Sustainable Development: Perspectives From Artificial Intelligence, Green Bonds, Green Economy, and Energy Innovation
持続可能な開発：人工知能、グリーンボンド、グリーン経済、エネルギー革新からの展望 (AI 翻訳)
Sunil Tiwari, Kamel Si Mohammed, Daniel Balsalobre‐Lorente
🤖 gxceed AI 要約
日本語
本研究は、AI、グリーン経済、クリーンエネルギー革新、グリーンファイナンスの持続可能な開発における相乗効果を、R2分解連結性とポートフォリオ分析を用いて検証。2018年2月から2023年9月の日次データを分析し、変数間の総連結指数が平均55%であることや、COVID-19パンデミックやロシア・ウクライナ紛争時にピークを迎えることを発見。投資ポートフォリオは高いヘッジ効果を示し、グリーンボンドやフィンテック、エネルギー転換への政策的含意を提示する。
English
This study examines the synergistic roles of AI, green economy, clean energy innovation, and green finance in achieving sustainable development using R2 decomposed connectedness and portfolio analysis. Analyzing daily data from Feb 2018 to Sep 2023, it finds an average total connectedness index of 55%, with peaks during COVID-19 and the Russia-Ukraine conflict. Portfolios with eco-friendly assets show strong hedging effectiveness, and policy implications for green bonds, fintech, and energy transition are recommended.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
本研究はグリーンボンドやAIを活用した持続可能な開発の可能性を示しており、日本のグリーンファイナンス拡大やエネルギー転換政策に示唆を与える。ただし、日本独自のデータは含まれていない。
In the global GX context
This paper provides empirical evidence on the interconnectedness of AI, green bonds, clean energy, and green economy, offering insights for portfolio diversification and policy-making in the context of global sustainable development.
👥 読者別の含意
🔬研究者:Researchers can use this methodology to analyze spillover effects in other sustainable asset classes.
🏢実務担当者:Portfolio managers can consider the hedging benefits of combining AI, green bonds, and clean energy assets.
🏛政策担当者:Policymakers can leverage the findings to promote integrated strategies for green finance and energy transition.
📄 Abstract（原文）
ABSTRACT In an era of global uncertainty and challenges, it is important to establish integration between environmental, economic, and technological strategies to achieve sustainable development. In this regard, this study investigates the synergistic roles of artificial intelligence (AI), green economy, clean energy innovation, and green finance in achieving sustainable development. In contrast to conventional methodologies, the present research employs a novel approach: R2 decomposed connectedness and portfolio analysis, using daily data from February 27, 2018, to September 9, 2023. These approaches measure how much of a shock to one variable is explained by shocks to others, thereby identifying the net transmitters and receivers of risks and shocks. The findings reveal an average total connectedness index of 55% among these variables, with significant peaks observed during periods of heightened instability, such as the COVID‐19 pandemic and the Russia‐Ukraine conflict. A decomposition of this connectedness shows that 29% stems from contemporaneous interactions, while 26% is attributable to lagged effects. Investment portfolios incorporating eco‐friendly assets, AI‐focused securities, and clean energy tokens exhibit strong hedging effectiveness, particularly during volatile market conditions. This underscores the capacity of AI, green economic principles, clean energy innovation, and green finance to collectively facilitate sustainable development and mitigate environmental emissions and climate impacts. The study recommends policy and practical implications focusing on green bonds, financial technology (Fintech), and energy transition across various levels.
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.1002/sd.70603first seen 2026-05-14 21:33:19
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