TY - JOUR
T1 - Forecasting the environmental, social, and governance rating of firms by using corporate financial performance variables
T2 - A rough set approach
AU - García, Fernando
AU - González-Bueno, Jairo
AU - Guijarro, Francisco
AU - Oliver, Javier
N1 - Publisher Copyright:
© 2020 by the authors.
PY - 2020/4/1
Y1 - 2020/4/1
N2 - The environmental, social, and governance (ESG) rating of firms is a useful tool for stakeholders and investment decision-makers. This paper develops a rough set model to relate ESG scores to popular corporate financial performance measures. This methodology permits handling with information in an uncertain, ambiguous, and imperfect context. A large database was gathered, including ESG scores, as well as industry sector and financial variables for publicly traded European companies during the period 2013–2018. We carried out 500 simulations of the rough set model for different values in the discretization parameter and different grouping scenarios of firms regarding ESG scores. The results suggest that the variables considered are useful in the prediction of ESG rank when firms are clustered in three or four equally balanced groups. However, the prediction power vanishes when a larger number of groups is computed. This would suggest that industry sector and financial variables serve to find big differences across firms regarding ESG, but the significance of the model drops when small differences in ESG performance are scrutinized.
AB - The environmental, social, and governance (ESG) rating of firms is a useful tool for stakeholders and investment decision-makers. This paper develops a rough set model to relate ESG scores to popular corporate financial performance measures. This methodology permits handling with information in an uncertain, ambiguous, and imperfect context. A large database was gathered, including ESG scores, as well as industry sector and financial variables for publicly traded European companies during the period 2013–2018. We carried out 500 simulations of the rough set model for different values in the discretization parameter and different grouping scenarios of firms regarding ESG scores. The results suggest that the variables considered are useful in the prediction of ESG rank when firms are clustered in three or four equally balanced groups. However, the prediction power vanishes when a larger number of groups is computed. This would suggest that industry sector and financial variables serve to find big differences across firms regarding ESG, but the significance of the model drops when small differences in ESG performance are scrutinized.
KW - Corporate financial performance
KW - Corporate social performance
KW - Esg rating
KW - Rough sets
KW - corporate financial performance
KW - corporate social performance
KW - ESG rating
KW - rough sets
UR - http://www.scopus.com/inward/record.url?scp=85085092870&partnerID=8YFLogxK
U2 - 10.3390/SU12083324
DO - 10.3390/SU12083324
M3 - Artículo en revista científica indexada
AN - SCOPUS:85085092870
SN - 2071-1050
VL - 12
JO - Sustainability (Switzerland)
JF - Sustainability (Switzerland)
IS - 8
M1 - 3324
ER -