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.

中文翻译：

---

可再生能源对七国集团经济体通胀的影响：来自人工神经网络和机器学习方法的证据


本文研究了 1997 年至 2021 年清洁能源采用（即可再生能源消费和发电）对七国集团经济体通货膨胀率的影响。主成分分析用于构建可再生能源消费和发电指数。然后，本文运行各种人工神经网络和机器学习方法来测试清洁能源主导的通货膨胀经济假设的有效性。据观察，可再生能源消费和生产可以显着预测通货膨胀率以及宏观经济变量。可再生能源消费和生产对通货膨胀率的影响是积极的。还讨论了相关的政策影响。