The Marginal Effects of Corporate Governance on Bank Financial Performance and Their Conditional Variations
企業統治が銀行の財務業績に与える限界的効果とその条件付き変動 (AI 翻訳)
Yanlin Zheng
🤖 gxceed AI 要約
日本語
本研究は、ESGのガバナンス（G）スコアと銀行の総資産利益率（ROA）との関係を分析。中国の上場銀行データを用い、パネル回帰とランダムフォレストにより、GスコアとROAの正の関連、不良債権比率との負の関連を発見。ガバナンス投資の限界効果は銀行タイプにより異なり、国有銀行で効果が大きい。
English
This study examines the marginal effect of corporate governance (G score) on bank financial performance using panel regression and random forest on Chinese listed banks (2009-2024). It finds a positive association with ROA and negative with NPL ratio. The effect varies by bank type, with stronger responses in state-owned banks.
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
本論文は中国銀行を対象とするが、日本でもESGガバナンススコア向上が財務指標に与える影響を定量評価する手法として参考になる。SSBJ対応や統合報告書におけるガバナンス開示の経済的効果を検討する際の示唆となる。
In the global GX context
While focused on Chinese banks, this paper provides a quantitative framework for evaluating the financial returns of governance investments, relevant to global ESG integration and the growing emphasis on governance in TCFD/ISSB frameworks.
👥 読者別の含意
🔬研究者:Demonstrates a method to quantify marginal benefits of governance investment, using both econometric and ML approaches.
🏢実務担当者:Banks can use governance score improvements as a lever for financial performance, with heterogeneous effects by ownership type.
🏛政策担当者:Suggests the need for dynamic monitoring of governance effectiveness to optimize resource allocation.
📄 Abstract（原文）
With the growing salience of Environmental, Social, and Corporate Governance (ESG), how banks can bolster financial performance through improved corporate governance has become a critical research agenda. This study investigates the marginal effect of corporate governance on banks' financial outcomes by centering on the nexus between ESG's governance (G) score and the return on total assets (ROA). It further explores the transmission mechanism through which governance investments shape bank performance and how these effects differ across bank types. Employing descriptive analysis, a panel regression model (two-way fixed effects), and a machine learning approach (random forest regression with five-fold cross-validation), the study analyzes data from multiple listed Chinese banks from 2009 to 2024. The findings reveal a significantly positive association between the G score and ROA, and a significantly negative association between the G score and the non-performing loan (NPL) ratio. An additional 10,000 yuan of governance investment per 10,000 yuan of assets leads to a 0.0002-percentage-point increase in ROA, with significant cross-institutional heterogeneity. State-owned banks exhibit stronger performance responses to governance improvements. The results underscore the imperative of constructing a system for evaluating the marginal benefits of governance investment and to monitoring its effectiveness dynamically in order to achieve more efficient resource allocation.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://aemps.ewapub.com/article/view/31581.pdffirst seen 2026-07-18 08:19:24
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。