Empirical applications of dyanamic discrete choice models usually either take the discount factor to be known or rely on high level exclusion restrictions that are difficult to interpret and hard to satisfy. We provide identification results under an intuitively appealing exclusion restriction on primitive utilities that is more directly useful in applied research. We show that while such exclusion restructions are not sufficient for point identification, they identify the discount factor up to a finite set. The identified set is characterized as the solutions to a single, well-behaved moment condition. We also show that our and existing exclusion restrictions limit the choice and state transition probability data in different ways; that is, they give the model nontrivial and distinct empirical content.