Do ESG Ratings Predict Credit Risk? Evidence From Croatian Firms and A Machine Learning Perspective
ESG格付けは信用リスクを予測するか？クロアチア企業の証拠と機械学習の視点 (AI 翻訳)
Vlatka Bilas, Tomislav Radoš, Lana Frkovic
🤖 gxceed AI 要約
日本語
本研究は、新興EU加盟国であるクロアチアの企業データを用いて、ESG格付けが信用リスク評価に有用な情報を提供するかを検証した。2024-2025年のデータを分析し、記述統計、計量経済モデル、ランダムフォレストによる予測を行った結果、ESGスコアと信用格付けの間の関係は弱く不安定であり、ESG変数の予測価値は限定的であることが示された。ESG格付けは企業規模やセクター、報告能力を反映する傾向がある。
English
This study examines whether ESG ratings provide useful information for credit risk assessment in an emerging EU member state, using Croatian firm data from 2024-2025. Combining econometric models and random forest prediction, the findings show a weak and unstable relationship between ESG scores and credit ratings, with limited predictive value. ESG ratings appear to reflect firm size, sector, and reporting capacity rather than a strong standalone signal of credit risk.
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
日本ではSSBJ開示が始まり、ESG情報の信用リスク評価への活用が注目される。本研究成果は、新興市場でのESG評価の限界を示唆し、日本の中小企業や新興市場への適用可能性を考える上で示唆に富む。
In the global GX context
This paper contributes to the global debate on the usefulness of ESG ratings for credit risk, particularly in less mature markets. It highlights the need for caution in relying on ESG scores as standalone credit risk indicators, relevant for investors and regulators under frameworks like CSRD and ISSB.
👥 読者別の含意
🔬研究者:Provides empirical evidence on ESG-credit risk link in an emerging market, with methodological insights for ML applications.
🏢実務担当者:Highlights the limitations of ESG ratings in credit assessment, informing due diligence and risk management.
🏛政策担当者:Suggests that ESG reporting quality and standardization need improvement to enhance predictive power.
📄 Abstract（原文）
This study investigates whether ESG ratings provide useful information for credit risk assessment in an emerging EU member-state context, where sustainability reporting is rapidly expanding but still institutionally developing. The motivation for the study arises from the increasing regulatory and financial relevance of ESG disclosure in the European Union and from the practical need to understand whether ESG indicators can support creditworthiness evaluation. Although prior research often links stronger ESG performance with lower credit risk, less is known about whether this relationship is observable in smaller and less mature markets, particularly during the early phase of adjustment to EU sustainability reporting requirements. To address this gap, the paper analyses firm-level data from the Croatian Chamber of Economy for 2024–2025. ESG is examined both as an aggregate score and through its Environmental, Social, and Governance components, while credit risk is measured using HGK creditworthiness indicators. The methodology combines descriptive and stratified analysis, pooled and within-firm econometric models, ordered-response and transition analyses, and random forest prediction to assess out-of-sample performance. The findings indicate a weak and unstable relationship between ESG measures and HGK credit ratings. Changes in ESG scores do not systematically translate into changes in credit ratings, and ESG variables add only modest predictive value. Overall, ESG ratings in this context appear to reflect firm size, sector, and reporting capacity more than a strong standalone signal of credit risk.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.5171/2026.4713926first seen 2026-08-15 05:24:38 · last seen 2026-08-16 05:33:38
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