IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v157y2026ics0140988326001106.html

The ‘climate Kuznets curve’: A critique

Author

Listed:
  • Castle, Jennifer L.
  • Hendry, David F.

Abstract

The ‘climate Kuznets curve’ relates the log of greenhouse gas (GHG) emissions, usually measured just by carbon dioxide (CO2), to the log of GDP and that squared in an inverse U-shaped relationship. In an all-electric world, there would be little relationship, as GDP would not be generated using fossil fuels. Rather the relation is between anthropogenic GHGs and fossil fuel use as we demonstrate for the United Kingdom, as well as demonstrating the non-constancy of the ‘climate Kuznets curve’. The danger of falsely believing GDP growth is the problem, not fossil fuel use, is that cutting GDP is mistakenly seen as a ‘solution’ to the climate crisis, leading to opposition to the green transition and facing unnecessary reductions in living standards if wrongly adopted.

Suggested Citation

  • Castle, Jennifer L. & Hendry, David F., 2026. "The ‘climate Kuznets curve’: A critique," Energy Economics, Elsevier, vol. 157(C).
    • Handle: RePEc:eee:eneeco:v:157:y:2026:i:c:s0140988326001106
    DOI: 10.1016/j.eneco.2026.109231
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988326001106
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2026.109231?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    Statistics

    Access and download statistics

    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:eee:eneeco:v:157:y:2026:i:c:s0140988326001106. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.