Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/79286 
Autor:innen: 
Erscheinungsjahr: 
2007
Schriftenreihe/Nr.: 
cemmap working paper No. CWP06/07
Verlag: 
Centre for Microdata Methods and Practice (cemmap), London
Zusammenfassung: 
This paper presents new identification 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 identification strategy depends on availability of a continuous observed state variable that satisfies certain exclusion restrictions. If such excluded variable is accessible, we show that the dynamic optimal stopping model is semiparametrically identified using control function approaches.
Schlagwörter: 
structural dynamic discrete choice models , semiparametric identification, optimal stopping time models
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
263.16 kB





Publikationen in EconStor sind urheberrechtlich geschützt.