E7新興経済における消費ベース炭素排出の要因：時間周波数・分布上の異質性
Time–frequency and distributional heterogeneity in the drivers of consumption-based carbon emissions across the E7 emerging economies (原題)
Fakhrullah Fakhrullah, Mingxing Li, Sher Khan, Marian Šuplata
🤖 gxceed AI 要約
日本語
本論文は、中国・インド・ブラジル・メキシコ・ロシア・インドネシア・トルコのE7諸国を対象に、2000〜2021年の消費ベース（貿易調整後）CO2排出の要因を再検証する。MMQR、ウェーブレット分位相関、クロス・クォンタイルグラムを組み合わせ、所得弾力性が排出分布に沿って低下すること、再生可能エネルギー普及が高排出域で最も排出削減的に働くことを示す。単一の平均弾力性では説明できない異質性を明らかにし、脱炭素政策は時間軸と分布を考慮すべきと主張する。
English
This paper re-examines drivers of consumption-based CO2 emissions across the E7 emerging economies (2000–2021) using MMQR, wavelet quantile correlation, and cross-quantilogram methods. Income elasticity declines across the emission distribution, while renewable penetration reduces emissions most strongly where emissions are highest. The authors argue for horizon-sensitive, distribution-contingent decarbonization policies rather than one-size-fits-all approaches.
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
日本企業のサプライチェーン排出（Scope 3）管理や、E7諸国での事業展開・調達リスク評価に間接的に関連。SSBJ開示の枠組みとは直接接続しないが、新興国拠点の排出プロファイル理解に資する。
In the global GX context
This study contributes to the global climate policy literature by demonstrating methodological heterogeneity in emission drivers across major emerging economies. It offers empirical nuance for transition finance and country-level decarbonization pathway design, though it does not directly engage TCFD/ISSB disclosure frameworks.
👥 読者別の含意
🔬研究者:E7諸国の排出要因分析における分位・周波数アプローチの適用例として、手法論的示唆が得られる。
🏢実務担当者:新興国サプライチェーンを持つ企業は、調達先国の排出特性を分布・時間軸で理解する材料として活用可能。
🏛政策担当者:新興国向け脱炭素支援策を設計する際、一律の弾力性仮定を避け、所得水準や排出分布に応じた政策設計の必要性を示唆。
📄 Abstract（原文）
Introduction Reconciling rapid economic advancement with credible climate stewardship remains the defining tension of the sustainable-development agenda in the world’s fastest-growing emerging markets. This paper re-examines the drivers of consumption-based (trade-adjusted) carbon dioxide emissions across the seven largest emerging economies China, India, Brazil, Mexico, Russia, Indonesia and Türkiye over 2000–2021, and asks whether a single average elasticity can describe economies that differ both in emission regime and in the horizon over which their drivers operate. Methods The panel is assembled entirely from observed data published by the Global Carbon Project and the World Bank. We couple the Method of Moments Quantile Regression (MMQR) of Machado and Santos Silva with a cross-sectionally augmented heterogeneous mean-group benchmark and two techniques still rare in environmental economics: the Wavelet Quantile Correlation (WQC) and the cross-quantilogram. Second-generation diagnostics for cross-sectional dependence, slope homogeneity, panel unit roots and cointegration precede estimation, and all inference is corroborated by a wild cluster bootstrap. Results The diagnostics confirm cross-sectional dependence, decisively heterogeneous slopes and first-order integration, while the evidence for a single cointegrating vector is only borderline a nuance we treat transparently. The income elasticity is positive throughout and its point estimates decline across the emission distribution (0.69 to 0.61), although a formal test cannot reject equality across quantiles; renewable-energy penetration is emission-reducing everywhere and most strongly where emissions are highest. An augmented specification with squared log-income yields a concave but within-sample monotonic profile, so we describe a quantile-declining scale elasticity rather than an inverted-U. The wavelet evidence points to low-frequency dominance, though the eight-to-sixteen-year band rests on few boundary-free coefficients and is read cautiously, and the cross-quantilogram locates directional predictability in the lower and central quantiles. Discussion Looking simultaneously through the quantile and the frequency lens materially changes what the data appear to say about the E7 transition. The findings caution against one-size-fits-all decarbonisation and argue for horizon-sensitive, distribution-contingent instruments aligned with Sustainable Development Goals 7, 12 and 13.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3389/fenvs.2026.1933128first seen 2026-10-02 04:58:08
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