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How to combine ESG scores? A proposal based on credit rating prediction

Articolo
Data di Pubblicazione:
2023
Abstract:
The diffusion of Environmental, Social and Governance (ESG) metrics is increasingly affecting corporates behaviour and their ability to attract investors. Corporate ESG practices are nowadays considered as a key element in evaluating creditworthiness and the cost of capital, to direct funds to the best-performing companies that limit the harmful impact on the planet and the societies. Due to this increased interest in ESG by companies, investors and policymakers, a high number of ESG scores and metrics have been developed, each with different methodologies and scopes. Because of this variety, it could be therefore challenging for investors to understand and compare ESG measures. In this paper, we address this issue by proposing a method to combine the information provided by different ESG scores into a single aggregate measure of company sustainability and link this combined score to the credit rating of companies. The proposed methodology can help investors to improve their investment decisions by combining more diverse information on company sustainability as a driver of companies' credit rating, thereby reducing information asymmetries.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
Bayesian models; credit rating; ESG rating; sustainable finance
Elenco autori:
Agosto, Arianna; Giudici, Paolo; Tanda, Alessandra
Autori di Ateneo:
AGOSTO ARIANNA
GIUDICI PAOLO STEFANO
TANDA ALESSANDRA
Link alla scheda completa:
https://iris.unipv.it/handle/11571/1480616
Link al Full Text:
https://iris.unipv.it//retrieve/handle/11571/1480616/559412/ESG___Bayesian_merge.pdf
Pubblicato in:
CORPORATE SOCIAL-RESPONSIBILITY AND ENVIRONMENTAL MANAGEMENT
Journal
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Dati Generali

URL

https://onlinelibrary.wiley.com/doi/10.1002/csr.2548
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