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Final work : Do ESG factors predict credit rating downgrades ? Evidence from S&P-rated European public companies

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Zhou, Yuemin ULiège
Promotor(s) : Blanchard, Gildas ULiège
Date of defense : 15-Jun-2026/27-Jun-2026 • Permalink : http://hdl.handle.net/2268.2/25413
Details
Title : Final work : Do ESG factors predict credit rating downgrades ? Evidence from S&P-rated European public companies
Author : Zhou, Yuemin ULiège
Date of defense  : 15-Jun-2026/27-Jun-2026
Advisor(s) : Blanchard, Gildas ULiège
Committee's member(s) : Suetens, David ULiège
Language : English
Number of pages : 75
Keywords : [en] credit risk
[en] IFRS9
[en] SICR
[en] credit rating downgrade
[en] ESG factors
Discipline(s) : Business & economic sciences > Finance
Target public : Researchers
Professionals of domain
Student
Institution(s) : Université de Liège, Liège, Belgique
Degree: Master de spécialisation en gestion des risques financiers
Faculty: Master thesis of the HEC-Ecole de gestion de l'Université de Liège

Abstract

[fr] This study examines the relationship between environmental, social, and governance (ESG) factors and corporate credit rating downgrades, distinguishing between input‑based ESG scores and output‑based ESG metrics. Using a panel of publicly listed corporates in European developed markets rated by S&P Global, the analysis investigates whether ESG‑related variables provide incremental predictive information for downgrade risk beyond traditional financial, macroeconomic, and structural controls. The results show that output‑based indicators including CO₂ emissions, ESG controversies, and country‑level physical climate vulnerability, are consistently associated with higher downgrade likelihood, whereas commonly used input‑based ESG scores are not. Firms with missing CO₂ disclosures exhibit lower observed downgrade risk, consistent with disclosure‑driven selection effects. The study provides robust evidence that realized ESG outcomes contain relevant information for downgrade risk, with implications for credit risk assessment and IFRS 9 SICR frameworks.


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  • Zhou, Yuemin ULiège Université de Liège > Master spéc. gest. risques fin.

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