Corporate Sustainability: A Model Uncertainty Analysis of Materiality

Abstract

For decades, scholars have searched for a connection between a corporation’s current performance with respect to sustainability and the future returns of its stock. In 2016, Khan, Serafeim, and Yoon published an apparent breakthrough in this quest: guidance on materiality from the Sustainability Accounting Standards Board allowed the construction of corporate sustainability scales that reliably predicted stock returns. Their finding had immediate and broad impact, but it remains, in its authors own words, just “first evidence.” Here, we further explore the relationship between material-sustainability and stock return by performing a “model uncertainty analysis.” We reproduce the original estimate but conclude that it is a statistical artifact. We then use machine learning to explore the practicality of employing historical associations to determine which aspects of sustainability are material to investors. We conclude that, for one popular source of data on corporate sustainability, accurate guidance on materiality may be difficult to achieve.

Keywords: materiality, social and financial performance, research methods, epistemology, model uncertainty, replication.

JEL Classification: Q51, D22, L25, C11, C18