グリーンファイナンス、経済発展段階、低炭素移行：中国地級市データを用いた動学パネル・閾値回帰による実証

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:グリーンファイナンスと脱炭素の非線形・動学的関係を中国都市データで検証した手法と閾値推定の感度分析が参考になる。

🏢実務担当者:地域・発展段階に応じたグリーンファイナンス調達の効果が異なる点を踏まえ、投資判断や開示戦略に活用できる。

🏛政策担当者:発展段階別の閾値を踏まえ、段階的・差別化されたグリーンファイナンス政策設計の根拠として参照できる。

Green finance is widely regarded as a key policy instrument for China’s carbon neutrality goals, yet identifying its effect on low-carbon transition requires addressing green finance’s high correlation with regional development, and its nonlinear features remain insufficiently tested at a fine geographic scale. Using a balanced panel of 325 Chinese prefecture-level cities (2010–2022), this paper applies a fixed-effects model, Difference GMM, and System GMM, validated via an expanded Monte Carlo simulation, and Hansen threshold regression using the level of economic development as the threshold variable. Green finance is significantly and positively associated with low-carbon transition (2.175 under fixed effects, 3.294 under Difference GMM, both p < 0.01), with significant dynamic persistence; its direct effect is concentrated in the deployment period but propagates forward through this persistence. Two threshold values are identified (CNY 78.40 billion and CNY 160.44 billion), with effect strength rising from 0.558 to 2.180 as development advances, though the lower threshold is sensitive to the trimming proportion used, and System GMM’s insignificant coefficient reflects genuine, unresolved estimation uncertainty. These findings indicate that the green finance–low-carbon transition association is a structural process shaped by development stage, offering an evidence-based, though not precisely fixed, quantitative basis for staged, differentiated policy design.

• openalex https://doi.org/10.3390/su18199928first seen 2026-09-30 04:54:06