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COP30アジェンダ下のグリーン成長指数：G7諸国における農業・人工知能・エネルギー転換の役割

Green Growth Index under the COP30 Agenda: The Roles of Agriculture, Artificial Intelligence and Energy Transition in G7 Countries (原題)

Bahar Özbek, Sefa Özbek, Mustafa Naimoğlu

Tarım Bilimleri Dergisi📚 査読済 / ジャーナル2026-10-12#エネルギー転換対象セクター: cross_sector
DOI: 10.15832/ankutbd.1884343
原典: https://doi.org/10.15832/ankutbd.1884343
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🤖 gxceed AI 要約

日本語

G7諸国の2010〜2022年データを用い、グリーン成長指数の規定要因をパネルデータ分析で検証。農業付加価値、人工知能、再エネ消費、環境税が有意に正の効果を持つ一方、経済自由度は非有意。農業とAIがグリーン成長を牽引することを示し、再エネと環境税の負の外部性抑制効果を裏付ける。

English

Using 2010–2022 G7 panel data with cross-sectional dependence and structural-break tests, the study examines determinants of a green growth index. Agricultural value added, AI, renewable energy, and environmental taxes show significant positive effects, while economic freedom is insignificant. Results highlight agriculture and AI as green growth drivers and confirm the role of renewables and environmental taxes in curbing negative externalities.

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

環境税と再エネをグリーン成長の実証的ドライバーとして示す点は、日本でのカーボンプライシング議論やGX推進政策の効果検証に示唆を与える。AI活用を成長要因として位置づける視点は、日本のGX×デジタル投資政策とも接続しうる。

In the global GX context

The paper adds macro-level empirical evidence to the global green growth and COP30 policy debate, quantifying environmental taxes and renewables as growth-compatible levers. Its inclusion of AI as a green growth determinant connects to the emerging AI-for-sustainability agenda, though it stops short of disclosure or ESG-rating applications relevant to ISSB/CSRD frameworks.

👥 読者別の含意

🔬研究者:G7パネルでのグリーン成長規定要因の実証手法（PANIC Fourier・構造変化考慮の共和分）とAI・環境税の効果推定が参考になる。

🏢実務担当者:環境税や再エネ調達がマクロのグリーン成長と両立する証拠として、政策対応・投資説明の背景資料に使える。

🏛政策担当者:環境税と再エネ支援、農業・AI投資の組み合わせがグリーン成長に寄与することを示す政策根拠として参照可能。

📄 Abstract（原文）

Sustainable development is among the most important global goals. In this context, economic, environmental, and social sustainability constitute three important components. Green growth is among the main focuses outlined in the COP30 Agenda. COP30 places great emphasis on a green growth approach that takes environmental issues into account and pays attention to combating the climate crisis. This study focuses on the determinants of green growth in the G7 countries, which stand out as the most developed group of countries. Within this scope, the role of agriculture and artificial intelligence is highlighted. Using data from 2010-2022 for G7 countries, the study investigates the relationship between green growth and agriculture, artificial intelligence, renewable energy, environmental taxes, and economic freedoms. Panel data techniques that consider cross-sectional dependence are used in estimating the broad empirical model. In this context, the PANIC Fourier unit root test and panel cointegration tests that take structural breaks into account are used. The empirical findings reveal that agricultural value added, artificial intelligence, renewable energy consumption, and environmental taxes have a statistically significant and positive effect on the green economic growth index; while the effect of the economic freedom index is statistically insignificant. These results highlight the leading role of the agricultural sector and artificial intelligence in achieving green growth. On the other hand, the importance of renewable energy and environmental taxes in preventing negative externalities of economic growth has also been demonstrated. These results offer important policy implications for G7 countries, shedding light on the factors that pave the way for sustainable development.

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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。