Identification and Estimation of Discrete Games of Complete Information

Stephen Ryan, Patrick Bajari and Han Hong

No 53, Computing in Economics and Finance 2005 from Society for Computational Economics

Abstract: We discuss the identification and estimation of discrete games with complete information. Following Bresnahan and Reiss, a discrete game is defined to be a generalization of a standard discrete choice model in which utility depends on the actions of other players. Using recent algorithms that compute the complete set of the Nash equilibria, we propose simulation-based estimators for static, discrete games. With appropriate exclusion restrictions about how covariates enter into payoffs and influence equilibrium selection, the model is identified with only weak parametric assumptions. Monte Carlo evidence demonstrates that the estimator can perform well in moderately-sized samples. As an illustration, we study the strategic decisions of firms in spatially-separated markets in establishing a presence on the Internet

Keywords: Empirical Industrial Organization; Simulation Based Estimation; Homotopies (search for similar items in EconPapers)
JEL-codes: C14 C15 L13 (search for similar items in EconPapers)
Date: 2005-11-11
New Economics Papers: this item is included in nep-dcm and nep-gth
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Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Identification and Estimation of a Discrete Game of Complete Information (2010)
Working Paper: Identification and Estimation of Discrete Games of Complete Information (2004)
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Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf5:53

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