Et studie af latente faktorer i ESG-scoren: Effekten af ESG-scorer på virksomheders finansielle performance

Martin Larsen & Frederik Munck Bigom

Studenteropgave: Kandidatafhandlinger


This paper investigates the effects of the different levels of ESG scores, and their underlying data, on the financial performance of S&P500 companies. The study is based on Thomson Reuters ESG data between 2005 and 2018. Initially a thorough sampling process is executed, including data imputation, to take care of the missing observations. The final sample includes 45 of the initial 500 companies and their respective ESG-score, pillar-scores, sub-scores and 21 of their fundamental enviromental- and raw data variables. The analysis, based on univariate time series analysis and multidimensional panel data regression analysis, aim to investigate the magnitude of ESG determinants on log-return. By conducting a thorough modelling process, where log-returns are fitted with each and every variable as external covariate, 345 models are identified. These models show that the magnitude of ESG determinants are indifferent. This is confirmed in extension by the results of the multidimensional regression analysis, which furthermore shows that the initially omitted inter-individual differences have no impact on the results. The robustness tests of both the univariate time series analysis and the multidimensional regression analysis is checked by conducting multiple tests, which include, tests of informationcriteria, imputation, influential observations and timeintervals. These measures are taken in order to validate the methological choices made in this paper. In short, by validating the robustness of the sampling and modelling process, this paper establishes that both ESG-scores and their underlying determinants have no significant impact on returns of S&P500 companies.

UddannelserCand.merc.mat Erhvervsøkonomi og Matematik, (Kandidatuddannelse) Afsluttende afhandling
Antal sider148