between CO 2 emissions and economic growth using machine learning techniques," International Journal of Sustainable Economy, Inderscience Enterprises Ltd, vol. 14(4), pages 399-410.
    • Handle: RePEc:ids:ijsuse:v:14:y:2022:i:4:p:399-410
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=125979
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:ijsuse:v:14:y:2022:i:4:p:399-410. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=301 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.