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<p>With the growing urgency of climate change mitigation, investments in clean energies have become a major catalyst for sustainable economic development and environmental conservation. The Regional Comprehensive Economic Partnership Agreement is an important multilateral trade agreement that is an essential framework for cooperative environmental action aimed at halting environmental degradation and promoting a sustainable future. This study uses advanced in-depth learning techniques to quantify the determinants of carbon emissions of member countries of RCEP from the first quarter of 2000 to the fourth quarter of 2023. The analysis assesses the impact of financing in carbon free energies sectors, fossil fuel-based energy consumption, financial sector development, economic growth and population ageing on environmental degradation. The analysis demonstrates that financing in carbon free energy significantly enhances environmental quality by reducing the intensity of emissions. There is also found joint probabilistic distribution among significant random variables in smart Bayes network topology. A novel insight revealed through constraint-based learning within this network is the conditional dependence of emissions on fossil fuel-based energy consumption, economic growth, and population aging moderated by the combined percentage effects of financial development and green finance. This study synthesizes targeted policy implications, providing governments in resource-abundant economies with empirically grounded strategies to synchronize financial instruments and energy regulations with overarching environmental sustainability goals.</p>

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Greening the future: deep intelligent neural networks-based analysis of green finance in renewable energy and environmental degradation in emerging economies

  • 期刊论文

  • 发表日期：

    2026年4月8日

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  • Hafiz Muhammad Naveed,
  • Yanchun Pan,
  • Arshian Sharif,
  • Muhammad Farhan Bashir,
  • Mamdouh Abdulaziz Saleh Al-Faryan

摘要

With the growing urgency of climate change mitigation, investments in clean energies have become a major catalyst for sustainable economic development and environmental conservation. The Regional Comprehensive Economic Partnership Agreement is an important multilateral trade agreement that is an essential framework for cooperative environmental action aimed at halting environmental degradation and promoting a sustainable future. This study uses advanced in-depth learning techniques to quantify the determinants of carbon emissions of member countries of RCEP from the first quarter of 2000 to the fourth quarter of 2023. The analysis assesses the impact of financing in carbon free energies sectors, fossil fuel-based energy consumption, financial sector development, economic growth and population ageing on environmental degradation. The analysis demonstrates that financing in carbon free energy significantly enhances environmental quality by reducing the intensity of emissions. There is also found joint probabilistic distribution among significant random variables in smart Bayes network topology. A novel insight revealed through constraint-based learning within this network is the conditional dependence of emissions on fossil fuel-based energy consumption, economic growth, and population aging moderated by the combined percentage effects of financial development and green finance. This study synthesizes targeted policy implications, providing governments in resource-abundant economies with empirically grounded strategies to synchronize financial instruments and energy regulations with overarching environmental sustainability goals.