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    Since there is little progress being made in multinational climate discussions, climate finance is at a crossroads as lenders must come up with new plans for the "Future of Environment Funds." The mission of effectively and efficiently distributing money to support the shift to low-carbon, climate-resilient economies has been given to climate finance organizations. Due to its purpose to contribute to a paradigm shift, the Green Climate Fund (GCF) is anticipated to help the most vulnerable populations adapt to and mitigate climate change. This research alters the premise of the Baumol and Oates public externality model to make it more appropriate for global climate governance analysis. This research then deduces the special pricing conditions to persuade the market to comply with Pareto optimality criteria by contrasting the Pareto optimality model of global climate governance and the market equilibrium model. The rules and potential approaches that must be followed for raising capital and allocating GCFs are then determined by taking into account global Pareto optimality and fiscal balance. The study finds that when each country assumes that the GCF aims to achieve Pareto optimality in climate governance globally and its own fiscal balance, the equilibrium results of the international climate game will not achieve both the financial balance of the GCF and global Pareto optimality simultaneously. The GCF may successfully finance non-bankable components of bigger "almost bankable projects," according to our empirical analysis of the GCF portfolio structure and strategy in this research. This lends credence to an alternative interpretation of the GCF. © 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.


    Jie Ding, Ying Wang, Siqi Wang, Muhammad Mohsin. Role of climate fund raising under fiscal balance on climate change mitigation: an analysis from Pareto optimality. Environmental science and pollution research international. 2023 Feb;30(7):19047-19060

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    PMID: 36223013

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