Learning About Directors

Abstract

This paper studies the importance of corporate boards through a learning model in which capital markets learn about incoming directors' quality. The model’s predictions are tested across a large sample of director appointments. Estimates show that governance-related uncertainty accounts for about 10% of stock return volatility when a new director joins. The learning framework provides a theoretically-grounded approach to identify when directors matter more to investors. The analysis shows that director importance varies with board composition and firm attributes: investors perceive directors as more important on boards with greater generational diversity, in smaller firms, and firms with higher knowledge capital.

Keywords: Boards of Directors, Corporate Governance, Bayesian Learning, Volatility

JEL Classification: G30, G34, G39, M12, M51