Identification and Estimation of Discrete Games of Complete Information
Stephen Ryan (),
Patrick Bajari and
No 53, Computing in Economics and Finance 2005 from Society for Computational Economics
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: L13 C14 C15 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dcm and nep-gth
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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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