排出削減の触媒か、炭素緩和の障壁か？中国における新型インフラが炭素排出に与える影響
A Catalyst for Emissions Reduction or a Barrier to Carbon Mitigation? The Impact of New-Type Infrastructure on Carbon Emissions in China (原題)
Mengdie Chen, Min Cheng, Xin Wang, Fangliang Wang
🤖 gxceed AI 要約
日本語
中国30省・2013〜2024年のパネルデータを用い、新型インフラ（NI）と炭素排出の関係を二方向固定効果・システムGMM・操作変数法で検証。NIと排出量には逆U字関係があり、産業構造合理化とグリーン技術革新が媒介する。この非線形関係は中西部のみで有意で、東部・東北部では確認されず、空間スピルオーバーも存在する。PSO-SVM予測と4シナリオ分析では、グリーン転換シナリオが最も早く低いピークに到達する。
English
Using panel data for 30 Chinese provinces (2013-2024), this study tests competing effects of new-type infrastructure (NI) on carbon emissions with two-way fixed effects, system GMM, and instrumental variables. It finds an inverted U-shaped relationship, mediated by industrial structure rationalization and green technological innovation, significant only in central and western regions, with cross-regional spatial spillovers. PSO-SVM forecasting across four scenarios shows emissions eventually decline, with the green-transition scenario peaking earliest and lowest.
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「Digital China」「Beautiful China」戦略を地域別に実装する必要性を示す研究。日本企業にとっては、中国拠点・サプライチェーンにおけるScope 3排出や移行リスク評価の際、地域差とインフラ投資の段階性を考慮する材料になる。SSBJ開示で中国事業の気候リスクを記述する際の背景情報として有用。
In the global GX context
This paper adds to the empirical literature on infrastructure-driven emissions pathways in emerging economies, relevant to global transition finance and country-level decarbonization planning. It offers evidence that digital infrastructure investment has stage-dependent and spatially spillover effects, informing how multinationals assess Scope 3 and transition risk in Chinese operations under frameworks like ISSB and TCFD.
👥 読者別の含意
🔬研究者:中国のインフラ・排出ネクサスにおける非線形性と空間スピルオーバーの実証手法（GMM、SDM、PSO-SVM）を参考にできる。
🏢実務担当者:中国に拠点を持つ企業は、地域別のインフラ成熟度と排出ピーク時期の違いをScope 3・移行計画に反映すべき。
🏛政策担当者:新型インフラ政策は地域差を考慮し、中西部ではグリーン技術革新との組み合わせを優先する設計が有効。
📄 Abstract（原文）
New-type infrastructure (NI) may increase carbon emissions through scale expansion while reducing them through technological progress, but systematic empirical testing of these competing effects remains limited. Using panel data for 30 Chinese provinces from 2013 to 2024, this study examines the nonlinear effects of NI on carbon emissions within a two-way fixed-effects framework, and employs the system generalized method of moments (GMM) and instrumental variable approaches to address potential endogeneity arising from dynamic panel bias, omitted variables, and other sources. We then examine industrial structure rationalization and green technological innovation as mediating variables, estimate spatial dependence with a spatial Durbin model, and combine particle swarm optimization–support vector machine (PSO-SVM) forecasting with alternative scenario assumptions. The evidence supports an inverted U-shaped association between NI and carbon emissions. Both mediating variables are significant, but the nonlinear relationship is found only in the central and western regions; it is not significant in the eastern or northeastern regions. NI also has significant cross-regional spatial spillover effects. Across the four scenarios, emissions ultimately decline, the green-transition scenario reaches the earliest and lowest peak, and rapid NI development produces greater pressure in the near term. These results characterize NI as a stage-dependent and spatially connected driver of emissions and support differentiated regional implementation of the Digital China and Beautiful China strategies.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/systems14091169first seen 2026-09-23 05:04:56
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