Maximilian Schnippering
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Fakultät für Wirtschafts- und Sozialwissenschaften
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Titel des Forschungsprojektes:
Analyzing the Impacts of Corporate Social Performance on Corporate Financial Performance
Mentor:
Prof. Dr. Timo Busch
Hintergrund des Projekts:
Companies widely publish sustainability reports on their operations, set-up programs to improve their sustainability ratings and try to manage the social and environmental impacts of their products. However, for decades there has been an ongoing discussion whether these steps are really providing a financial value for the companies. This relation between Corporate Social Performance (CSP) and Corporate Financial Performance (CFP) is part of a long lasting discussion in academia (Barnett and Salomon 2012).
In that regard, McWilliams and Siegel (2000) pointed out the importance of selecting the right set of variables for a quantitative analysis as omitted variables will bias the estimation models. Hence, they are claiming that only studies are valid that control for all important variables. According to their findings, R&D is a key variable for analyzing the relationship between CSP and CFP. They are concluding that there is a neutral relationship between CSP and CFP when R&D is included in the model.
Zielsetzung des Projekts:
The underlying PhD project aims to reflect the before mentioned issue by using an enhanced longitudinal database for a robust quantitative analysis and by re-investigating the role of Research and Development (R&D) investments in this context.
The results shall indicate how sustainability measures have an impact on the financial performance of a company; thus providing well-based reasons for companies to deepen their engagement in sustainability management. Accordingly, the project aims to foster the transparency in this debate by providing an in-depth approach for examining the role of sustainability and building a business case.
Vorgehen:
The core hypothesis is based on the understanding that there is a significant relationship between CSP in CFP in a robust model that controls for all additional important variables.
The creation of a robust model that consists of a longitudinal time-series and that incorporates all relevant variables will be in the center of the analysis. Methodologically, multivariate statistics will be used in order to analyze the econometric models. Therefore, linear and curvilinear regression models will be designed. In order to build a solid database, information from ThomsenReuters’ Datastream will be used to obtain the necessary financial information and for the CSP information the MSCI ESG KLD dataset shall be used as this would be in accordance with the previous research. This data will allow for a panel design as information is available from 1991 to 2015.