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Identification and estimation of games with incomplete information using excluded regressors

Arthur Lewbel and Xun Tang

Journal of Econometrics, 2015, vol. 189, issue 1, 229-244

Abstract: We show structural components in binary games with incomplete information are nonparametrically identified using variation in player-specific excluded regressors. An excluded regressor for a player i is a sufficiently varying state variable that does not affect other players’ utility and is additively separable from other components in i’s payoff. Such excluded regressors arise in various empirical contexts. Our identification method is constructive, and provides a basis for nonparametric estimators. For a semiparametric model with linear payoffs, we propose root-N consistent and asymptotically normal estimators for players’ payoffs. We also discuss extension to the case with multiple Bayesian Nash equilibria in the data-generating process without assuming equilibrium selection rules.

Keywords: Games with incomplete information; Excluded regressors; Nonparametric identification; Semiparametric estimation; Multiple equilibria (search for similar items in EconPapers)
JEL-codes: C14 C51 D43 (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (16)

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Working Paper: Identification and Estimation of Games with Incomplete Information Using Excluded Regressors (2013) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:189:y:2015:i:1:p:229-244

DOI: 10.1016/j.jeconom.2014.10.014

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