Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/217158 
Year of Publication: 
2019
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 10 [Issue:] 3 [Publisher:] The Econometric Society [Place:] New Haven, CT [Year:] 2019 [Pages:] 853-890
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
The estimation of nonstationary dynamic discrete choice models typically requires making assumptions far beyond the length of the data. We extend the class of dynamic discrete choice models that require only a few-period-ahead conditional choice probabilities, and develop algorithms to calculate the finite dependence paths. We do this both in single agent and games settings, resulting in expressions for the value functions that allow for much weaker assumptions regarding the time horizon and the transitions of the state variables beyond the sample period.
Subjects: 
Dynamic discrete choice
finite dependence
conditional choice probabilities
JEL: 
C33
C35
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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