ASEAN5における石油・石炭・再生可能エネルギー消費、経済成長、貿易が炭素排出に与える影響：パネルARDLとMMQR分析からの知見
The effect of oil, coal and renewable energy consumption, economic growth and trade on carbon emissions in ASEAN-5: Insights from panel ARDL and method of moments quantile regression (MMQR) analysis (原題)
Çiler SİGEZE, Esra Ballı, Mehmet Sedat UĞUR, Abdurrahman Nazif Çatık, Gulnoza Matyakubova, Bekhzod Kuziboev, Jamshid Pardaev, O'g'iljon Artiqova
🤖 gxceed AI 要約
日本語
本論文はASEAN5カ国を対象に1971〜2020年のデータを用い、石油・石炭・再生可能エネルギー消費、GDP、貿易がCO2排出に与える影響をパネルARDLとMMQRで分析した。石油・石炭消費とGDPは排出を有意に増加させ、再生可能エネルギーは削減に寄与する。高排出国ではGDPと再エネの効果がより強く、貿易も高排出国で有意となる。石炭・石油依存の低減と再エネ導入加速が政策優先課題と結論づける。
English
Using panel ARDL and MMQR on ASEAN-5 data (1971–2020), this study examines how oil, coal, renewable energy, GDP and trade affect CO2 emissions. Oil, coal and GDP raise emissions, while renewables reduce them; effects strengthen at higher quantiles. It calls for cutting coal/oil dependence and accelerating renewable deployment, especially in high-emitting countries.
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
日本企業にとってASEANは主要な生産・調達拠点であり、現地の排出構造と再エネ移行速度はScope 3やサプライチェーン脱炭素戦略に直結する。日本国内のSSBJ開示対応というより、海外拠点の移行リスク評価に資する。
In the global GX context
Adds emerging-market empirical evidence to the global energy-transition literature, complementing TCFD/ISSB scenario work by quantifying how fuel mix and growth drive emissions across ASEAN-5. Useful for transition-finance and supply-chain decarbonization analysis in a key manufacturing region.
👥 読者別の含意
🔬研究者:パネルARDLとMMQRを組み合わせ、排出分布の分位点ごとにエネルギー・成長・貿易の効果差を示す実証手法の参照例となる。
🏢実務担当者:ASEAN拠点を持つ企業は、現地の石炭・石油依存度と再エネ移行速度を踏まえ、Scope 3や調達先の移行リスクを評価できる。
🏛政策担当者:ASEAN各国の石炭・石油依存低減と再エネ導入加速を優先する政策設計の根拠として参照可能。
📄 Abstract（原文）
Type of the article: Research ArticleAbstractThis paper investigates the impact of oil, coal, renewable energy consumption, CO2 emissions in the ASEAN-5 countries for the period from 1971 to 2020 utilizing the panel ARDL and MMQR models. The panel autoregressive distributed lag (ARDL) model estimates average short- and long-run effects, whereas the method of moments quantile regression (MMQR), a panel quantile technique, estimates how these effects vary across the distribution of emissions. The MMQR results shed light on the impacts of variables on CO2 emissions estimated at different emission levels. The results show that oil, coal consumption, and GDP are significant factors influencing CO2 emissions. Conversely, renewable energy sources contribute significantly to reductions in CO2 emissions. Also, the results reveal that trade activities have a significant impact on emissions in countries exhibiting high emission levels. In particular, the effects of GDP and renewable energy become stronger at higher quantiles, whereas those of oil and coal remain relatively stable. Furthermore, the panel causality tests reveal bidirectional causality between CO2 emissions and oil consumption and economic growth. The results also support unidirectional causality from coal consumption to emissions, and causality from emissions to renewable energy. The results indicate the need for comprehensive efforts across various policy areas to reduce emissions and address climate change. Reducing coal and oil dependence should be a priority for all ASEAN-5 countries, while faster renewable deployment matters most for high emitters.AcknowledgmentEsra Balli would like to acknowledge the financial support provided by the Council of Higher Education (YÖK) through the Academic Development Program (AKAP).
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.21511/ee.17(3).2026.17first seen 2026-10-02 04:48:04
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