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The impact of renewable energy on inflation in G7 economies: Evidence from artificial neural networks and machine learning methods

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  • Zhang, Long
  • Padhan, Hemachandra
  • Singh, Sanjay Kumar
  • Gupta, Monika

Abstract

This paper examines the impact of cleaner energy adoption (i.e., renewable energy consumption and generation) on inflation rates in G7 economies from 1997 to 2021. The Principal Component Analysis is used to construct the renewable energy consumption and generation indices. Then, the paper runs various artificial neural networks and machine learning methods to test the validity of the cleaner energy-led inflationary economy hypothesis. It is observed that renewable energy consumption and production significantly predict inflation rates along with macroeconomic variables. The effects of renewable energy consumption and production on inflation rates are positive. Related policy implications are also discussed.

Suggested Citation

  • Zhang, Long & Padhan, Hemachandra & Singh, Sanjay Kumar & Gupta, Monika, 2024. "The impact of renewable energy on inflation in G7 economies: Evidence from artificial neural networks and machine learning methods," Energy Economics, Elsevier, vol. 136(C).
    • Handle: RePEc:eee:eneeco:v:136:y:2024:i:c:s0140988324004262
    DOI: 10.1016/j.eneco.2024.107718
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