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Estimating the effects of ESG scores on corporate credit ratings using multivariate ordinal logit regression

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  • Luca Zanin

    (Prometeia)

Abstract

We estimated the effects of Environmental, Social, and Governance (ESG) scores on the credit ratings of firms in the sectors of manufacturing, mining and quarrying, wholesale and retail trade, information and communication, and real estate activities and located in North America, Europe, and Asia using a multivariate ordinal logit model. We use credit ratings by the S&P and Fitch agencies and the Refinitiv ESG pillar scores as measures of the performance of firms on sustainability matters. We found that the Environmental pillar score is the dimension of sustainability that most contributes to improving the goodness-of-fit of the credit rating model. It has a significant positive effect on credit ratings in all sectors investigated, with stronger effects for mining and quarrying firms. Firms that manage environmental matters better than their industry peers are perceived as more resilient to long-term risks and these tend to be rewarded by credit rating agencies. Some mixed evidence between credit rating agencies is found for the social and governance dimensions in terms of statistical significance and estimated marginal effects by sector.

Suggested Citation

  • Luca Zanin, 2022. "Estimating the effects of ESG scores on corporate credit ratings using multivariate ordinal logit regression," Empirical Economics, Springer, vol. 62(6), pages 3087-3118, June.
    • Handle: RePEc:spr:empeco:v:62:y:2022:i:6:d:10.1007_s00181-021-02121-4
    DOI: 10.1007/s00181-021-02121-4
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    References listed on IDEAS

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    Cited by:

    1. Li, Hao & Guo, Hui & Hao, Xinyao & Zhang, Xuan, 2023. "The ESG rating, spillover of ESG ratings, and stock return: Evidence from Chinese listed firms," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    2. Zanin, Luca, 2023. "A flexible estimation of sectoral portfolio exposure to climate transition risks in the European stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    3. Daniel Ramos-García & Carmen López-Martín & Raquel Arguedas-Sanz, 2023. "Climate transition risk in determining credit risk: evidence from firms listed on the STOXX Europe 600 index," Empirical Economics, Springer, vol. 65(5), pages 2091-2114, November.

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    More about this item

    Keywords

    Corporate credit rating; Environmental; Social; and Governance (ESG) scores; Multivariate ordinal logit regression;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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