高炭素・低炭素製造業間のリスク波及:低炭素政策不確実性下における持続可能な産業転換への示唆
Risk Spillovers Between High-Carbon and Low-Carbon Manufacturing Industries: Implications for Sustainable Industrial Transformation Under Low-Carbon Policy Uncertainty (原題)
Jining Wang, Xiaoyu Xia, Lei Wang, Dian Sheng
🤖 gxceed AI 要約
日本語
TVP-VAR-BKモデルと周波数領域の波及効果手法を用い、高炭素・低炭素製造業間のリスク波及の動態と構造を分析。化学産業と4つの低炭素産業が純リスク送り手となる一方、他の高炭素産業は受け手となる階層的パターンを確認。低炭素政策不確実性指数(LCPU)を構築し、そのショックが主に短期で波及効果に影響し、業種により反応の大きさと経路が異なることを示した。
English
Using a TVP-VAR-BK model and frequency-domain spillover methods, the paper examines risk spillovers between high-carbon and low-carbon manufacturing industries. Chemical and four low-carbon industries act as net risk transmitters, while other high-carbon industries are net receivers, with spillovers mostly short-term. A low-carbon policy uncertainty index (LCPU) is constructed, and TVP-SV-VAR shows LCPU shocks affect spillovers mainly in the short term with industry heterogeneity.
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
低炭素政策の不確実性が産業間のリスク連関に与える影響を定量化する視点は、日本のGX政策(GX推進法・カーボンプライシング導入議論)が企業の資本コストや業種間リスク配分に及ぼす影響を考える上で参考になる。ただし分析対象は中国産業であり、日本企業への直接適用には注意を要する。
In the global GX context
The paper contributes to global climate-policy-risk scholarship by quantifying how low-carbon policy uncertainty transmits risk across manufacturing value chains, a lens relevant to transition-finance risk assessment and ISSB/TCFD scenario analysis. Its frequency-domain approach offers a methodological template for studying policy-driven transition risk in other jurisdictions.
👥 読者別の含意
🔬研究者:政策不確実性と産業間リスク波及を周波数領域で捉える計量手法の応用例として参考になる。
🏢実務担当者:低炭素政策の不確実性が業種間のリスク連鎖に及ぶことを踏まえ、サプライチェーン上の移行リスク評価に示唆を得られる。
🏛政策担当者:低炭素政策の不確実性が産業安定性に与える波及経路を理解し、政策の予見可能性向上の重要性を検討する材料となる。
📄 Abstract(原文)
The sustainable transformation of manufacturing industries requires a better understanding of risk linkages between high-carbon and low-carbon sectors, particularly under changing low-carbon policy conditions. This paper employs the TVP-VAR-BK model and the frequency-domain spillover method to systematically investigate the risk spillover characteristics and evolutionary patterns between high-carbon and low-carbon manufacturing industries from both dynamic and static dimensions. On this basis, a low-carbon policy uncertainty index (LCPU) is constructed, and the TVP-SV-VAR model is further applied to investigate the dynamic responses of risk spillovers between high-carbon and low-carbon manufacturing industries to LCPU shocks. The results show that: (1) Risk linkages exist between high-carbon and low-carbon manufacturing industries and exhibit a hierarchical pattern along the industrial chain. In terms of overall risk spillovers, the Chemical Industry (CH) and the four low-carbon manufacturing industries act as net risk transmitters within the system, while the other three high-carbon manufacturing industries mainly serve as net risk receivers. (2) Risk spillovers between high-carbon and low-carbon manufacturing industries are predominantly short-term. In the short term, the Chemical Industry (CH) exhibits a strong net risk transmission effect, whereas in the long term, all four low-carbon manufacturing industries act as net risk transmitters. (3) There is a pronounced dynamic relationship between changes in low-carbon policy uncertainty and risk linkages across manufacturing industries. The effects of LCPU shocks are concentrated primarily in the short term and decay rapidly as the forecast horizon increases. Moreover, high-carbon and low-carbon manufacturing industries differ in both the magnitude of their responses and their dynamic response paths, exhibiting clear time-varying characteristics and industry heterogeneity. These findings provide empirical evidence for improving cross-industry risk management and enhancing policy coordination, offering practical implications for maintaining industrial stability and supporting sustainable manufacturing transformation.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su182010684first seen 2026-10-23 05:13:00 · last seen 2026-11-06 04:48:26
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