Development or environmental sustainability? Investigating the relationship between poverty rate and carbon emissions using the K-nearest neighbor algorithm

Mohamed F. Abd El-Aal (), Abdelsamiea Tahsin Abdelsamiea (), Kamel Garfa (), Saja Aldera () and Mustafa Radwan ()

International Journal of Innovative Research and Scientific Studies, 2025, vol. 8, issue 10, 97-103

Abstract: This paper applies the k-nearest neighbor (k-NN) algorithm, recognized for its predictive accuracy, to investigate the relationship between global poverty rates and global carbon emissions. The analysis explores how variations in poverty levels influence environmental carbon emissions. The results demonstrate that the relationship between poverty rates and carbon emissions resembles the production possibility curve, showing an inverse relationship: as poverty rates increase, carbon emissions decrease. Specifically, the k-NN model reveals that a 1% rise in poverty rates leads to a 0.29% reduction in carbon emissions. This outcome reflects the tendency for emissions to fall when economic growth slows. The study concluded that the global quest to eradicate poverty is closely linked to environmental challenges. While reducing poverty contributes to improved living standards, it also threatens to increase emissions, necessitating a balance between economic growth and environmental sustainability. The findings highlight the urgent need for policies that reconcile poverty reduction and environmental conservation. A key recommendation is to rely heavily on renewable energy to support economic growth while reducing carbon emissions. This approach enables progress toward poverty reduction and environmental protection.

Keywords: CO2 emissions; Global poverty rate; K-nearest neighbor algorithm; Machine learning algorithms. (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:aac:ijirss:v:8:y:2025:i:10:p:97-103:id:10752

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