A Learning-Based Approach to Evaluating Boards of Directors
57 Pages Posted: 13 Aug 2015 Last revised: 7 Oct 2018
Date Written: September 30, 2018
Directors matter, contrary to the “rubber-stamp” view of board governance. The gender of a director also matters, as does the individual’s specific function on the board. This paper uses a Bayesian learning model in the spirit of Pan, Wang and Weisbach (PWW, 2015) to study outstanding questions on boards. This framework reveals that a director has a statistically significant impact on governance-related uncertainty that is about one-third the impact that PWW find for new CEOs. The results help delineate what matters in governance by outlining the channels through which directors make a difference. For instance, while women on boards are not as influential on average, they are especially important when the firm faces acute monitoring needs, consistent with findings in Adams and Ferreira (2009).
Keywords: Board of Directors, Corporate Governance, Bayesian Learning, Director Turnover
JEL Classification: G30, G34, G39, M12, M51
Suggested Citation: Suggested Citation