Ripple Effects of Climate Policy Uncertainty: Spatial Structural Evolution and Heterogeneous Spillovers of Low-Carbon Energy Transition in China
気候政策の不確実性の波及効果：中国における低炭素エネルギー転換の空間構造的進化と不均一な波及効果 (AI 翻訳)
Yuanyuan Hao
🤖 gxceed AI 要約
日本語
本論文は、中国31省のパネルデータを用いて、気候政策の不確実性（CPU）が低炭素エネルギー転換（LET）に与える影響を空間計量経済学的手法で分析した。CPUはLETを促進し、有意な空間的波及効果を持つこと、政府の環境規制と公衆の環境意識がその効果を増幅することを示した。地域間の格差は収束傾向にあるが、一部で二極化も見られる。
English
This paper uses panel data from 31 Chinese provinces (2000-2024) with spatial econometric methods to examine how climate policy uncertainty (CPU) affects low-carbon energy transition (LET). Findings show CPU significantly accelerates LET with spatial spillover effects, and both government environmental regulation and public awareness amplify this effect. Regional disparities are converging but some polarization exists.
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
中国の地域別分析は、日本のような国でも地域ごとの気候政策の不確実性がエネルギー転換に与える影響を考える上で示唆に富む。政府規制と国民意識の増幅効果は、日本の政策立案にも参考となる。
In the global GX context
This study provides valuable insights into the spatial dynamics of energy transition under policy uncertainty, relevant for countries with regional disparities (e.g., EU, US). The role of government regulation vs. public awareness offers lessons for policy design globally.
👥 読者別の含意
🔬研究者:Spatial econometric approach to energy transition under policy uncertainty, with evidence on spillover effects and amplification mechanisms.
🏢実務担当者:Understanding how regional policy uncertainty and regulation interact can inform corporate energy strategy and site selection.
🏛政策担当者:Region-specific climate incentives are crucial; government regulation has a stronger amplifying effect than public awareness alone.
📄 Abstract（原文）
In the pursuit of global climate change mitigation and carbon neutrality objectives, climate policy uncertainty (CPU) has emerged as a significant constraining factor. Against this backdrop, gaining a deep understanding of how different regions respond to climate risks and achieve low-carbon energy transition (LET) becomes particularly crucial. Drawing on panel data from China's 31 provinces spanning 2000–2024, this study employs kernel density estimation and spatial econometric methods to examine the spatiotemporal evolution of CPU and LET, as well as the underlying mechanisms of influencing factors. Research findings indicate that: (1) CPU and LET exhibit an overall upward trend, with regional disparities showing signs of convergence. However, coordination levels in certain regions are becoming increasingly polarized. (2) Spatially, the evolution pattern shows Western regions > Eastern regions > Central regions, with spatial agglomeration primarily characterized by H-H-type and L-L-type agglomerations. (3) CPU can significantly accelerate the LET and possesses pronounced spatial spillover effects. (4) Both government environmental regulation and public environmental awareness amplify the role of CPU in promoting LET development, with government environmental regulation having a greater amplifying effect than public environmental awareness. Therefore, the findings of this study provide important theoretical foundations and practical guidance for local governments to develop climate incentive policies tailored to their specific conditions, advance regional energy strategy transformations, and contribute to achieving the dual carbon goals.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.17632/j7rhfrvrvffirst seen 2026-07-10 05:15:40 · last seen 2026-07-10 05:28:55
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