Conditional Choice Probabilities and the Estimation of Dynamic Models
AbstractThis paper develops a new method for estimating the structural parameters of (discrete choice) dynamic programming problems. They show the valuation functions characterizing the expected future utility associated with the choices often can be represented as an easily computed function of the state variables, structural parameters, and the probabilities of choosing alternative actions for states which are feasible in the future. Under certain conditions, nonparametric estimators of these probabilities can be formed from sample information. Substituting the estimators for the true conditional choice probabilities, the authors establish the consistency and asymptotic normality of the resulting structural parameter estimators. Copyright 1993 by The Review of Economic Studies Limited.
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Bibliographic InfoArticle provided by Wiley Blackwell in its journal Review of Economic Studies.
Volume (Year): 60 (1993)
Issue (Month): 3 (July)
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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0034-6527
Other versions of this item:
- Hotz, V.J. & Miller, R.A., 1991. "Conditional Choice Probabilities and the Estimation of Dynamic Models," GSIA Working Papers 1992-12, Carnegie Mellon University, Tepper School of Business.
- V. Joseph Hotz & Robert A. Miller, 1992. "Conditional Choice Probabilities and the Estimation of Dynamic Models," Working Papers 9202, Harris School of Public Policy Studies, University of Chicago.
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