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运用机器学习方法评估气候相关金融政策对脱碳的影响。

Evaluating climate-related financial policies' impact on decarbonization with machine learning methods.

作者信息

D'Orazio Paola, Pham Anh-Duy

机构信息

Chair of Economics, Faculty of Economics and Business Administration, Chemnitz University of Technology, Thüringer Weg 7, 09126, Chemnitz, Germany.

Joint Lab Artificial Intelligence and Data Science, Osnabrück University, 49074, Osnabrück, Germany.

出版信息

Sci Rep. 2025 Jan 11;15(1):1694. doi: 10.1038/s41598-025-85127-7.

DOI:10.1038/s41598-025-85127-7
PMID:39799213
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11724838/
Abstract

This study examines how Climate-Related Financial Policies (CRFPs) support decarbonization and renewable energy transitions across 87 countries from 2000 to 2023. Using the Policy Sequencing Score (PSS) and a bindingness-weighted adoption indicator, it explores the relationships between CRFPs, CO2 emissions, and Renewable Energy Production (REP) across diverse economic and institutional contexts. Findings reveal significant variation in outcomes. Advanced economies and OECD countries leverage structured policies and robust institutions to achieve steady emissions reductions and REP growth, with diminishing returns at higher policy intensities. Emerging Markets and Developing Economies (EMDEs) face institutional and structural constraints but show strong responsiveness to targeted policies, particularly in Sub-Saharan Africa and South Asia, where renewable energy growth potential is notable. Regions such as Latin America and East Asia display mixed trends, reflecting unique challenges and opportunities. Binding policies prove essential for environmental outcomes, particularly in institutionalized settings, while EMDEs require capacity building and international cooperation to address barriers. This study highlights the importance of tailoring CRFPs to specific contexts, emphasizing policy sequencing, enforcement, and capacity building. By identifying global and regional variations, the findings provide actionable insights for aligning financial systems with climate goals, fostering a sustainable low-carbon transition, and addressing equity challenges.

摘要

本研究考察了2000年至2023年期间气候相关金融政策(CRFP)如何在87个国家支持脱碳和可再生能源转型。利用政策排序得分(PSS)和约束力加权采用指标,本研究探讨了在不同经济和制度背景下CRFP、二氧化碳排放和可再生能源生产(REP)之间的关系。研究结果显示结果存在显著差异。发达经济体和经合组织国家利用结构化政策和强大的制度来实现稳定的减排和REP增长,在更高的政策强度下收益递减。新兴市场和发展中经济体(EMDE)面临制度和结构约束,但对有针对性的政策表现出强烈反应,特别是在撒哈拉以南非洲和南亚,那里可再生能源增长潜力显著。拉丁美洲和东亚等地区呈现出混合趋势,反映了独特的挑战和机遇。具有约束力的政策对环境结果至关重要,特别是在制度化环境中,而EMDE需要能力建设和国际合作来应对障碍。本研究强调了使CRFP适应特定背景的重要性,强调政策排序、执行和能力建设。通过识别全球和区域差异,研究结果为使金融系统与气候目标保持一致、促进可持续的低碳转型以及应对公平挑战提供了可操作的见解。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f95/11724838/7159eec2e7a9/41598_2025_85127_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f95/11724838/995755058076/41598_2025_85127_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f95/11724838/5e4ec81d42e9/41598_2025_85127_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f95/11724838/7c7cc0c63542/41598_2025_85127_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f95/11724838/6c4a14398468/41598_2025_85127_Fig11_HTML.jpg

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