Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/64639 
Authors: 
Year of Publication: 
2009
Series/Report no.: 
cemmap working paper No. CWP08/09
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
This paper presents new identification results for the class of structural dynamic discrete choice 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 utility function of one choice in the model is parametric but the distribution of unobserved heterogeneities is nonparametric. The proposed identification method does not rely on the availability of terminal period data and hence can be applied to infinite horizon structural dynamic models. For identification we assume availability of a continuous observed state variable that satisfies certain exclusion restrictions. If such excluded variable is accessible, we show that the structural dynamic discrete choice model is semiparametrically identified using the control function approach.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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