ESG Factors and Firms' Credit Risk

Laura Bonacorsi, Vittoria Cerasi, Paola Galfrascoli and Matteo Manera ()

No 507, Working Papers from University of Milano-Bicocca, Department of Economics

Abstract: We study the relationship between the risk of default and Environmental, Social and Governance (ESG) factors using Machine Learning (ML) techniques on a cross-section of European listed companies. Our proxy for credit risk is the z-score originally proposed by Altman (1968).We consider an extensive number of ESG raw factors sourced from the rating provider MSCI as potential explanatory variables. In a first stage we show, using different SML methods such as LASSO and Random Forest, that a selection of ESG factors, in addition to the usual accounting ratios, helps explaining a firm’s probability of default. In a second stage, we measure the impact of the selected variables on the risk of default. Our approach provides a novel perspective to understand which environmental, social responsibility and governance characteristics may reinforce the credit score of individual companies.

Keywords: credit risk; z-scores; ESG factors; Machine learning. (search for similar items in EconPapers)
JEL-codes: C5 D4 G3 (search for similar items in EconPapers)
Pages: 48
Date: 2022-12, Revised 2022-12
New Economics Papers: this item is included in nep-big, nep-cfn, nep-cmp, nep-env and nep-fmk
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://repec.dems.unimib.it/repec/pdf/mibwpaper507.pdf (application/pdf)

Related works:
Working Paper: ESG Factors and Firms’ Credit Risk (2022)
Working Paper: ESG Factors and Firms’ Credit Risk (2022)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mib:wpaper:507

Access Statistics for this paper

More papers in Working Papers from University of Milano-Bicocca, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Matteo Pelagatti ().