Arbeitspapier
Nonparametric identification of dynamic models with unobserved state variables
We consider the identification of a Markov process {Wt, Xt*} for t=1,2,...,T when only {Wt} for t=1, 2,..,T is observed. In structural dynamic models, Wt denotes the sequence of choice variables and observed state variables of an optimizing agent, while Xt* denotes the sequence of serially correlated state variables. The Markov setting allows the distribution of the unobserved state variable Xt* to depend on Wt-1 and Xt-1*. We show that the joint distribution of (Wt, Xt*, Wt-1, Xt-1*) is identified from the observed distribution of (Wt+1, Wt, Wt-1, Wt-2, Wt-3) under reasonable assumptions. Identification of the joint distribution of (Wt, Xt*, Wt-1, Xt-1*) is a crucial input in methodologies for estimating dynamic models based on the conditional-choice-probability (CCP) approach pioneered by Hotz and Miller.
- Language
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Englisch
- Bibliographic citation
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Series: cemmap working paper ; No. CWP13/08
- Classification
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Wirtschaft
- Subject
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Markovscher Prozess
Ökonometrie
- Event
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Geistige Schöpfung
- (who)
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Hu, Yingyao
Shum, Matthew
- Event
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Veröffentlichung
- (who)
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Centre for Microdata Methods and Practice (cemmap)
- (where)
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London
- (when)
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2008
- DOI
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doi:10.1920/wp.cem.2008.1308
- Handle
- Last update
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10.03.2025, 11:44 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Hu, Yingyao
- Shum, Matthew
- Centre for Microdata Methods and Practice (cemmap)
Time of origin
- 2008
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