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Estimating Dynamic Discrete Choice Models Via Convex Analysis

Chiong, Khai X. and Galichon, Alfred and Shum, Matthew (2013) Estimating Dynamic Discrete Choice Models Via Convex Analysis. Social Science Working Paper, 1374. California Institute of Technology , Pasadena, CA. (Unpublished) http://resolver.caltech.edu/CaltechAUTHORS:20170727-090045366

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Abstract

Using results from convex analysis, we characterize the identification and estimation of dynamic discrete-choice models based on the random utility framework. Based on these insights, we propose a new two-step estimator for these models, which is easily applicable to models in which the utility shocks may not derive from an extreme- value distribution, and may be mutually correlated with each other and with the state variables. Monte Carlo results demonstrate the good performance of this estimator, and we provide a short application using the dynamic bus engine replacement model in Rust (1987).


Item Type:Report or Paper (Working Paper)
ORCID:
AuthorORCID
Shum, Matthew0000-0002-6262-915X
Additional Information:The authors thank Thierry Magnac for helpful comments, and John Rust for his data. Galichon’s research has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement n◦313699 and from FiME, Laboratoire de Finance des Marchés de l’Energie (www.fime-lab.org).
Group:Social Science Working Papers
Funders:
Funding AgencyGrant Number
European Research Council (ERC)UNSPECIFIED
Laboratoire de Finance des Marchés de l’EnergieUNSPECIFIED
Record Number:CaltechAUTHORS:20170727-090045366
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170727-090045366
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:79479
Collection:CaltechAUTHORS
Deposited By: Hanna Storlie
Deposited On:07 Aug 2017 18:34
Last Modified:08 Sep 2017 23:24

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