[Impact of China's Digital Economy on the Spatial Correlation Network of Carbon Emissions from a Carbon Transfer Perspective].
炭素移転の視点から見た中国のデジタル経済が炭素排出の空間的相関ネットワークに与える影響 (AI 翻訳)
Shu-Qiang Jiang, Zhi-Liang Dong
🤖 gxceed AI 要約
日本語
本研究は2010～2022年の中国30省パネルデータを用い、複雑ネットワーク分析と計量経済モデルを統合してデジタル経済が炭素排出の空間的相関ネットワークに与える動的影響を実証した。デジタル経済指数の1単位上昇は、地域が排出送信ノードとなる確率を8.473倍にする一方、受信ノードとなる確率を0.338倍に低下させる。また、コア・ペリフェリー構造や空間的・時間的異質性を明らかにした。
English
Using panel data from 30 Chinese provinces (2010-2022) and integrating complex network analysis with econometric modeling, this study empirically examines the dynamic impact of the digital economy on the spatial correlation network of carbon emissions. A one-unit increase in the digital economy index raises the probability of a region becoming a sending node by 8.473 times while reducing its likelihood of being a receiving node to 0.338 times. Core-periphery structures and spatiotemporal heterogeneity are revealed.
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
中国のデジタル経済と炭素排出ネットワークの関係を実証。日本のGX政策においてもデジタル化と排出削減の連携が注目される中、地域間排出移転のメカニズム理解に示唆を与える。SSBJやScope3対応におけるサプライチェーン排出構造分析にも応用可能。
In the global GX context
This paper empirically demonstrates how the digital economy reshapes spatial emission networks in China, offering insights for coordinated regional climate governance. Globally, it contributes to understanding cross-boundary emission spillovers relevant to TCFD/ISSB frameworks and transition finance.
👥 読者別の含意
🔬研究者:Provides insights on spatial dynamics of carbon emissions influenced by the digital economy, useful for researchers studying emission networks and digitalization.
🏛政策担当者:Highlights the need for coordinated regional climate policies and the role of the digital economy in shaping emission patterns.
📄 Abstract（原文）
The digital economy serves as the core driver for industrial structure transformation and upgrading， playing a critical leveraging role in advancing carbon emission reduction. Based on panel data from 30 Chinese provinces spanning from 2010 to 2022， this study constructs a spatial correlation network of carbon emissions and employs integrated methodologies of complex network analysis and econometric modeling to empirically examine the dynamic impact of the digital economy on this network. The results reveal three key findings： First， the spatial correlation network exhibited significant temporal volatility with macro-level spatial heterogeneity and polarization， demonstrating a pronounced core-periphery structure. Second， hierarchical and reciprocal patterns dominated the network's microstructure， indicating its preliminary developmental stage and substantial structural optimization potential. Third， the digital economy's impact on carbon emission correlations showed spatiotemporal heterogeneity： a one-unit increase in the digital economy index elevated a region's probability of becoming a sending node in the network by a factor of 8.473 while reducing its likelihood of being a receiving node to 0.338 times the original state. Nevertheless， region-specific attributes and developmental stages yielded more nuanced effects. The in-depth investigation into how the digital economy influences carbon emission networks provides actionable insights for coordinated regional climate governance.
🔗 Provenance — このレコードを発見したソース
- openalex https://pubmed.ncbi.nlm.nih.gov/42473360first seen 2026-07-22 05:13:15
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