Studying the impact of the Green Deal on the EU economy using Gradient Boosting Algorithm

Frahi Fadila
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Frahi Fadila: University of Algiers 3 (Algeria)

IJEP, 2025, vol. 8, issue 01, Pages : 01-17

Abstract: This study aims to assess the impact of the European Green Deal on the EU economy by employing a Gradient Boosting Algorithm to analyze the influence of various environmental policies. The study utilizes simulated monthly data derived from annual statistics provided by official sources such as the IEA, Eurostat, ILO, and the European Commission. A machine learning model—Gradient Boosting—is implemented to examine the predictive relationships between economic indicators such as environmental taxes, green infrastructure investment, renewable energy, and green employment on industrial output. Results indicate that environmental taxes are the most influential factor affecting industrial performance, followed by green infrastructure and renewable energy investment. Green innovation funding and green employment show lesser impact. The Gradient Boosting model demonstrates strong predictive accuracy with an R² score of 0.930. Policymakers should consider balancing fiscal regulations with incentive-based green investment strategies. Greater support for green innovation and employment training is essential to enhance long-term sustainability.

Keywords: Gradient Boosting Algorithm; Green Infrastructure; Renewable Energy; Green Jobs (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:bjm:ijep00:v:8:y:2025:i:01:id:345

DOI: 10.54241/2065-008-001-001

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