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 unobserved 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 f Wt, Xt* | Wt-1, Xt-1* is identified from the observed distribution f Wt+1, Wt | Wt-1, Wt-2, Wt-3 under reasonable assumptions. Identification of f 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: Working Paper ; No. 543
- Klassifikation
-
Wirtschaft
- Thema
-
Markovscher Prozess
Ökonometrie
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Hu, Yingyao
Shum, Matthew
- Ereignis
-
Veröffentlichung
- (wer)
-
The Johns Hopkins University, Department of Economics
- (wo)
-
Baltimore, MD
- (wann)
-
2008
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Hu, Yingyao
- Shum, Matthew
- The Johns Hopkins University, Department of Economics
Entstanden
- 2008
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