中国における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 CO 2 emissions in China: a rolling window analysis (2000–2023) (原題)
Ihsen Abid
🤖 gxceed AI 要約
日本語
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年以降弱まるが正のままで、完全なデカップリングは未達成。クリーンエネルギー金融は遅れて負の効果、工業成長は構造転換で有意性を失う。政策主導の構造変革が排出削減に重要と示唆。
English
This study analyzes time-varying determinants of per capita CO2 emissions in China (2000-2023) using rolling window OLS. GDP-emissions link weakens but remains positive, indicating incomplete decoupling. Clean energy finance shows delayed negative effects, while industrial growth loses significance due to structural transformation. Policy-mediated structural change is key to mitigation.
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
中国の排出削減が政策・構造転換に依存することを示し、日本のアジア向け環境協力やグリーン金融戦略に示唆。日本の排出削減政策の時間的効果評価にも応用可能。
In the global GX context
Provides empirical evidence on policy-driven decarbonization in China, relevant to global climate finance and structural transformation debates. Offers insights for ISSB-aligned disclosure on transition risks in emerging economies.
👥 読者別の含意
🔬研究者:Time-varying methods for emission drivers; useful for comparative studies on decoupling.
🏢実務担当者:Insights on green finance effectiveness and structural shifts for supply chain planning.
🏛政策担当者:Evidence for adaptive policies and green finance scaling to meet carbon targets.
📄 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/10.1080/21606544.2026.2714390first seen 2026-08-30 04:35:51
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