A Learning-Based Approach to Evaluating Boards of Directors
60 Pages Posted: 7 Jun 2017
Date Written: March 14, 2017
Using predictions from a learning model, this paper exploits the cross-sectional variation in the learning-induced decline in stock return volatility over director tenure to infer the marginal value of different kinds of directors. This new framework confirms prior empirical findings and documents new results. For example, directors joining better compensated boards have higher marginal value while the marginal value of a director joining an entrenched board is muted. Furthermore, the estimates imply that governance related uncertainty associated with the arrival of a new director accounts for 7% of return volatility, shedding light on the extent to which governance matters.
Suggested Citation: Suggested Citation