Final work : Do ESG factors predict credit rating downgrades ? Evidence from S&P-rated European public companies
Zhou, Yuemin
Promotor(s) :
Blanchard, Gildas
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
|
| Date of defense : | 15-Jun-2026/27-Jun-2026 |
| Advisor(s) : | Blanchard, Gildas
|
| Committee's member(s) : | Suetens, David
|
| 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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