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Does ESG performance improve firm creditworthiness?

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  • Kanno, Masayasu

Abstract

This study examines whether ESG performance improves a firm’s creditworthiness. To this end, we develop two methodologies for logistic regression with or without two-stage least squares for selecting default risk factors pertaining to Japanese firms given their ESG scores. The results show that ESG performance contributes more to the prediction of a firm’s default risk for longer risk horizons. Notably, ESG-related activities do not necessarily contribute to a firm’s default risk reduction. Overall, this study provides effective credit risk analysis methodologies for related entities, such as ESG management firms, lenders, and investors.

Suggested Citation

  • Kanno, Masayasu, 2023. "Does ESG performance improve firm creditworthiness?," Finance Research Letters, Elsevier, vol. 55(PA).
    • Handle: RePEc:eee:finlet:v:55:y:2023:i:pa:s1544612323002660
    DOI: 10.1016/j.frl.2023.103894
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    Cited by:

    1. Arianna Agosto & Paolo Giudici & Alessandra Tanda, 2023. "How to combine ESG scores? A proposal based on credit rating prediction," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 30(6), pages 3222-3230, November.
    2. Palmieri, Egidio & Ferilli, Greta B. & Stefanelli, Valeria & Geretto, Enrico F. & Polato, Maurizio, 2023. "Assessing the influence of ESG score, industry, and stock index on firm default risk: A sustainable bank lending perspective," Finance Research Letters, Elsevier, vol. 57(C).

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    More about this item

    Keywords

    Environmental; Social; and Governance (ESG); Default risk; Logistic regression with two-stage least squares (2SLS);
    All these keywords.

    JEL classification:

    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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