SIER Working Paper Series

113 Learning Rival’s Information in Interdependent Value Auctions

Abstract

We study a simple auction model with interdependent values in which bidders can learn their rival’s information and compete in the first-price or second-price auction. We characterize unique symmetric equilibrium strategies-both learning and bidding strategies-for the two auction formats. While bidders learn rival’s signals with higher probabilities in the first-price auction, they earn higher rent in the second-price auction. We also show that when learning cost is small, signal correlation is low, or value interdependence is weak, the first-price auction generates a higher revenue than the second-price auction, while the revenue ranking is reversed otherwise.