Struc Semiparametric Identification of Tural Dynamic Optimal Stopping Time Models

[Abstract] This paper presents new identi…cation results for the class of structural dynamic optimal stopping time models that are built upon the framework of the structural discrete Markov decision processes proposed by Rust (1994). We demonstrate how to semiparametrically identify the deep structural parameters of interest in the case where the utility function of an absorbing choice in the model is parametric but the distribution of unobserved heterogeneity is nonparametric. Our identi…cation strategy depends on availability of a continuous observed state variable that satis…es certain exclusion restrictions. If such excluded variable is accessible, we show that the dynamic optimal stopping model is semiparametrically identi…ed using control function approaches.