Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/49893
Authors: 
Hu, Yingyao
Shum, Matthew
Year of Publication: 
2008
Series/Report no.: 
Working papers // the Johns Hopkins University, Department of Economics 543
Abstract: 
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, WtWt-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.
Document Type: 
Working Paper

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