Set Inference for Semiparametric Discrete Games

Kyoo il Kim ()

No 16-2006, Working Papers from Singapore Management University, School of Economics

Abstract: We consider estimation and inference of parameters in discrete games allowing for multiple equilibria, without using an equilibrium selection rule. We do a set inference while a game model can contain infinite dimensional parameters. Examples can include signaling games with discrete types where the type distribution is nonparametrically specified and entry-exit games with partially linear payoffs functions. A consistent set estimator and a confidence interval of a function of parameters are provided in this paper. We note that achieving a consistent point estimation often requires an information reduction. Due to this less use of information, we may end up a point estimator with a larger variance and have a wider confidence interval than those of the set estimator using the full information in the model. This finding justifies the use of the set inference even though we can achieve a consistent point estimation. It is an interesting future research to compare these two alternatives: CI from the point estimation with the usage of less information vs. CI from the set estimation with the usage of the full information.

Keywords: Semiparametric Estimation; Set Inference; Infinite Dimensional Parameters; Inequality Moment Conditions; Signaling Game with Discrete Types (search for similar items in EconPapers)
JEL-codes: C13 C14 C35 C62 C73 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2006-09
New Economics Papers: this item is included in nep-ecm, nep-gth and nep-sea
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published in SMU Economics and Statistics Working Paper Series

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Working Paper: Set Inference for Semiparametric Discrete Games (2006)
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