Green Finance and Environmental Sustainability: An Empirical Evaluation of Financial Instruments in the Azerbaijani Economy
グリーンファイナンスと環境持続可能性：アゼルバイジャン経済における金融手段の実証評価 (AI 翻訳)
Vugar Mehdiyev, A. Musayev, Tamar Orjonikidze
🤖 gxceed AI 要約
日本語
本研究は2010～2023年のアゼルバイジャンを対象に、グリーンボンド、ESG融資、再生可能エネルギー金融がCO2排出に与える影響をARDLモデルで実証分析。グリーンファイナンス指数1%上昇で排出0.314%減少、ESG融資で0.202%減少、再生可能エネルギー比率で0.482%減少。誤差修正項は年58%の調整速度を示す。
English
This study uses an ARDL bounds testing approach to empirically investigate the impact of green bonds, ESG lending, and renewable energy finance on CO2 emissions in Azerbaijan from 2010 to 2023. A 1% increase in the Green Finance Index reduces emissions by 0.314%, ESG lending by 0.202%, and renewable energy share by 0.482%. The error correction term indicates annual adjustment of 58%.
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
本論文はアゼルバイジャンという資源依存型移行経済の事例を提供する。日本の金融機関が同様の経済構造を持つ新興国でのグリーンファイナンス戦略を検討する際の参考資料となる。
In the global GX context
This paper provides empirical evidence from a fossil-fuel-dependent transition economy, contributing to the global literature on the effectiveness of green finance instruments. It offers insights for policymakers and investors in resource-rich countries navigating the green transition.
👥 読者別の含意
🔬研究者:Empirical validation of green finance impact on emissions using ARDL, with implications for transition economies.
🏢実務担当者:Evidence that green bonds and ESG lending can reduce emissions, useful for financial institutions designing green products.
🏛政策担当者:Policy recommendations including mandatory green bond taxonomies and blended finance for fossil-fuel-dependent economies.
📄 Abstract（原文）
This study empirically investigates the relationship between green finance instruments and environmental sustainability in Azerbaijan over the period 2010–2023. Using an Autoregressive Distributed Lag (ARDL) bounds testing approach, the study examines how green bonds, ESG-oriented lending, renewable energy finance, and the composite Green Finance Index (GFI) affect CO₂ emissions in a transition economy heavily dependent on fossil fuel revenues. The empirical findings confirm long-run cointegration among the variables and validate the Environmental Kuznets Curve (EKC) hypothesis for Azerbaijan. Long-run coefficients indicate that a one percent increase in the Green Finance Index reduces CO₂ emissions by 0.314% (p < 0.01), while ESG lending reduces emissions by 0.202% (p < 0.05). Renewable energy share exhibits the strongest negative effect (−0.482, p < 0.01). The Error Correction Term (ECT = −0.581) implies that approximately 58% of short-run disequilibria are corrected annually. Diagnostic tests confirm model stability, absence of serial correlation, and homoscedastic residuals. The study contributes original empirical evidence from a resource-rich transition economy, offering actionable policy recommendations including mandatory green bond taxonomies, blended finance frameworks, and carbon-linked financial instruments. These findings have significant implications for policymakers in Azerbaijan and comparable resource-dependent economies navigating the green transition.Copyright© 2026 The Author(s). This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited.Article’s History: Received 15th of March, 2026; Revised 24th of April, 2026; Accepted 29th of May, 2026; Available online: 30th of June, 2026. Published as research article in the Volume XXI, Summer, Issue 3(93), 2026.
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