The Low-Carbon Policy and Urban Industrial Transformation: Evidence from China’s Low-Carbon City Pilot Using Double Machine Learning
低炭素政策と都市産業変革：二重機械学習を用いた中国の低炭素都市パイロットからの証拠 (AI 翻訳)
Y Li, zhenghuang shi, Wenhui Chen, Y. Wang, Yiwen Ye
🤖 gxceed AI 要約
日本語
本研究は、中国の低炭素都市パイロット（LCCP）政策が都市の産業変革を促進するかを検証。2008～2023年の283都市のパネルデータと二重機械学習（DDML）を用いた結果、LCCP政策は産業の高度化を有意に促進することが示された。メカニズム分析では、政府支援と公衆環境意識の向上が重要な経路である。効果は資源型都市や経済発展の進んだ都市で顕著であり、地域格差を拡大する傾向がある。
English
This study examines whether China's Low-Carbon City Pilot (LCCP) policy enhances urban industrial transformation. Using panel data from 283 Chinese cities (2008-2023) and double machine learning, it finds that LCCP significantly promotes industrial upgrading. Mechanism analysis shows government support and public environmental awareness as key channels. Effects are stronger in resource-based and economically developed cities, widening regional disparities.
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
中国の低炭素都市政策の効果を実証した本論文は、日本における地域別脱炭素政策の設計や、政府支援・市民意識の役割を考える上で示唆に富む。特に、都市の特性に応じた政策効果の差異は、日本の自治体政策立案に参考となる。
In the global GX context
This paper contributes to global climate policy evaluation literature by providing robust causal evidence from China's Low-Carbon City Pilot using double machine learning. Its findings on heterogeneous effects and regional disparities are relevant for policymakers worldwide designing context-specific climate policies.
👥 読者別の含意
🔬研究者:Researchers interested in causal inference methods for policy evaluation and urban industrial transformation under climate policy.
🏢実務担当者:Corporate sustainability teams can gain insights into how low-carbon city policies may affect industrial upgrading, though the context is China.
🏛政策担当者:Policymakers can note the importance of government support and public awareness, and the need to tailor policies to city characteristics.
📄 Abstract（原文）
China’s Against the backdrop of the global low-carbon transition, balancing ecological protection and economic development has become a critical challenge. This study aims to examine whether and how the Low-Carbon City Pilot (LCCP) policy enhances urban industrial transformation momentum. Using panel data from 283 Chinese cities during 2008–2023, we employ a double machine learning (DDML) approach and use industrial robot installation density as a proxy for industrial development momentum. The results show that the LCCP policy significantly promotes industrial transformation and upgrading. Mechanism analysis indicates that the policy strengthens transformation momentum by enhancing government support and increasing public environmental awareness, particularly in cities with lower innovation costs. The effects are more pronounced in resource-based cities, non-old industrial bases, and economically developed cities, while also exacerbating regional disparities as more developed cities benefit more. These findings provide important implications for achieving coordinated development between carbon reduction and industrial transformation.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su18084088first seen 2026-05-17 05:24:14
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