IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v150y2025ics0140988325006607.html
   My bibliography  Save this article

How does environmental policy shape the impact of energy innovation funding on renewable energy generation? Evidence from econometric and machine learning approaches

Author

Listed:
  • Sen, Kanchan Kumar
  • Karmaker, Shamal Chandra
  • Chapman, Andrew J.
  • Saha, Bidyut Baran

Abstract

Achieving sustainable development in the energy sector, particularly in renewable energy, requires substantial innovation funding, as it is essential for reaching net-zero emissions by 2050. This study explores how environmental policy influences the effect of energy innovation funding on renewable energy generation, addressing a key research gap in understanding policy impacts on energy transitions. Using both econometric and machine learning methods, the study analyzed data from 27 countries in the Organisation for Economic Co-operation and Development (OECD) between 2001 and 2020. The findings reveal that while energy innovation funding accelerated renewable energy generation, poor environmental policies weaken this relationship, suggesting that strong environmental policies are essential to complement energy innovation funding for promoting renewable energy generation. Additionally, the results indicate that market-based policies are more effective in enhancing the impact of energy funding on accelerating the renewable energy generation compared to non-market-based policies. These insights highlight the importance of aligning energy innovation funding with stringent market-oriented environmental policies to fully harness their potential and expedite the transition to renewable energy. Policymakers should prioritize the development of the strategies that integrate energy funding with effective policy frameworks, ensuring that the transition to renewable energy is not only swift but also sustainable.

Suggested Citation

  • Sen, Kanchan Kumar & Karmaker, Shamal Chandra & Chapman, Andrew J. & Saha, Bidyut Baran, 2025. "How does environmental policy shape the impact of energy innovation funding on renewable energy generation? Evidence from econometric and machine learning approaches," Energy Economics, Elsevier, vol. 150(C).
  • Handle: RePEc:eee:eneeco:v:150:y:2025:i:c:s0140988325006607
    DOI: 10.1016/j.eneco.2025.108833
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988325006607
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2025.108833?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

    ;
    ;
    ;
    ;
    ;
    ;

    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:150:y:2025:i:c:s0140988325006607. 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.