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<p>Emerging Asian economies, such as China, India, Indonesia, South Korea, Malaysia, the Philippines, and Thailand, face the dual challenge of rapid industrialisation and increasing exposure to environmental degradation related issues. The conventional measure of using emissions only captures the cause of environmental degradation, but it fails to account for the broader economic costs of degradation. To address this gap, the study introduces pollution cost as a measure of environmental degradation, making it a more policy-relevant indicator. To further draw nuance insights, this study employs a hybrid methodology that combines a physics-inspired dissipative model with a non-linear Logit model for panel data ranging from 2015 to 2024. This dual approach allows the identification of entropy-driven stress flows, resilience thresholds, and probabilistic regime dynamics. Results show that environmental vulnerability (EV), carbon emissions, financed emissions (FE), and disaster frequency act as stressors that significantly increase the probability of high-cost regimes. In contrast, adaptability and renewable energy penetration reduces probability by 20 to 30%, thereby associated with a reduction in the likelihood. The dissipative estimates identify an indicative resilience threshold (<InlineEquation ID="IEq1"><EquationSource Format="TEX">\(\:c\:\)</EquationSource></InlineEquation>= -0.569), beyond which systemic costs escalate sharply. The Logit results further indicate that emissions nearly double the likelihood of high-cost regimes, while renewable adoption counters. These estimates extend beyond the obvious; the interaction effects reveal that disasters weigh in vulnerable economies, whereas financed emissions are less harmful when coupled with energy transitions. Policy takeaways emphasise the critical role of renewable energy, adaptive capacity, and green financial regulation in reducing pollution costs and securing sustainability-oriented growth in Emerging Asia.</p>

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Pollution cost dynamics and regime transitions in emerging Asia: a dissipative-Logit approach

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月4日

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  • Dhyani Mehta,
  • Nikunj Patel,
  • Abdikafi Hassan Abdi

摘要

Emerging Asian economies, such as China, India, Indonesia, South Korea, Malaysia, the Philippines, and Thailand, face the dual challenge of rapid industrialisation and increasing exposure to environmental degradation related issues. The conventional measure of using emissions only captures the cause of environmental degradation, but it fails to account for the broader economic costs of degradation. To address this gap, the study introduces pollution cost as a measure of environmental degradation, making it a more policy-relevant indicator. To further draw nuance insights, this study employs a hybrid methodology that combines a physics-inspired dissipative model with a non-linear Logit model for panel data ranging from 2015 to 2024. This dual approach allows the identification of entropy-driven stress flows, resilience thresholds, and probabilistic regime dynamics. Results show that environmental vulnerability (EV), carbon emissions, financed emissions (FE), and disaster frequency act as stressors that significantly increase the probability of high-cost regimes. In contrast, adaptability and renewable energy penetration reduces probability by 20 to 30%, thereby associated with a reduction in the likelihood. The dissipative estimates identify an indicative resilience threshold (\(\:c\:\)= -0.569), beyond which systemic costs escalate sharply. The Logit results further indicate that emissions nearly double the likelihood of high-cost regimes, while renewable adoption counters. These estimates extend beyond the obvious; the interaction effects reveal that disasters weigh in vulnerable economies, whereas financed emissions are less harmful when coupled with energy transitions. Policy takeaways emphasise the critical role of renewable energy, adaptive capacity, and green financial regulation in reducing pollution costs and securing sustainability-oriented growth in Emerging Asia.