How Do Pilot Policies for Climate—Adaptive City Development Enhance Urban Green Energy Efficiency?
気候適応型都市開発のパイロット政策は都市のグリーンエネルギー効率をどのように向上させるか？ (AI 翻訳)
Chuanchao Li, Yuanhe Du, Shuangyang Zhai
🤖 gxceed AI 要約
日本語
中国284都市の2012-2023年データを用い、気候レジリエント都市政策を自然実験として、二重機械学習と空間ラグモデルで気候リスクガバナンスが都市のグリーンエネルギー効率に与える因果効果を検証。政策はグリーンファイナンス、技術革新、産業高度化を通じて効率を向上させ、地域間の正の波及効果も確認。
English
Using data from 284 Chinese cities (2012-2023) and a quasi-natural experiment of climate-resilient city pilots, this study applies double machine learning and spatial lag models to show that climate risk governance significantly enhances urban green energy efficiency via green finance, green innovation, and industrial upgrading, with positive spatial spillovers to neighboring regions.
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
日本の自治体や企業にとって、気候適応政策がグリーン移行に与える因果効果の実証は、SSBJ対応や地域の脱炭素戦略を検討する上で参考になる。特に、グリーンファイナンスの波及効果は、地域間連携の重要性を示唆する。
In the global GX context
This study provides causal evidence on how climate adaptation policies drive green energy efficiency, relevant to global discussions on aligning adaptation and mitigation under frameworks like TCFD and ISSB. The spatial spillover findings highlight the need for regional coordination in climate transition finance.
👥 読者別の含意
🔬研究者:Provides a rigorous causal framework (double ML + spatial) for evaluating climate policy impacts on energy efficiency, useful for similar studies in other contexts.
🏢実務担当者:Highlights the role of green finance and innovation in enhancing energy efficiency, informing corporate strategy for climate-resilient investments.
🏛政策担当者:Offers evidence that climate-resilient city policies can spur green transitions and recommends strengthening green finance coordination across regions.
📄 Abstract（原文）
Against the backdrop of deepening global climate governance and the ongoing advancement of the dual carbon goals, clarifying whether climate risk management can effectively drive improvements in urban green energy efficiency holds significant importance for synergistically advancing climate adaptation and green transition. This study employs data from 284 prefecture-level and above cities in China spanning 2012–2023, utilising the climate-resilient city pilot policy as a quasi-natural experiment. By integrating dual machine learning models with spatial lag models, it systematically examines the causal effects, transmission mechanisms, and spatial spillover characteristics of climate risk governance on urban green energy efficiency. Findings reveal: ① Climate-resilient city development significantly enhances local green energy efficiency through three pathways: green finance development, green technological innovation, and industrial structure upgrading; ② The impact exhibits pronounced spatio-temporal heterogeneity, characterised by delayed and amplified effects, particularly pronounced in inland, central cities, and non-resource-based cities; ③ The impact exhibits a pronounced positive spatial correlation, not only catalysing local green transitions but also generating positive spatial spillovers to neighbouring regions, indicating potential for regional collaborative development. Additionally, green finance itself possesses positive cross-regional spillover effects. This study provides empirical evidence and policy recommendations for optimising climate adaptation policy design, strengthening green finance coordination, and advancing regionally linked green transitions.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su18157929first seen 2026-08-09 05:15:54
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