From Digital Trade to Climate Gains: How Global Value Chains and Carbon Pricing Drive CO2 Reductions in OECD Economies
デジタル貿易から気候利益へ：グローバルバリューチェーンと炭素価格がOECD経済のCO2削減を促進する方法 (AI 翻訳)
Nour A. J. Azam, Yao Liu, Sajal Kabiraj, Mohammed Azam, Omar Abu Risha
🤖 gxceed AI 要約
日本語
本研究は、OECD38か国の2000〜2024年の月次パネルデータを用い、デジタル貿易とグローバルバリューチェーン（GVC）がCO2排出削減に与える影響を分析。炭素価格が1トンあたり40ドルを超えると排出量が有意に減少すること、AI物流の導入がデジタル貿易の環境効果を高めることなどを示した。再生可能エネルギーの導入と規制の厳格化がこれらの効果を補強する。
English
This study uses monthly panel data from 38 OECD economies (2000-2024) to analyze how digital trade and global value chains (GVCs) affect CO2 reductions. It finds a carbon pricing threshold of USD 40/tonne above which emissions drop significantly, and that AI-enabled logistics amplify the environmental benefits of digital trade. Renewable energy adoption and regulatory stringency reinforce these effects.
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
日本では2023年度から炭素価格の段階的導入が進んでおり、本論文のUSD 40/トン閾値は政策設計に直接的な示唆を与える。また、GVC参加とデジタル貿易の環境効果が条件付きである点は、日本のサプライチェーンDX推進において考慮すべき要素を提示する。
In the global GX context
The finding of a USD 40/tonne carbon pricing threshold offers empirical guidance for jurisdictions like the EU (ETS) and Canada. The conditional role of digital trade via AI logistics contributes to the debate on technology-enabled decarbonization within global value chains, relevant for ISSB and TCFD-aligned transition planning.
👥 読者別の含意
🔬研究者:Provides evidence on conditional effects of digital trade and carbon pricing thresholds, useful for scholars studying climate policy interactions and GVC decarbonization.
🏢実務担当者:Highlights that AI logistics and carbon pricing above USD 40/tonne can enhance digital trade's emission reductions, informing corporate climate strategy and supply chain management.
🏛政策担当者:Identifies a critical carbon price threshold and the importance of complementary renewable energy and digital infrastructure policies for effective decarbonization.
📄 Abstract（原文）
This study examines how digital trade contributes to decarbonization within global value chains (GVCs), focusing on the roles of AI-enabled logistics, carbon pricing, and renewable energy policy. Using a monthly panel of 38 OECD economies from 2000 to 2024, we combine econometric models with machine-learning techniques to identify threshold effects and conditional relationships. The empirical specification includes fixed effects, interaction terms for AI-enhanced logistics, and carbon-pricing threshold analysis. At the same time, structural equation modelling (SEM) is used to assess mediation through renewable energy and regulatory stringency. The results indicate that GVC participation is significantly associated with lower CO2 emissions (β = −0.064, p < 0.01). Digital trade alone is not statistically significant (β = −0.030), but its environmental effect becomes stronger when combined with AI-enhanced logistics. We identify a carbon-pricing threshold of USD 40 per tonne, above which emissions decline significantly (Δ = −15%, p < 0.01). Renewable energy adoption further reinforces the beneficial effect of digital trade under stronger regulatory conditions. These findings suggest that the emissions effects of digital trade are conditional rather than uniform and depend on complementary policy, technological, and energy factors. While the analysis is limited to OECD economies and monthly aggregate data, the study helps explain mixed findings in the literature by identifying the conditions under which digital trade is more likely to support emissions reduction.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su18084142first seen 2026-05-05 19:15:18
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。