中国のCO2排出の時間変動要因：ローリング窓分析（2000〜2023年）
Time-varying drivers of CO2 emissions in China: a rolling window analysis (2000–2023) (原題)
Ihsen Abid
🤖 gxceed AI 要約
日本語
本研究は2000〜2023年の中国の一人当たりCO2排出量の決定要因を、ローリング窓OLSで分析。GDPとの関係は2010年以降弱まるが未だ非結合は不完全。クリーンエネルギー金融は遅延効果を持つ。産業成長の影響は低下し、構造転換が示唆される。政策主導の構造変革が排出削減に重要と結論。
English
This study analyzes time-varying determinants of per capita CO2 emissions in China (2000-2023) using rolling window OLS. GDP-emissions link weakens post-2010 but remains positive, indicating incomplete decoupling. Clean energy finance shows delayed negative effects. Industrial growth loses significance, suggesting structural decarbonization. Policy-mediated transformation is key for China's dual carbon targets.
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
中国の排出動向は日本のサプライチェーン排出（Scope3）や国際的な気候政策に影響する。日本企業にとっては中国市場での事業リスク評価や、グリーンファイナンスの国際展開を考える上で参考になる。
In the global GX context
This paper contributes to global understanding of decoupling dynamics in a major emitter, relevant for transition finance and climate policy design. It highlights the role of green finance and institutional quality, informing ISSB-aligned disclosure and transition planning.
👥 読者別の含意
🔬研究者:Provides empirical evidence on time-varying drivers of emissions, useful for modeling and policy evaluation.
🏢実務担当者:Highlights the importance of green finance and structural transformation for companies operating in China.
🏛政策担当者:Offers insights for designing adaptive environmental policies and scaling up green finance instruments.
📄 Abstract（原文）
This study examines the time-varying determinants of per capita CO2 emissions in China over 2000–2023, focusing on how macroeconomic, financial, and institutional factors evolve. Using annual data from the World Bank and governance indicators, a rolling window Ordinary Least Squares (OLS) approach is employed to capture dynamic relationships between emissions and their drivers. The results show that the GDP–emissions relationship weakens after 2010 but remains positive, indicating incomplete decoupling. Clean energy finance exhibits delayed but increasingly negative effects, reflecting implementation lags. Industrial growth loses significance over time, indicating structural decarbonization, while labour force effects capture sectoral reallocation rather than scale effects. Political stability reduces emissions only when aligned with effective environmental enforcement. These findings demonstrate that emissions mitigation in China is driven by policy-mediated structural transformation rather than automatic economic adjustment. Based on these findings, the study recommends: (i) adopting adaptive, environmental policies that respond to evolving economic structures; (ii) scaling up green finance instruments – such as green bonds and international climate finance – to accelerate clean energy deployment; (iii) strengthening institutional quality and regulatory enforcement; and (iv) promoting structural transformation toward low-carbon and service-oriented sectors. These policy directions are essential to support China’s dual carbon targets of peaking emissions by 2030 and achieving carbon neutrality by 2060.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.6084/m9.figshare.33198180first seen 2026-08-31 04:54:27
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