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Identification and Estimation of Games with Incomplete Information Using Excluded Regressors

Author

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  • Arthur Lewbel

    () (Boston College)

  • Xun Tang

    (University of Pennsylvania)

Abstract

The existing literature on binary games with incomplete information assumes that either payoff functions or the distribution of private information are finitely parameterized to obtain point identification. In contrast, we show that, given excluded regressors, payoff functions and the distribution of private information can both be nonparametrically point identified. An excluded regressor for 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. We show how excluded regressors satisfying these conditions arise in contexts such as entry games between firms, as variation in observed components of fixed costs. Our identification proofs are constructive, so consistent nonparametric estimators can be readily based on them. For a semiparametric model with linear payoffs, we propose root-N consistent and asymptotically normal estimators for parameters in players payoffs. Finally, we extend our approach to accommodate the existence of multiple Bayesian Nash equilibria in the data-generating process without assuming equilibrium selection rules.

Suggested Citation

  • Arthur Lewbel & Xun Tang, 2012. "Identification and Estimation of Games with Incomplete Information Using Excluded Regressors," Boston College Working Papers in Economics 808, Boston College Department of Economics, revised 05 Mar 2013.
  • Handle: RePEc:boc:bocoec:808
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    References listed on IDEAS

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    Cited by:

    1. Chen, Songnian & Khan, Shakeeb & Tang, Xun, 2016. "Informational content of special regressors in heteroskedastic binary response models," Journal of Econometrics, Elsevier, vol. 193(1), pages 162-182.
    2. repec:eee:econom:v:201:y:2017:i:2:p:249-268 is not listed on IDEAS

    More about this item

    Keywords

    Games with Incomplete Information; Excluded Regressors; Nonparametric Identification; Semiparametric Estimation; Multiple Equilibria.;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection

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