Identification of Time Preferences in Dynamic Discrete Choice Models: Exploiting Choice Restrictions

I study the identification of time preferences in dynamic discrete choice models. Time preferences play a crucial role in these models, as they affect inference and counterfactual analysis. Previous literature has shown that observed choice probabilities do not identify the exponential discount factor in general. Recent identification results rely on specific forms of exogenous variation that impact transition probabilities but not instantaneous utilities. Although such variation allows for set identification of the respective parameter, point identification is only achieved in limited cases. To circumvent this shortcoming, I focus on models in which economic decision-makers might be restricted in their choice sets. I show that time preferences can be identified provided that there is variation in the probability of being restricted that does not affect utilities or transition probabilities. The derived exclusion restrictions are easy to interpret and potentially fulfilled in many empirical applications.