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Aggregating ESG scores: a Wasserstein distance-based method

Author

Listed:
  • Arianna Agosto

    (University of Pavia)

  • Antonio Balzanella

    (Università degli studi della Campania Luigi Vanvitelli)

  • Paola Cerchiello

    (University of Pavia)

Abstract

The evaluation of the Environmental, Social and Governance (ESG) profile of companies is gaining more and more importance in the credit and financial system and is made more challenging by the availability of alternative- and often divergent- ESG ratings. In addition, the contribution of the three dimensions (E, S and G) to the final evaluation is not disclosed by the raters. This paper proposes an approach for aggregating the three dimensions constituting ESG ratings by means of optimal transport from the perspective of the Wasserstein distance. An empirical exercise, conducted on a dataset related to Small and Medium Enterprises (SMEs), shows that the proposed aggregated indicator represents a statistically sound and explainable tool for the users of ESG ratings, especially when non-homogenous evaluations are provided. Our proposal is also compared to Principal Component Analysis (PCA), a state of the art machine learning algorithm widely employed in the literature concerning the building of synthetic indicators.

Suggested Citation

  • Arianna Agosto & Antonio Balzanella & Paola Cerchiello, 2025. "Aggregating ESG scores: a Wasserstein distance-based method," DEM Working Papers Series 228, University of Pavia, Department of Economics and Management.
    • Handle: RePEc:pav:demwpp:demwp0228
    as

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    File URL: https://economiaemanagement.dip.unipv.it/sites/dip10/files/2025-05/DEMWP0228.pdf
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    References listed on IDEAS

    as
    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. Monica Billio & Michele Costola & Iva Hristova & Carmelo Latino & Loriana Pelizzon, 2021. "Inside the ESG ratings: (Dis)agreement and performance," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 28(5), pages 1426-1445, September.
    3. Cuestaalbertos, J. A. & Ruschendorf, L. & Tuerodiaz, A., 1993. "Optimal Coupling of Multivariate Distributions and Stochastic Processes," Journal of Multivariate Analysis, Elsevier, vol. 46(2), pages 335-361, August.
    4. Gucciardi, Gianluca & Ossola, Elisa & Parisio, Lucia & Pelagatti, Matteo, 2025. "Common factors behind companies’ Environmental ratings," International Review of Financial Analysis, Elsevier, vol. 100(C).
    5. Emma Avetisyan & Michel Ferrary, 2013. "Dynamics of Stakeholders’ Implications in the Institutionalization of the CSR Field in France and in the United States," Journal of Business Ethics, Springer, vol. 115(1), pages 115-133, June.
    6. Florian Berg & Julian F Kölbel & Roberto Rigobon, 2022. "Aggregate Confusion: The Divergence of ESG Ratings [Corporate social responsibility and firm risk: theory and empirical evidence]," Review of Finance, European Finance Association, vol. 26(6), pages 1315-1344.
    7. Steven Scalet & Thomas Kelly, 2010. "CSR Rating Agencies: What is Their Global Impact?," Journal of Business Ethics, Springer, vol. 94(1), pages 69-88, June.
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