危機はエネルギー転換金属市場を統合するのか分断するのか？コネクテッドネスに基づく危機類型論からの証拠
Do crises integrate or fragment energy transition metals markets? Evidence from a connectedness-based crisis typology (原題)
Abdulla Al-Haddad, Azzam Abu-Rayash
🤖 gxceed AI 要約
日本語
本論文は、2017〜2025年の11の危機事象がエネルギー転換金属（ETM）17種のリターン波及性に与えた影響を、Diebold–Yılmazコネクテッドネス手法で分析し、「統合vs分断」「不安定vs安定」の2軸で危機を類型化する。供給側ショック（武力紛争・二国間貿易制限）は市場の連動性を一貫して低下させる一方、需要側ショック（パンデミック・金融引き締め・金融危機）は連動性を高めるという「分断のパラドックス」を発見した。この二分法は25通りのイベント窓設定で頑健に維持され、危機が一律にシステミックリスクを増幅するという通説に反証を突きつける。
English
Using daily data on 17 energy transition metals and rolling Diebold–Yılmaz connectedness, the paper builds a two-dimensional crisis typology (integration vs. fragmentation; volatile vs. stable) across 11 crisis events from 2017–2025. It finds a fragmentation paradox: supply-side shocks (conflicts, trade restrictions) reduce market connectedness, while demand-side shocks (pandemics, monetary tightening, financial crises) increase it — robust across 25 event-window specifications. The mechanism rests on asymmetric idiosyncratic transmission for supply shocks versus common macroeconomic channels for demand shocks, with implications for strategic reserves, hedging, and critical-mineral risk.
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
日本は蓄電池・EV・半導体向けに多くの重要鉱物を輸入依存しており、経済安全保障や資源外交の文脈で本論文の「供給ショックは分断的」という知見は戦略備蓄や調達多角化の政策設計に示唆を与える。SSBJ開示とは直接の接点は薄いが、Scope 3上流の調達リスク評価に援用可能。
In the global GX context
As ISSB/CSRD push companies to disclose supply-chain and physical/transition risk, this paper offers a quantitative lens on how geopolitical shocks to critical minerals transmit differently from demand shocks — useful for scenario analysis and critical-mineral risk framing in transition plans. It challenges the contagion assumption underlying many systemic-risk models used in climate-financial stress testing.
👥 読者別の含意
🔬研究者:コネクテッドネス分析における「危機＝一律に連動性上昇」という前提を、供給/需要ショックの非対称性で修正する実証的枠組みを提供する。
🏢実務担当者:重要鉱物の調達ポートフォリオやヘッジ戦略を設計する際、地政学リスクは伝染的ではなくモジュール的である点をリスク評価に反映できる。
🏛政策担当者:戦略備蓄や重要鉱物の経済安全保障政策において、供給途絶は市場分断を通じて個別金属に非対称に波及する点を考慮すべき。
📄 Abstract（原文）
This paper develops a two-dimensional crisis typology that classifies the impact of major crisis episodes on return spillover connectedness across energy transition metals (ETM) markets. Using daily data for 17 metals, spanning base metals, precious metals, battery metals, and technology metals, and the rolling-window Diebold–Yılmaz (2012) connectedness framework, the paper classifies 11 crisis events between 2017 and 2025 along two orthogonal axes: the direction of the connectedness shift (integration vs. fragmentation) and the stability of the response (volatile vs. stable), with the latter benchmarked against a bootstrap-derived threshold from pre-crisis markets. The typology reveals a fragmentation paradox: supply-side shocks (armed conflicts and bilateral trade restrictions) consistently decrease market connectedness, while demand-side shocks (pandemics, monetary tightening, and financial crises) consistently increase it. This dichotomy, which is robustly preserved across all 25 event-study window specifications, challenges the prevailing assumption in the connectedness literature that crises uniformly amplify systemic risk through heightened spillovers. The mechanism is grounded in the distinction between common-factor and idiosyncratic transmission channels: supply disruptions affect individual metals asymmetrically based on their geographic exposure, fragmenting the co-movement structure, while demand shocks operate through common macroeconomic channels that drive all metals together. The typology has implications for strategic reserves policy, portfolio hedging, and energy transition risk assessment, suggesting that geopolitical risk to critical minerals supply chains is more modular than the contagion hypothesis predicts.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.eneco.2026.109671first seen 2026-11-15 04:49:32
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。