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<p>South Asia faces a critical challenge in balancing economic growth with environmental sustainability, especially amid mounting global concerns over climate change. This study examines the long-term relationships between digital trade, green technology investment, financial inclusion, natural resource rent, and carbon dioxide emissions in South Asian economies from 2003 to 2023. Using the Generalized Method of Moments–Panel Vector Auto Regression (GMM-PVAR) model, the study captures both dynamic interactions and causal linkages among the variables. The findings reveal that lagged carbon emissions significantly reduce current emissions, indicating a corrective mechanism influenced by regulatory and economic adjustments. Both green technology investment and digital trade substantially reduce carbon emissions. However, financial inclusion tends to increase emissions due to greater economic activities in carbon-intensive industries. Natural resource rent does not significantly impact carbon emissions. Causality analysis confirms both unidirectional and bidirectional causal relationships, highlighting the significance of legislative actions to balance environmental sustainability and economic prosperity. These findings provide valuable insights for policymakers in South Asia and beyond, emphasizing the need for strategic investments in green innovation and digital infrastructure to achieve sustainable development goals.</p>

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Shaping sustainable future through green technology investment and digital trade in South Asia: a novel approach of GMM-PVAR

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月3日

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  • Weiying Yang,
  • Tayyaba Rani,
  • Feng Wang

摘要

South Asia faces a critical challenge in balancing economic growth with environmental sustainability, especially amid mounting global concerns over climate change. This study examines the long-term relationships between digital trade, green technology investment, financial inclusion, natural resource rent, and carbon dioxide emissions in South Asian economies from 2003 to 2023. Using the Generalized Method of Moments–Panel Vector Auto Regression (GMM-PVAR) model, the study captures both dynamic interactions and causal linkages among the variables. The findings reveal that lagged carbon emissions significantly reduce current emissions, indicating a corrective mechanism influenced by regulatory and economic adjustments. Both green technology investment and digital trade substantially reduce carbon emissions. However, financial inclusion tends to increase emissions due to greater economic activities in carbon-intensive industries. Natural resource rent does not significantly impact carbon emissions. Causality analysis confirms both unidirectional and bidirectional causal relationships, highlighting the significance of legislative actions to balance environmental sustainability and economic prosperity. These findings provide valuable insights for policymakers in South Asia and beyond, emphasizing the need for strategic investments in green innovation and digital infrastructure to achieve sustainable development goals.