Identification and Estimation of Large Network Games with Private Link Information
Hulya Eraslan () and
Xun Tang ()
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Hulya Eraslan: Rice University, Department of Economics
Xun Tang: Rice University, Department of Economics
Koç University-TUSIAD Economic Research Forum Working Papers from Koc University-TUSIAD Economic Research Forum
We study the identification and estimation of large network games where each individual holds private information about its links and payoffs. Extending Galeotti, Goyal, Jackson, Vega-Redondo and Yariv (2010), we build a tractable empirical model of network games where the individuals are heterogeneous with private link and payoff information, and characterize its unique, symmetric pure-strategy Bayesian Nash equilibrium. We then show that the parameters in individual payoffs are identified under "large market" asymptotics, whereby the number of individuals increases to infinity in a fixed and small number of networks. We also propose a consistent two-step m-estimator for individual payoffs. Our method is distribution-free in that it does not require parametrization of the distribution of shocks in individual payoffs. Monte Carlo simulation show that our estimator has good performance in moderate-sized samples.
New Economics Papers: this item is included in nep-ecm, nep-gth, nep-net and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:koc:wpaper:1809
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