Abstract
This paper revisits Heinrich F. von Stackelberg's original description of leader-follower games under incomplete information, exploring how learning dynamics shape strategic interaction. The leader iteratively updates its conjecture about the follower's reaction function before choosing the activity level that maximizes its payoff. The follower, in turn, responds optimally to each activity level, revealing information that the leader uses to refine its conjecture. Assuming linear conjectures, a smooth updating process à la Jean- Marie and Tidball (2006), and quadratic payoff functions, we establish conditions for which the learning process converges asymptotically. We characterize the outcomes of the learning process in terms of activity levels and payoffs, within both a sequential partnership game and a sequential duopoly game with quantity competition. Moreover, we compare these outcomes to those of the complete information solution and the cooperative solution. In the process, we uncover conditions under which the lack of information, and resulting strategic ambiguity, leads to higher joint payoffs, and under which usual intuitions about the first mover advantage need qualifications.