When Blockholders Vote: Information Aggregation in DAO Governance

Abstract

DAO governance reveals a time path of votes rather than only a final voting outcome. We use this transparency to test a classic corporate governance question: when do large shareholders use their votes to lead other investors, and when do they wait to learn from them? We develop a dynamic model in which an informed blockholder chooses when to vote in a sequential voting process. The central tradeoff is between learning and leadership: waiting lets the blockholder learn from small-voter actions, while voting early reveals expert information to later voters. The model predicts that majority blockholders wait, while relative precision increases the value of earlier intervention. It also shows how multiple blockholders can cross-validate one another’s signals. Using DAO vote-sequence data, we show that whales with higher relative precision vote earlier, whereas majority whales vote later. Early resolution is positively associated with subsequent TVL growth when it is accompanied by multiple-whale participation, while neither component alone is robustly positive. The evidence suggests that blockholder voting is not merely an exercise of control, but a dynamic process in which voting power and information advantage jointly determine when large shareholders act.