Dynamically eliciting unobservable information

Christopher P. Chambers, Nicolas S. Lambert
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引用次数: 14

Abstract

We answer the following question: At $t=1$, an expert has (probabilistic) information about a random outcome X. In addition, the expert will obtain further information about $X$ as time passes, up to some time t=T+1 at which X will be publicly revealed. (How) Can a protocol be devised that induces the expert, as a strict best response, to reveal at the outset his prior assessment of both X and the information flows he anticipates and, subsequently, what information he privately receives' (The protocol can provide the expert with payoffs that depend only on the realization of X, as well as any decisions he may take.) We show that this can be done with the following sort of protocol: At the penultimate time t=T, the expert chooses a payoff function from a menu of such functions, where the menu available to him was chosen by him at time $t=T-1$ from a menu of such menus, and so forth. We show that any protocol that affirmatively answers our question can be approximated by a protocol of the form described. We show how these results can be extended from discrete time to continuous time problems of this sort.
动态地引出不可观察的信息
我们回答以下问题:在$t=1$时,专家有关于随机结果X的(概率)信息。此外,随着时间的推移,专家将获得关于$X$的进一步信息,直到某个时间t= t +1, X将被公开。(如何)设计一个协议,作为严格的最佳反应,诱导专家在一开始就透露他对X和他预期的信息流的先前评估,以及随后他私下收到的信息”(协议可以为专家提供仅依赖于实现X的回报,以及他可能采取的任何决策)。我们证明这可以用以下协议来完成:在倒数第二个时间t= t,专家从这些函数的菜单中选择一个收益函数,其中他可用的菜单是他在时间$t= t -1$时从这些菜单的菜单中选择的,以此类推。我们证明,任何协议,肯定地回答我们的问题,可以近似的协议的形式描述。我们展示了如何将这些结果从离散时间问题推广到这类连续时间问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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