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Optimal Pricing of Information
arXiv - CS - Computer Science and Game Theory Pub Date : 2021-02-26 , DOI: arxiv-2102.13289
Shuze Liu, Weiran Shen, Haifeng Xu

A decision maker looks to take an active action (e.g., purchase some goods or make an investment). The payoff of this active action depends on his own private type as well as a random and unknown state of nature. To decide between this active action and another passive action, which always leads to a safe constant utility, the decision maker may purchase information from an information seller. The seller can access the realized state of nature, and this information is useful for the decision maker (i.e., the information buyer) to better estimate his payoff from the active action. We study the seller's problem of designing a revenue-optimal pricing scheme to sell her information to the buyer. Suppose the buyer's private type and the state of nature are drawn from two independent distributions, we fully characterize the optimal pricing mechanism for the seller in closed form. Specifically, under a natural linearity assumption of the buyer payoff function, we show that an optimal pricing mechanism is the threshold mechanism which charges each buyer type some upfront payment and then reveals whether the realized state is above some threshold or below it. The payment and the threshold are generally different for different buyer types, and are carefully tailored to accommodate the different amount of risks each buyer type can take. The proof of our results relies on novel techniques and concepts, such as upper/lower virtual values and their mixtures, which may be of independent interest.

中文翻译:

信息的最佳定价

决策者希望采取积极行动(例如,购买一些商品或进行投资)。这种积极行动的回报取决于他自己的私人类型以及随机和未知的自然状态。为了在此主动行动与另一个被动行动之间做出决定,这总是导致安全不断的效用,决策者可以从信息销售商那里购买信息。卖方可以访问已实现的自然状态,并且此信息对于决策者(即信息买方)有用,可以更好地从主动行动中估算其收益。我们研究了卖方设计收入最优定价方案以将其信息出售给买方的问题。假设买家的私人类型和自然状态是从两个独立的分布中得出的,我们以封闭形式全面描述了卖方的最佳定价机制。具体而言,在买方支付函数的自然线性假设下,我们表明最优定价机制是阈值机制,该机制对每种买方类型收取一定的预付款,然后揭示实现状态是高于某个阈值还是低于某个阈值。对于不同的购买者类型,付款和门槛通常是不同的,并且经过精心设计以适应每种购买者类型可能承担的不同风险。我们的结果证明依赖于新颖的技术和概念,例如较高/较低的虚拟值及其混合,它们可能具有独立的意义。我们证明了最佳定价机制是阈值机制,该机制对每个购买者类型收取一定的预付款,然后揭示实现状态是高于某个阈值还是低于某个阈值。对于不同的购买者类型,付款和门槛通常是不同的,并且经过精心调整以适应每种购买者类型可能承担的不同风险。我们的结果证明依赖于新颖的技术和概念,例如较高/较低的虚拟值及其混合,它们可能具有独立的意义。我们证明了最佳定价机制是阈值机制,该机制对每个购买者类型收取一定的预付款,然后揭示实现状态是高于某个阈值还是低于某个阈值。对于不同的购买者类型,付款和门槛通常是不同的,并且经过精心调整以适应每种购买者类型可能承担的不同风险。我们的结果证明依赖于新颖的技术和概念,例如较高/较低的虚拟值及其混合,它们可能具有独立的意义。并经过精心设计,以适应每种类型的买方可能承担的不同风险。我们的结果证明依赖于新颖的技术和概念,例如较高/较低的虚拟值及其混合,它们可能具有独立的意义。并经过精心设计,以适应每种类型的买方可能承担的不同风险。我们的结果证明依赖于新颖的技术和概念,例如较高/较低的虚拟值及其混合,它们可能具有独立的意义。
更新日期:2021-03-01
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