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

A-Tier
Journal: Energy Economics
Year: 2024
Volume: 136
Issue: C

Authors (4)

Zhang, Long (not in RePEc) Padhan, Hemachandra (Indian Institute of Management...) Singh, Sanjay Kumar (not in RePEc) Gupta, Monika (not in RePEc)

Score contribution per author:

1.005 = (α=2.01 / 4 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:eee:eneeco:v:136:y:2024:i:c:s0140988324004262
Journal Field
Energy
Author Count
4
Added to Database
2026-01-28