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ESG-Ratings: Nonparametric Methods of Construction

https://doi.org/10.22394/1726-1139-2024-2-92-107

EDN: FARZRW

Abstract

Many of the largest Russian companies are evaluated by international financial institutions or rating agencies in terms of their influence on ESG factors that take into account environmental issues, interaction with society and corporate governance. Such ratings can have various names, most often referred to as ESG ratings. The inherent subjectivity of the assessments, along with the lack of generally recognized standards and transparency of the methodology, cause concern both from the assessed companies and from investors and regulators. ESG ratings of Russian rating agencies are at an early stage of their development, which is reflected in a small number of evaluated companies. The purpose of the study is to study the main methodological problems in the compilation of ESG ratings identified by the academic and business community with a focus on studying the issue of choosing weights when constructing a summary indicator. The information base of the study is the data published by the rating agency RAEX, which is positioned as the largest agency in the field of non-credit ratings. A comparative analysis of the rating agency’s weight selection methods with nonparametric methods, such as methods of shell analysis, determination of preferences based on similarity with the ideal solution and calculation of the geometric mean is carried out. Based on the results of the study of the initial data of the rating agency, it can be concluded that most companies have low ratings for the environmental component and high ratings for the corporate governance component, while none of the companies has a benchmark rating. The main methodological problem in the selection of weights is the subjective nature of the weights used by the rating agency. Correlation analysis of the studied non-parametric methods showed a high correlation with each other and with the initial ratings of the rating agency, however, at the level of some individual companies, the ratings may differ depending on the chosen method.

About the Authors

A. V. Yurkov
Saint Petersburg State University of Industrial Technologies and Design
Russian Federation

Alexander V. Yurkov, Professor of Mathematics Department, Doctor of Physical and Mathematical Sciences 

Saint Petersburg



Zh. R. Babaeva
Saint Petersburg State University
Russian Federation

Zhuldyz R. Babaeva, PhD Student at the Faculty of Economics

Saint Petersburg

   


References

1. Babenko M. V., Bik S. I., Postnova A. I. Green economy. Definitions and concepts. Moscow : World Wildlife Fund (WWF), 2018. [Electronic resource]. URL: https://www.b-soc.ru/wp-content/uploads/2021/02/zelenaya-ekonomika-glossarij.pdf (accessed: 14.02.2024). (In Russ.).

2. Bobylev S. N. Economics of sustainable development. Moscow : KnoRus Publishing House, 2021. (In Russ.).

3. Verenikin A. O., Makhankova N. A., Verenikina A.Yu. Measuring the sustainability of the development of large Russian companies // Russian Management Journal [Rossiiskii zhurnal menedzhmenta]. 2021. Vol. 19 (3). P. 237–287. (In Russ.) https://doi.org/10.21638/spbu18.2021.301.

4. Gilyarovskaya L. T. Economic analysis. 2nd ed. Moscow : UNITY DANA, 2004. (In Russ.)

5. Grishankova S. D. ESG ratings. ESG transformation as a vector of sustainable development. In 3 vols. General ed. by K. E. Turbina and I. Y. Yurgens. Vol. 2. Moscow : Aspect Press, 2022. (In Russ.).

6. Danilov Yu. A., Pivovarov D. A., Davydov I. S. Rating assessments of sustainable finance // Economic development of Russia [Ekonomicheskoe razvitie Rossii]. 2021. N 28 (4). P. 25–33. (In Russ.)

7. Korshunov O.Yu., Lvova N. A., Rakhimov Z.Yu. Adaptation of the utility function to assess the impact of responsible investment on financial markets // Finance and Business [Finansy i biznes]. 2021. Vol. 17. N 3. P. 70–86. (In Russ.)

8. Morgunov E. P., Morgunova O. N. Promotion of the method for evaluating the effectiveness of Data Envelopment Analysis systems in Russia. XX International. Scientific-Practical Conf. System analysis in design and management. Proceedings in 2 parts. Peter the Great Saint Petersburg Polytechnic University, 2016. (In Russ.)

9. Nefedov A. S., Shakirov V. A. Multicriteria evaluation of alternatives based on the TOPSIS method under conditions of uncertainty of the preferences of the decision-maker // Information technology. Problems and solutions [Informatsionnye tekhnologii. Problemy i resheniya]. 2019. Vol. 3 (8). P. 25–32. (In Russ.)

10. Ovechkin D. V. Responsible investments: divergence of ESG ratings // Modern Economy Success. 2021. N 1. P. 170–174. (In Russ.) EDN: ZTJJDO.

11. Stolbov M. I., Shchepeleva M. A. The impact of ESG factors on financial stability // Prob lems of Economics [Voprosy ekonomiki]. 2022. N 11. P. 136–148. (In Russ.) https://doi.org/10.32609/0042-8736-2022-11-1-13.

12. Soboleva O. V., Steshenko A. S. ESG factors as a new mechanism for enhancing responsible investment and achieving sustainable development goals. Sustainable Development: Challenges and Opportunities: A Collection of Scientific Articles. Ed. by Viktorova E. V. Saint Petersburg : SPbGOUE, 2020. (In Russ.).

13. Khalitskaya K. Selection of technologies using the TOPSIS method // Forsyth [Forsait]. 2020. Vol. 14. N 1. P. 85–96. (In Russ.).

14. Khachatryan A. V. Divergence in ESG ratings: foreign regulatory trends // Financial Journal [Finansovyi zhurnal]. 2022. Vol. 14. N 5. P. 89–104.. https://doi.org/10.31107/2075-1990-20225-89-104 (In Russ.).

15. Aiba Y., Ito T., Ibe Y. Network structure in ESG ratings suggests new corporate strategies: Evolving AI technology to quantify qualitative data // Securities Analysts Journal. 2020.

16. D’Amato V., D’Ecclesia R., Levantesi S. Fundamental ratios as predictors of ESG scores: A machine learning approach // Decisions in Economics and Finance. 2021. Vol. 44. P. 1087–1110. https://doi.org/10.1007/s10203-021-00364-5.

17. Arthur H., Urban M. A., Wójcik D. Alternative ESG ratings: How technological innovation is reshaping sustainable investment // Sustainability. 2021. Vol. 13 (6). https://doi.org/10.3390/su13063551.

18. Berg F., Koelbel J. F., Rigobon R. Aggregate confusion: The divergence of ESG ratings. // Review of Finance. 2022. Nov. Vol. 26 (6). P. 1315–44. https://doi.org/10.1093/rof/rfac033.

19. Charlin V., Cifuentes A., Alfaro J. ESG ratings: an industry in need of a major overhaul // Journal of Sustainable Finance & Investment. 2022. P. 1–19. https://doi.org/10.1080/20430795.2022.2113358.

20. Chen L., Lipei Z., Jun H., Helu X., Zhongbao Z. Social responsibility portfolio optimization incorporating ESG criteria. // Journal of Management Science and Engineering. Vol. 1. P. 75–85. https://doi.org/10.1016/j.jmse.2021.02.005.

21. Christensen D. M., Serafeim G., Sikochi A. Why is Corporate Virtue in the Eye of The Beholder? The Case of ESG Ratings // The Accounting Review. 2022. Vol. 97 (1). P. 147–175. https://doi.org/10.2308/TAR-2019-0506.

22. Gillan S. L., Koch A., Starks L. T. Firms and social responsibility: A review of ESG and CSR research in corporate finance // Journal of Corporate Finance. 2021. Vol. 66. P. 101889. https://doi.org/10.1016/j.jcorpfin.2021.101889.

23. Li F., Polychronopoulos A. What a difference an ESG ratings provider makes // Research affiliates. 2020. Vol. 24 [Electronic resource]. URL: https://www.researchaffiliates.com/content/dam/ra/publications/pdf/770-what-a-difference-an-esg-ratings-provider-makes.pdf (accessed: 20.12.2023).

24. Liern V., Pérez-Gladish B. Ranking corporate sustainability: A flexible multidimensional approach based on linguistic variables. // International Transactions in Operational Research. 2018. Vol. 25 (3). P. 1081–1100. https://doi.org/10.1111/itor.12469.

25. MacNeil I., Esser I. From a financial to an entity model of ESG // European Business Organization Law Review. 2022. Vol. 23 (1). P. 9–45. https://doi.org/10.1007/s40804-021.

26. Stevens S. S. On the Theory of Scales of Measurement // Science. 1946. Vol. 103 (2684). P. 677–680. DOI: 10.1126/science.103.2684.677.


Review

For citations:


Yurkov A.V., Babaeva Zh.R. ESG-Ratings: Nonparametric Methods of Construction. Administrative Consulting. 2024;(2):92-107. (In Russ.) https://doi.org/10.22394/1726-1139-2024-2-92-107. EDN: FARZRW

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ISSN 1726-1139 (Print)
ISSN 1816-8590 (Online)