Board Background, ESG Engagement, and Asset Prices

Companies are increasingly required by its stakeholders and society to incorporate environmental, social, and governance (ESG) goals into its decision making. To achieve these goals, board members are expected to have adequate expertise on these subjects. The objective of this study is to examine how the ESG background of board members including education and work experience affects firms' ESG engagement, and how business outcome and the stock market react to this during normal and crisis periods, especially after the outbreak of COVID-19. This project aims to construct a new measure of firms' ESG engagement using machine learning, based on a variety of corporate/regulatory disclosures including earnings calls, 10-Ks and SEC comment letters from multiple novel sources.
The project contributes to the literature in the following ways:
(i) the relationship between board members' background and firms' ESG engagement is rarely explored. Understanding this relationship is crucial not only for shareholders and investors, but also for policymakers for the purpose of regulation, and the study aims to provide the first evidence on this;
(ii) the study proposes a new measure of firms' ESG engagement using new techniques in machine learning and text mining, which can capture the perspectives from both investors and regulators and potentially address the self-reporting issue from firm disclosures.

Overall, the project aims to provide evidence that has implications for shareholders, investors and regulators to more effectively support firms' undertaking of ESG policies and to better measure ESG engagement to promote sustainable development and growth for society.