Bayesian Estimation of a Dynamic Game with Endogenous, Partially Observed, Serially Correlated State

38 Pages Posted: 24 Jan 2012

See all articles by A. Ronald Gallant

A. Ronald Gallant

Duke University - Fuqua School of Business, Economics Group; New York University - Department of Economics

Han Hong

Independent

Ahmed Khwaja

University of Cambridge - Judge Business School; Yale School of Management; Yale University - Cowles Foundation

Date Written: December 1, 2011

Abstract

We consider dynamic games that can have state variables that are partially observed, serially correlated, endogenous, and heterogeneous. We propose a Bayesian method that uses a particle filter to compute an unbiased estimate of the likelihood within a Metropolis chain. Unbiasedness guarantees that the stationary density of the chain is the exact posterior, not an approximation. The number of particles required is easily determined. The regularity conditions are weak. Results are verified by simulation from two dynamic oligopolistic games with endogenous state. One is an entry game with feedback to costs based on past entry and the other a model of an industry with a large number of heterogeneous firms that compete on product quality.

Keywords: Dynamic Games, Partially Observed State, Endogenous State, Serially Correlated State, Particle Filter

JEL Classification: E00, G12, C51, C52

Suggested Citation

Gallant, A. Ronald and Hong, Han and Khwaja, Ahmed, Bayesian Estimation of a Dynamic Game with Endogenous, Partially Observed, Serially Correlated State (December 1, 2011). Economic Research Initiatives at Duke (ERID) Working Paper No. 118. Available at SSRN: https://ssrn.com/abstract=1990446

A. Ronald Gallant (Contact Author)

Duke University - Fuqua School of Business, Economics Group ( email )

Box 90097
Durham, NC 27708-0097
United States

New York University - Department of Economics ( email )

269 Mercer Street, 7th Floor
New York, NY 10011
United States

Han Hong

Independent

No Address Available

Ahmed Khwaja

University of Cambridge - Judge Business School ( email )

Trumpington Street
Cambridge, CB2 1AG
United Kingdom

Yale School of Management ( email )

135 Prospect Street
P.O. Box 208200
New Haven, CT 06520-8200
United States

Yale University - Cowles Foundation

Box 208281
New Haven, CT 06520-8281
United States

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