Identification of Dynamic Discrete Choice Models with Hyperbolic Discounting Using a Terminating Action

We study the identification of dynamic discrete choice models with hyperbolic discounting using a terminating action. We provide novel identification results for both sophisticated and naive agents’ discount factors and their utilities in a finite horizon framework under the assumption of a stationary flow utility. In contrast to existing identification strategies we do not require to observe the final period for the sophisticated agent. Moreover, we avoid normalizing the flow utility of a reference action for both the sophisticated and the naive agent. We propose two simple estimators: one that estimates the two discount factors without specifying the flow utilities, and another that jointly estimates both the discount factors and the flow utilities. We show that both estimators perform well in simulations.