Stock market development, bank credit, and renewable energy as drivers of carbon intensity using a wavelet quantile approach
ウェーブレット分位点アプローチを用いた株式市場の発展、銀行信用、再生可能エネルギーが炭素強度に与える影響の分析 (AI 翻訳)
Tien Hoang Nguyen, Thi Ngoc Lan Pham, Vu Bao Tran, Thanh Phuc Nguyen
🤖 gxceed AI 要約
日本語
本研究は、ベトナムにおける株式市場の拡大、銀行信用、貿易開放度、再生可能エネルギーが炭素強度に与える影響を、時間依存性・非線形性・分布の不均一性を考慮して分析した。ウェーブレット分位回帰(WQR)とウェーブレット分位相関(WQC)を用いた手法が新規性であり、短・中期サイクルでは株式市場と銀行信用が炭素強度を上昇させる一方、再生可能エネルギーはほぼ全ての時間スケールで炭素強度を低減することを示した。
English
This study examines the time-dependent, nonlinear, and distributional heterogeneity of stock market expansion, bank credit, trade openness, and renewable energy on carbon intensity in Vietnam using wavelet quantile regression and correlation. Results show that stock market and bank credit increase carbon intensity in short- and medium-term cycles, while renewable energy consistently reduces carbon intensity across almost all quantiles and time scales, offering strong evidence for green finance and renewable energy policies.
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
本論文はベトナムを対象としているが、日本においても金融市場の発展と再生可能エネルギーの普及が炭素強度に与える影響を考察する上で示唆に富む。特に、短期的な金融拡大が排出増加につながる可能性は、日本のグリーンファイナンス政策の設計において参考となる。
In the global GX context
This paper contributes to the global literature on the financial determinants of carbon intensity in emerging economies. Its wavelet-based methodology allows for time-frequency decomposition, revealing that financial development can have adverse short-term emission effects, whereas renewable energy is consistently beneficial. These findings inform the design of green finance policies and energy transition strategies in similar contexts.
👥 読者別の含意
🔬研究者:The wavelet quantile approach offers a methodological innovation for studying nonlinear and time-varying relationships in energy and environmental economics.
🏛政策担当者:Highlights the need for green-oriented financial regulations and renewable energy investments to achieve low-carbon growth in emerging economies.
📄 Abstract(原文)
This study examines the time-dependent, nonlinear, and distributional heterogeneity of stock market expansion, bank credit, trade openness, and renewable energy in their influence on carbon intensity in Vietnam, an emerging economy with developing financial markets and an ongoing energy transition. To improve temporal detail, the study modified the data to quarterly intervals using a quadratic match-sum and used a wavelet–quantile technique based on Wavelet Quantile Regression (WQR) and Wavelet Quantile Correlation (WQC) to examine heterogeneity across quantiles and time scales. Decomposing influence over time is a novel methodological contribution to the field, in contrast to traditional analyses that aggregate findings across a single scale or employ mean-level techniques. The results show that the stock market and bank credit are two consistently positive and unexpected determinants of carbon intensity. As the stock market expands and bank credit increases, carbon intensity rises in short- and medium-term cycles, with stronger effects at higher quantiles. As expected, economic expansion raises carbon intensity, with long-term effects. At upper quantiles and over medium- to long-term cycles, economic growth consistently raises carbon intensity, indicating that growth-driven industrialization amplifies emissions, particularly during high-emission regimes. Renewable energy consistently reduces carbon intensity across almost all quantiles (and time–frequency bands), with a substantial quantitative impact on decarbonization, and it also has a long-term effect by facilitating technological upgrading and greener production. These findings show that Vietnam needs green-oriented funding, energy capacity and production, and pro-green trade policies to achieve low-carbon growth.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1007/s43621-026-03677-wfirst seen 2026-06-17 05:44:36 · last seen 2026-06-17 07:14:03
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