论文标题
关于有限理性不注意模型的分布鲁棒性
On the Distributional Robustness of Finite Rational Inattention Models
论文作者
论文摘要
在本文中，我们研究了在决策者面临有关状态的真实先验分布面临的不确定性的环境中的理性不专有模型。决策者试图选择一套随机选择规则，而不是一组有限的替代方案，这些替代方案对先前的歧义是可靠的。我们完全表征了理性不集中模型的分布鲁棒性，这是根据可拖动的凹入程序的。我们建立了必要和足够的条件来构建强大的考虑集。最后，我们通过引入\ emph {糟糕的敏感性}的概念来量化先前不确定性的影响。
In this paper we study a rational inattention model in environments where the decision maker faces uncertainty about the true prior distribution over states. The decision maker seeks to select a stochastic choice rule over a finite set of alternatives that is robust to prior ambiguity. We fully characterize the distributional robustness of the rational inattention model in terms of a tractable concave program. We establish necessary and sufficient conditions to construct robust consideration sets. Finally, we quantify the impact of prior uncertainty, by introducing the notion of \emph{Worst-Case Sensitivity}.
