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Signaling is an important topic in the study of asymmetric information ineconomic settings. In particular, the transparency of information available toa seller in an auction setting is a question of major interest. We introducethe study of signaling when conducting a second price auction of aprobabilistic good whose actual instantiation is known to the auctioneer butnot to the bidders. This framework can be used to model impressions selling indisplay advertising. We study the problem of computing a signaling scheme thatmaximizes the auctioneer's revenue in a Bayesian setting. While the generalcase is proved to be computationally hard, several cases of interest are shownto be polynomially solvable. In addition, we establish a tight bound on theminimum number of signals required to implement an optimal signaling scheme andshow that at least half of the maximum social welfare can be preserved withinsuch a scheme.

Signaling Schemes for Revenue Maximization