Skip to main content

ESG Risk Perception in Sustainable Financial Decisions. Quantitative Methods Perspective

  • Conference paper
  • First Online:

Part of the book series: Springer Proceedings in Business and Economics ((SPBE))

Abstract

The role of ESG risk in both decisions of financial institutions and enterprises is systematically growing. The financial sector is particularly predisposed to the exposure of ESG risk, which is an increasingly important element taken into account in the credit risk management process. Therefore, sustainable financial decisions are those that take into account the ESG risk in the decision-making process. The paper discusses the quantitative methods used in the ESG risk analysis. The critical literature review, induction, and deduction methods were implemented to diagnose the significance of qualitative methods in ESG assessment process. Within the methods enabling the analysis on the financial market, the mathematical, statistical, and econometric methods are of particular use. The results of the study confirmed that usage of quantitative tools in the study of ESG factors is beneficial for the analysis of economic and financial conditions of entities.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    https://pdfs.semanticscholar.org/3597/efbeea7542e0c649cc366fea523678ca06a5.pdf.

  2. 2.

    The Weber median was calculated in R program: l1median of pcaPP package.

  3. 3.

    See, for example, Mendoza and Martins [40], Huang et al. [41], Buchholz et al. [42], Figueira et al. [43], and Nermend [44].

  4. 4.

    A detailed description of these methods can be found, for example, in the works: Figueira et al. [45], Triantaphyllou [46].

References

  1. Changhong, Z., Yu, G., Jiahai, Y., Mengya, W., Daiyu, L., Yiou, Z., Jiangang, K.: ESG and corporate financial performance: empirical evidence from China’s listed power generation companies. Sustainability 10(8), 1–18 (2018)

    Google Scholar 

  2. Finansinspektionen: How Can the Financial Sector Contribute to Sustainable Development. https://www.fi.se/contentassets/123efb8f00f34f4cab1b0b1e17cb0bf4/finansiella_foretags_hallbarhetsarbete_eng.pdf (2016). Accessed 19 Nov 2018

  3. Muñoz-Torres, M.J., Fernández-Izquierdo, M.A., Rivera-Lirio, J.M., Escrig-Olmedo, E.: Can environmental, social, and governance rating agencies favor business models that promote a more sustainable development? Corp. Soc. Responsib. Environ. Manag. (2018). https://doi.org/10.1002/csr.1695

    Article  Google Scholar 

  4. Hachigian, H., McGill, S.M.: Reframing the governance challenge for sustainable investment. J. Sustain. Financ. Invest. 2(3–4), 166–178 (2012)

    Google Scholar 

  5. World Wildlife Fund: Living Planet Report. https://www.worldwildlife.org/pages/living-planet-report-2014 (2014). Accessed 19 Nov 2018

  6. Bravo, R., Matute, J., Pina, J.M.: CSR as a vehicle to reveal the corporate identity: a study focused on the websites of Spanish financial entities. J. Bus. Ethics 107(2), 129–146 (2012)

    Article  Google Scholar 

  7. Przychodzen, J., Gomez-Bezares, F., Przychodzen, W., Larreina, M.: ESG issues among fund managers: factors and motives. Sustainability 8, 1078 (2016)

    Article  Google Scholar 

  8. Kumar, N.C.A., Smith, C., Badis, L., Wang, N., Ambrosy, P., Tavares, R.: ESG factors and risk-adjusted performance: a new quantitative model. J. Sustain. Financ. Invest. 6(4), 292–300 (2016). https://doi.org/10.1080/20430795.2016.1234909

    Article  Google Scholar 

  9. HSBC: Sustainable Financing and ESG Investing Report. https://www.gbm.hsbc.com/insights/sustainable-financing/sustainable-financing-and-esg-investing-report (2018). Accessed 31 Dec 2018

  10. FA Institute: Environmental, Social and Governance (ESG) Survey. http://www.cfainstitute.org/-/media/documents/survey/esg-survey-report-2017.ashx (2017). Accessed 31 Dec 2018

  11. Morningstar: The Morningstar Sustainability Rating: Helping Investors Evaluate the Sustainability of Portfolios. https://www.morningstar.com/articles/745467/morningstar-sustainability-rating.html (2017). Accessed 31 Dec 2018

  12. MSCI: MSCI ESG Ratings Methodology. https://www.msci.com/documents/10199/123a2b2b-1395-4aa2-a121-ea14de6d708a (2018). Accessed 31 Dec 2018

  13. Risklab: ESG Risk Factors in a Portfolio Context. https://www.ipe.com/esg-risk-in-a-portfolio-context/34522.article (2010). Accessed 31 Dec 2018

  14. Łuniewska, M.: Ekonometria finansowa. Analiza rynku kapitałowego. PWN, Warszawa (2008)

    Google Scholar 

  15. Wiśniewski, J.W.: Ekonometryczne badanie zjawisk jakościowych. Studium metodologiczne. Uniwersytet Mikołaja Kopernika, Toruń (1986)

    Google Scholar 

  16. Chow, G.C.: Ekonometria. PWN, Warszawa (1995)

    Google Scholar 

  17. Johnston, J.: Econometric Methods. McGraw-Hill Book Company (1991)

    Google Scholar 

  18. Zeliaś, A., Pawełek, B., Wanat, S.: Prognozowanie ekonomiczne. Teoria, przykłady, zadania. PWN, Warszawa (2003)

    Google Scholar 

  19. Gruszczyński, M. (ed.): Mikroekonometria. Modele i metody analizy danych indywidualnych, pp. 63, 75. Wolters Kluwer Polska Sp. z o.o., Warszawa (2010)

    Google Scholar 

  20. Gruszczyński, M.: Corporate governance and financial performance of companies in Poland. Int. Adv. Econ. Res. 12(2), 251–259 (2006)

    Article  Google Scholar 

  21. Gruszczyński, M.: Uporządkowany model logitowy: zastosowana biznesowe i finansowe. In: Tarczyński, W. (ed.) Rynek kapitałowy. Skuteczne inwestowanie. Wydawnictwo Naukowe Uniwersytetu Szczecińskiego, Szczecin (2007)

    Google Scholar 

  22. Curry, T., Fissel, G., Hanweck, G.: Market information, bank holding company risk, and market discipline. FDIC Working Paper 2003-04 (2003). https://doi.org/10.2139/ssrn.886687

  23. Berger, A.E.: Potential competitive effects of Basel II on banks in SME credit markets in the United States. J. Financ. Serv. Res. 26(1), 5–36 (2006)

    Article  Google Scholar 

  24. Masciandaro, D., Porta, A.: Single authority in financial markets supervision: lessons for UE enlargement. Paper presented at conference Financial Intermediation in the New Europe: Economics, Policies and Institutions, Mediolan (2003)

    Google Scholar 

  25. Freytag, A., Masciandaro, D.: Financial supervision fragmentation and central bank independence: the two sides of the same coin? University of Lecce Economics Working Paper 76(37) (2005). https://doi.org/10.2139/ssrn.837124

  26. Del-Rio, A., Young, G.: The impact of unsecured debt on financial distress among British households. Bank of England Working Paper 262 (2005). https://doi.org/10.2139/ssrn.824147

  27. Gascogine, J., Turner, P.: Asymmetries in Bank of England monetary policy. Appl. Econ. Lett. 11(10), 615–618 (2004). https://doi.org/10.1080/1350485042000227296

    Article  Google Scholar 

  28. Łuniewska, M., Tarczyński, W.: Metody wielowymiarowej analizy porównawczej na rynku kapitałowym, pp. 41–43, 57. PWN, Warszawa (2006)

    Google Scholar 

  29. Hellwig, Z.: Zastosowanie metody taksonomicznej do typologicznego podziału krajów ze względu na poziom ich rozwoju oraz zasoby i strukturę wykwalifikowanych kadr. Przegl. Stat. 4, 307–326 (1968)

    Google Scholar 

  30. Grabiński, T., Wydymus, S., Zeliaś, A.: Metody prognozowania rozwoju społeczno-gospodarczego. Wydawnictwo Akademii Ekonomicznej, Kraków (1982)

    Google Scholar 

  31. Pociecha, J., Podolec, B., Sokołowski, A., Zając, K.: Metody taksonomiczne w badaniach społeczno-ekonomicznych, p. 71. PWN, Warszawa (1998)

    Google Scholar 

  32. Nowak, E.: Metody Taksonomiczne w Klasyfikacji Obiektów Spo-łeczno-gospodarczych. PWE, Warszawa (1990)

    Google Scholar 

  33. Jajuga, K.: Statystyczna analiza wielowymiarowa. PWN, Warszawa (1993)

    Google Scholar 

  34. Malina, A.: Wielowymiarowa analiza przestrzennego zróżnicowania struktury gospodarki Polski według województw. Wydawnictwo AE w Krakowie, Kraków (2004)

    Google Scholar 

  35. Młodak, A.: Analiza taksonomiczna w statystyce regionalnej, pp. 136–137. Centrum Doradztwa i Informacji DIFIN, Warszawa (2006)

    Google Scholar 

  36. Panek, T.: Statystyczne metody wielowymiarowej analizy porównawczej, pp. 57–58. SGH w Warszawie, Warszawa (2009)

    Google Scholar 

  37. Walesiak, M.: Uogólniona miara odległości GDM w statystycznej analizie wielowymiarowej z wykorzystaniem programu R. Wydanie drugie poprawione i rozszerzone. Wydawnictwo Uniwersytetu Ekonomicznego, Wrocław (2016)

    Google Scholar 

  38. Vicke, P.: Multicriteria Decision-Aid. Wiley, Chichester (1992)

    Google Scholar 

  39. Broniewicz, B., Dziurdzikowska, E.: Metody wielokryterialne w równoważeniu procesów społeczno-gospodarczych. Pr. Nauk. Uniw. Ekon. Wrocław. 491, 53–62 (2017). https://doi.org/10.15611/pn.2017.491.05

    Article  Google Scholar 

  40. Mendoza, G.A., Martins, H.: Multi-criteria decision analysis in natural resource management: a critical review of methods and new modelling paradigms. For. Ecol. Manage. 230(1–3), 1–22 (2006). https://doi.org/10.1016/j.foreco.2006.03.023

    Article  Google Scholar 

  41. Huang, I.B., Keisler, J., Linkov, I.: Multi-criteria decision analysis in environmental sciences: ten years of applications and trends. Sci. Total Environ. 409(19), 3578–3594 (2011). https://doi.org/10.1016/j.scitotenv.2011.06.022

    Article  Google Scholar 

  42. Buchholz, T., Rametsteiner, E., Volk, T.A., Luzadis, V.A.: Multi criteria analysis for bioenergy systems assessments. Energy Policy 37(2), 484–495 (2009). https://doi.org/10.1016/j.enpol.2008.09.054

    Article  Google Scholar 

  43. Figueira, J., Greco, S., Ehrgott, M. (eds.): Multiple Criteria Decision Analysis: State of the Art Surveys. Springer, London (2005)

    Google Scholar 

  44. Nermend, K.: Metody analizy wielokryterialnej i wielowymiarowej we wspomaganiu decyzji. PWN, Warszawa (2017)

    Google Scholar 

  45. Figueira, J., Mousseau, V., Roy, B.: ELECTRE methods. In: Figueira, J., Greco, S., Ehrgott, M. (eds.) Multiple Criteria Decision Analysis: State of the Art Surveys. Springer, New York (2005)

    Chapter  Google Scholar 

  46. Triantaphyllou, E.: Multi-criteria Decision Making Methods: A Comparative Study. Kluwer Academic Publishers (2000)

    Google Scholar 

  47. Frondel, M., Horbach, J., Rennings, K.: End-of-pipe or cleaner production? An empirical comparison of environmental innovation decisions across OECD countries. Bus. Strategy Environ. 16, 571–584 (2007). https://doi.org/10.1002/bse.496

    Article  Google Scholar 

  48. Moussiopoulos, N., Achillas, C., Vlachokostas, C., Spyridi, D., Nikolaou, K.: Environmental, social and economic information management for the evaluation of sustainability in urban areas: a system of indicators for Thessaloniki, Greece. Cities 27(5), 377–384 (2010). https://doi.org/10.1016/j.cities.2010.06.001

    Article  Google Scholar 

  49. Inglehart, R.: Public support for environmental protection: objective problems and subjective values in 43 societies. Polit. Sci. Polit. 28(1), 57–72 (1995). https://doi.org/10.2307/420583

    Article  Google Scholar 

  50. Bassen, A., Meyer, K., Schlange, J.: The Influence of Corporate Responsibility on the Cost of Capital. http://ssrn.com/abstract=984406/ (2006). Accessed 30 Dec 2018

  51. Husted, B.W., Allen, D.B.: Strategic Corporate Social Responsibility and Value Creation: A Study of Multinational Enterprises in Mexico. https://core.ac.uk/download/pdf/9426392.pdf (1996). Accessed 31 Dec 2018

Download references

Acknowledgements

Research results presented in this paper are an element of research project implemented by the National Science Center Poland under the grant OPUS13 no UMO-2017/25/B/HS4/02172.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Magdalena Ziolo .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ziolo, M., Bak, I., Sinha, R., Datta, M. (2020). ESG Risk Perception in Sustainable Financial Decisions. Quantitative Methods Perspective. In: Nermend, K., Łatuszyńska, M. (eds) Experimental and Quantitative Methods in Contemporary Economics. CMEE 2018. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-30251-1_12

Download citation

Publish with us

Policies and ethics