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Identifying Dynamic Games with Serially Correlated Unobservables

Hu, Yingyao and Shum, Matthew (2013) Identifying Dynamic Games with Serially Correlated Unobservables. In: Structural Econometric Models. Advances in Econometrics. No.31. Emerald Group Publishing Limited , Bingley, UK, pp. 97-113. ISBN 9781783500529.

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In this article, we consider the nonparametric identification of Markov dynamic games models in which each firm has its own unobserved state variable, which is persistent over time. This class of models includes most models in the Ericson and Pakes (1995) and Pakes and McGuire (1994) framework. We provide conditions under which the joint Markov equilibrium process of the firms’ observed and unobserved variables can be nonparametrically identified from data. For stationary continuous action games, we show that only three observations of the observed component are required to identify the equilibrium Markov process of the dynamic game. When agents’ choice variables are discrete, but the unobserved state variables are continuous, four observations are required.

Item Type:Book Section
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URLURL TypeDescription chapter chapter
Shum, Matthew0000-0002-6262-915X
Additional Information:Copyright 2013 by Emerald Group Publishing Limited. First draft: August 20, 2008. Caltech held draft: October 13, 2008.
Subject Keywords:Dynamic games, identification, unobserved heterogeneity, serial correlation
Series Name:Advances in Econometrics
Issue or Number:31
Classification Code:JEL: L13, C73, C14
Record Number:CaltechAUTHORS:20160329-104135709
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Official Citation: Yingyao Hu , Matthew Shum (2013), Identifying Dynamic Games with Serially Correlated Unobservables, in Eugene Choo , Matthew Shum (ed.) Structural Econometric Models (Advances in Econometrics, Volume 31) Emerald Group Publishing Limited, pp.97 - 113
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:65741
Deposited On:30 Mar 2016 19:27
Last Modified:10 Nov 2021 23:49

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