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.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP13/08
- Klassifikation
-
Wirtschaft
- Thema
-
Markovscher Prozess
Ökonometrie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Hu, Yingyao
Shum, Matthew
- Ereignis
-
Veröffentlichung
- (wer)
-
Centre for Microdata Methods and Practice (cemmap)
- (wo)
-
London
- (wann)
-
2008
- DOI
-
doi:10.1920/wp.cem.2008.1308
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Hu, Yingyao
- Shum, Matthew
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2008
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