気候政策の不確実性とリスク波及：中国炭素市場からの証拠
Climate policy uncertainty and risk spillovers: Evidence from China’s carbon markets (原題)
Jinjin Tian, Li Chen, Yong Ma, Ruixin Zhong
🤖 gxceed AI 要約
日本語
中国8地域の炭素市場を対象に、TVP-VAR接続性フレームワーク、GARCH-MIDAS、ネットワーク分析を統合し、気候政策不確実性（CPU）とリスク波及の関係を2018年1月〜2024年5月で分析。リスク波及は非対称かつ時変的で、深圳・重慶・福建が純送信者、北京・湖北・天津が吸収者となる。CPUは長期の炭素価格ボラティリティを増幅する一方、短期の総リスク波及を一時的に抑制し、市場統合の深化とともに効果が弱まる。
English
Using provincial CPU indices, TVP-VAR connectedness, GARCH-MIDAS and network analysis, this study examines dynamic risk spillovers across China's eight regional carbon markets (Jan 2018–May 2024). Spillovers are asymmetric and time-varying: Shenzhen, Chongqing and Fujian are net transmitters; Beijing, Hubei and Tianjin absorb shocks. CPU amplifies long-term carbon price volatility but temporarily suppresses short-term total spillovers, weakening as market integration deepens.
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
中国の全国炭素市場（全国碳排放権交易市場）と地域市場の統合過程は、日本がGXリーグ・カーボンプライシング構想や東証カーボン・クレジット市場を設計する上で参照価値が高い。政策不確実性が炭素価格ボラティリティに与える影響は、日本企業の炭素価格リスク管理や内部炭素価格設定の前提にも示唆を与える。
In the global GX context
As the world's largest carbon market system matures, evidence on how policy uncertainty transmits across regional carbon markets informs the design of linked and integrated carbon markets globally. It contributes to climate-related financial risk literature relevant to TCFD/ISSB risk disclosure and transition finance, showing policy-driven vs market-driven risk dynamics vary by horizon.
👥 読者別の含意
🔬研究者:炭素市場のリスク波及と政策不確実性の時変的関係を定量化する手法（TVP-VAR＋GARCH-MIDAS＋ネットワーク）の応用例として有用。
🏢実務担当者:炭素価格のボラティリティと政策リスクを踏まえた炭素コスト・ヘッジ戦略の検討材料になる。
🏛政策担当者:炭素市場統合の深化に伴い政策不確実性の波及効果が変化する点は、市場安定化策や政策予見性確保の設計に示唆を与える。
📄 Abstract（原文）
Under China’s “dual carbon” strategy, carbon emissions trading has become a key instrument for mitigating climate-related financial risks. However, climate policy uncertainty (CPU) has emerged as an important source of systemic risk, reshaping volatility dynamics and cross-regional risk spillovers in carbon markets. This study examines how CPU is associated with the structure and transmission of risks within China’s carbon market system. Using provincial-level CPU indices, we integrate a TVP-VAR-based connectedness framework with GARCH-MIDAS models and network analysis to investigate dynamic risk spillovers across China’s eight regional carbon markets from January 2018 to May 2024. The results show that risk spillovers are highly asymmetric and time-varying: Shenzhen, Chongqing, and Fujian consistently act as net risk transmitters, while Beijing, Hubei, and Tianjin mainly absorb external shocks. CPU significantly amplifies long-term carbon price volatility but temporarily suppresses short-term total risk spillovers by dampening market expectations, an effect that weakens as market integration deepens. Moreover, the impact of CPU on regional net spillovers is heterogeneous, reflecting differences in economic structure and policy sensitivity. Overall, the findings suggest a descriptive pattern in which the relative importance of policy-driven and market-driven factors varies across time horizons, warranting further formal investigation and provide important implications for climate-related risk management and market stability.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.iref.2026.105917first seen 2026-10-05 05:28:14
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