The Role of ESG in Sustainable Development: An Analysis Through the Lens of Machine Learning

Abstract

With the ever-increasing environmental degradation, poor corporate governance, and social disharmony, adopting sustainable practices is imperative to ensure a prolonged and healthy quality of life. Environmental, social and governance (ESG) investing is a form of socially responsible investing promoting sustainability. ESG ratings quantitatively measure the sustainable practices of companies, with lower ratings meaning more sustainable practices adopted. With the goal of contributing to United Nations' sustainable development goal number 17, first, we present a methodology for creating a dataset that houses both ESG and financial parameters of publicly listed companies worldwide. Second, we present a framework for conducting statistical analysis and leveraging machine learning techniques to gauge the importance of ESG parameters for investment decisions and how they affect financial performance of firms. For companies with the best ESG ratings, ‘return on equity’ was found to be greater than rest of the companies. While using linear and random forest regression models, prediction accuracy of growth variables ‘profit margin’ and 'return on assets' increased when ESG data was used along with financial data as input. Companies having the highest 'profit margins' were the ones having the best ESG ratings. With this study, we hope to bolster worldwide collaboration for sustainable development.