Can green finance and effective governance accelerate the low-carbon transition? A quantile analysis of OECD countries

Lu Yu et al.

Journal of Innovation & Knowledge2026https://doi.org/10.1016/j.jik.2026.101023article
AJG 1ABDC C
Weight
0.50

What the paper says

Climate change driven by greenhouse gas emissions necessitates comprehensive strategies that combine financial mechanisms and institutional quality to achieve effective carbon reduction in developed economies. This study examines the influence of green finance and government effectiveness on carbon emissions in OECD economies from 1996 to 2022. Using the Method of Moments Quantile Regression (MMQR), the study shows that green finance reduces carbon emissions, with the magnitude of the coefficients increasing from lower to higher quantiles, while government effectiveness exerts even stronger negative effects that also intensify at higher emission levels. Both mechanisms emerge as important independent determinants with heterogeneous effects across the emission distribution, indicating that high-emission countries benefit more substantially from these interventions. Policymakers should therefore prioritize differentiated strategies that combine higher renewable energy R&D expenditure with improvements in institutional quality, particularly in high-emission countries, while also implementing complementary measures to decouple economic growth from environmental degradation. This study provides the first comprehensive quantile-based analysis that simultaneously examines green finance and government effectiveness as independent determinants of consumption-based carbon emissions in OECD countries, distinguishing it from prior research that has examined these factors in isolation or relied on mean-based regression techniques.

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https://doi.org/https://doi.org/10.1016/j.jik.2026.101023

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@article{lu2026,
  title        = {{Can green finance and effective governance accelerate the low-carbon transition? A quantile analysis of OECD countries}},
  author       = {Lu Yu et al.},
  journal      = {Journal of Innovation & Knowledge},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.jik.2026.101023},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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