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Econometrica Vol. 78 No. 5 2010

Identification and Estimation of a Discrete Game of Complete Information

Patrick Bajari1; Han Hong2; Stephen Patrick Ryan3

1 University of Minnesota · 2 Stanford University · 3 Massachusetts Institute of Technology

open access

Abstract

We discuss the identification and estimation of discrete games of complete information. Following Bresnahan and Reiss (1990, 1991), a discrete game is a generalization of a standard discrete choice model where utility depends on the actions of other players. Using recent algorithms to compute all of the Nash equilibria to a game, we propose simulation-based estimators for static, discrete games. We demonstrate that the model is identified under weak functional form assumptions using exclusion restrictions and an identification at infinity approach. Monte Carlo evidence demonstrates that the estimator can perform well in moderately sized samples. As an application, we study entry decisions by construction contractors to bid on highway projects in California. We find that an equilibrium is more likely to be observed if it maximizes joint profits, has a higher Nash product, uses mixed strategies, and is not Pareto dominated by another equilibrium.

DOI
10.3982/ecta5434
Volume
78
Issue
5
Pages
1529-1568
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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