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炭素市場とエネルギー化学市場間のリスク波及:多層ネットワークによる実証

Risk Spillovers Between Carbon and Energy Chemical Markets: Evidence from a Multi-Layer Network (原題)

Xin Sui, Jinhao Zhou, Lu Lu

Sustainability📚 査読済 / ジャーナル2026-11-07#炭素価格Origin: CN経営インパクト: 調達リスク対象セクター: chemicals
DOI: 10.3390/su182111379
原典: https://doi.org/10.3390/su182111379

🤖 gxceed AI 要約

日本語

本論文は周波数領域の多層ネットワーク手法を用い、炭素市場とエネルギー化学市場間のリスク波及を短期・中期・長期の時間スケールに分解して分析する。炭素市場は主に純リスク受容者、エネルギー化学市場は純リスク発信者であり、波及は短期層が支配的で時間軸が長くなるほど減衰する。炭素市場の構造的重要性は総じて低く層間で不均一だが、段階ごとに主要市場が交代することを示す。

English

Using a frequency-domain multi-layer network, this paper decomposes risk spillovers between carbon and energy chemical markets into short-, medium-, and long-term layers. Carbon markets are mainly net risk receivers while energy chemical markets are net transmitters, with spillovers dominated by the short-term layer and weakening over longer horizons. Carbon markets' structural importance is lower and uneven, with key markets rotating across phases, offering implications for collaborative risk regulation during the green transition.

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

炭素価格が産業セクターへ波及するリスク経路を示す点は、日本企業の炭素コスト感応度やGX推進下の財務リスク管理、SSBJ開示における気候関連リスク評価に示唆を与える。

In the global GX context

Adds a network-based, multi-timescale view of how carbon pricing transmits risk into industrial sectors, relevant to transition-risk assessment under TCFD/ISSB and to financial-stability debates around carbon market design.

👥 読者別の含意

🔬研究者:炭素市場と産業市場のリスク伝播を周波数・ネットワークで捉える実証手法の参考になる。

🏢実務担当者:炭素価格変動が自社サプライチェーンや調達コストへ波及する経路の理解に役立つ。

🏛政策担当者:炭素市場と産業市場の協調的なリスク規制設計を検討する際の根拠となる。

📄 Abstract(原文)

In the context of the low-carbon transition and sustainable development, this paper investigates risk spillovers between carbon and energy chemical markets by adopting a frequency-domain multi-layer network approach. Spillovers are decomposed into short-, medium-, and long-term frequency layers to distinguish risk spillovers across different time scales. Intra-layer weighted directed networks are constructed for each layer, and inter-layer connections are established between adjacent layers to form a multi-layer network. Change point identification is then applied to divide the sample into six phases. The empirical results are summarized as follows: First, carbon markets are predominantly net risk receivers, while energy chemical markets are predominantly net risk transmitters, although exceptions exist in both groups. Second, spillovers are dominated by the short-term frequency layer and diminish as the time scale lengthens. Third, the structural importance of carbon markets is generally lower and uneven across markets and frequency layers, whereas energy chemical markets maintain relatively stable cross-frequency-layer connections. Finally, the network positions of carbon markets evolve across phases, with key markets rotating over time, while energy chemical markets remain structurally dominant. These findings provide a frequency-domain multi-layer network perspective for understanding risk spillovers between carbon and energy chemical markets and offer implications for collaborative risk regulation, thereby contributing to financial stability and sustainable market development during the green transition.

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