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弱信息假设下离散博弈的估计

Estimation of Discrete Games with Weak Assumptions on Information
Review of Economic Studies · 2022 · Lorenzo Magnolfi、Camilla Roncoroni

中文摘要

我们提出了一种在参与者可用信息的弱假设下估计静态离散博弈的方法。我们没有完全设定博弈的信息结构,而是允许所有与参与者知晓自身支付相一致的信息结构。为使该方法可行,我们采用贝叶斯相关均衡(BCE)作为解概念。我们在BCE与无限制的均衡选择下刻画了尖锐识别集,并发现在协变量变异有限的简单博弈中,识别集是提供信息的。在应用中,我们估计了意大利超市行业的进入模型,并量化了大型商场对当地超市的影响。估计与预测结果不同于在更严格假设下获得的结果。

Abstract

Abstract We propose a method to estimate static discrete games with weak assumptions on the information available to players. We do not fully specify the information structure of the game but allow instead for all information structures consistent with players knowing their own payoffs. To make this approach tractable, we adopt as a solution concept Bayes correlated equilibrium (BCE). We characterize the sharp identified set under BCE and unrestricted equilibrium selection, and find that in simple games with limited variation in covariates identified sets are informative. In an application, we estimate a model of entry in the Italian supermarket industry and quantify the effect of large malls on local supermarkets. Estimates and predictions differ from those obtained under more restrictive assumptions.
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