Revenue Enhancement Via Asymmetric Signaling in Interdependent-Value Auctions

THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE(2019)

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摘要
We consider the problem of designing the information environment for revenue maximization in a sealed-bid second price auction with two bidders. Much of the prior literature has focused on signal design in settings where bidders are symmetrically informed, or on the design of optimal mechanisms under fixed information structures. We study common- and interdependent-value settings where the mechanism is fixed (a second-price auction), but the auctioneer controls the signal structure for bidders. We show that in a standard common- value auction setting, there is no benefit to the auctioneer in terms of expected revenue from sharing information with the bidders, although there are effects on the distribution of revenues. In an interdependent-value model with mixed private- and common- value components, however, we show that asymmetric, information-revealing signals can increase revenue.
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