Winner takes all? Understanding the impact of energy transition on employment under the constraint of China’s carbon peak target
勝者総取り？中国の炭素ピーク目標制約下でのエネルギー転換が雇用に与える影響の理解 (AI 翻訳)
Jianhui Cong, Rui Li, Weiqiang Zhang
🤖 gxceed AI 要約
日本語
本論文は、炭素ピーク制約下でのエネルギー転換が中国の雇用再配分に与える影響を、産業連関モデルと多目的最適化を用いて分析。結果、雇用は全体で増加するものの、沿岸部と高付加価値部門に集中し、内陸部や資源依存地域で大きな損失が生じる「勝者総取り」パターンが明らかになった。特に炭素依存の山西省では約10%の雇用喪失が予測される。
English
This study uses an MRIO and multi-objective optimization model to simulate how China's carbon peak constrained energy transition reshapes formal labor demand. Results show aggregate employment gains but a 'winner takes all' pattern: coastal regions and high-value service/power sectors capture benefits while inland resource-dependent regions face severe losses, with coal-dependent Shanxi potentially losing nearly 10% of formal employment.
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
中国の事例だが、日本のGX政策でも地域間不均衡や雇用移行は重要な課題。SSBJや有報での社会関連開示にも示唆を与える。
In the global GX context
Provides empirical evidence on spatial employment risks of the energy transition, relevant for global Just Transition frameworks and ISSB/TCFD-related social disclosures.
👥 読者別の含意
🔬研究者:Offers a multi-regional model linking energy transition to employment reallocation, useful for just transition and carbon management research.
🏢実務担当者:Highlights sectoral and regional employment shifts that can inform corporate transition planning and stakeholder engagement in China.
🏛政策担当者:Demonstrates that carbon peak pathways must consider spatial and sectoral employment risks to avoid social disruption.
📄 Abstract（原文）
Achieving carbon peak and carbon neutrality requires not only reducing emissions but also managing the macroeconomic side effects of the energy transition. This study examines employment reallocation as a carbon transition management problem rather than as a conventional labor market performance issue. We develop an integrated multi-regional input-output (MRIO) and multi-objective optimization model to simulate how China's carbon peak constrained energy transition reshapes formal labor demand across 42 sectors and 31 provinces. The novelty of this study lies in linking a theoretical mechanism of capital biased energy transition with a detailed interregional production network, thereby identifying where the social costs of decarbonization are likely to concentrate. Our results show that although the transition increases aggregate employment, it generates a clear "winner takes all" pattern. Employment gains are captured mainly by economically developed coastal regions and high value added service and power related sectors, while less developed inland and resource dependent regions face severe losses. Shanxi, a typical coal dependent province, could lose nearly 10% of formal employment opportunities, and job growth in renewables is insufficient to fully offset losses in traditional fossil fuel and power industries. These findings provide policy relevant evidence for carbon management by showing that carbon peak pathways must be evaluated not only by emission outcomes but also by their spatial and sectoral employment risks.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1186/s13021-026-00475-9first seen 2026-06-25 04:54:58
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