Identifying Dynamic Games with Serially-Correlated Unobservables

19 Pages Posted: 20 Mar 2016

See all articles by Yingyao Hu

Yingyao Hu

Johns Hopkins University - Department of Economics

Matthew Shum

California Institute of Technology

Date Written: June 10, 2013

Abstract

In this paper 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.

Suggested Citation

Hu, Yingyao and Shum, Matthew, Identifying Dynamic Games with Serially-Correlated Unobservables (June 10, 2013). Available at SSRN: https://ssrn.com/abstract=2750177 or http://dx.doi.org/10.2139/ssrn.2750177

Yingyao Hu

Johns Hopkins University - Department of Economics ( email )

3400 Charles Street
Baltimore, MD 21218-2685
United States

Matthew Shum (Contact Author)

California Institute of Technology ( email )

Pasadena, CA 91125
United States

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