This paper develops identiﬁcation and estimation methods for dynamic structural models when agents’ actions are unobserved by econometricians. We provide conditions under which choice probabilities and latent state transition rules are nonparametrically identiﬁed with a continuous state variable in a single-agent dynamic discrete choice model. Our identiﬁcation results extend to (1) models with serially correlated unobserved heterogeneity and continuous choices, (2) cases in which only discrete state variables are available, and (3) dynamic discrete games. We apply our method to study moral hazard problems in US gubernatorial elections. We ﬁnd that the probabilities of shirking increase as the governors approach the end of their terms.