Green Energy, Economic Growth, and Innovation for Sustainable Development in OECD Countries

Tianhao Zhao () and Syed Ahsan Ali Shah ()
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Tianhao Zhao: School of Management, Lancaster University, Lancaster LA1 4YW, UK
Syed Ahsan Ali Shah: Mathematics and Experimental Sciences Department, University of Salamanca (USAL), Paseo de Canalejas, 169, 37008 Salamanca, Spain

Sustainability, 2024, vol. 16, issue 22, 1-14

Abstract: This study explores the interrelationship between green energy adoption, economic growth, and innovation in promoting sustainable development within OECD countries. Using a random forest regression model, the research analyzes secondary data from 2013 to 2022 to identify the most significant contributors to sustainable development. The random forest model was selected for its ability to handle non-linear relationships and feature importance ranking, providing a comprehensive understanding of the variables’ impacts. The analysis reveals that green energy adoption has the strongest influence on the human development index (HDI), with an importance score of 0.43, followed by gross domestic product (GDP) and the global innovation index (GII). These findings underscore the pivotal role of green energy adoption, amplified by economic growth and technological innovation, in advancing sustainable development. While the study focuses on OECD countries, the insights offer valuable implications for global sustainability initiatives. The evidence supports the argument that prioritizing green energy, supported by economic and innovative drivers, is crucial for achieving broader sustainable development goals. This research provides a methodological contribution by demonstrating the effectiveness of machine learning models in analyzing complex sustainability data and offers empirical evidence that informs policy and future research in a broader context.

Keywords: green energy; economic growth; technological innovation; sustainable development; machine learning; random forest (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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