Efficiency of the Generalized Second-Price Auction for Value Maximizers

Yuan Deng, Mohammad Mahdian, Jieming Mao, Vahab Mirrokni, Hanrui Zhang, Song Zuo

Keywords: autobidding, generalized second price auction, price of anarchy

TL;DR: We prove fine-grained bounds on the price of anarchy of the generalized second-price auction where bidders are value maximizers (i.e., autobidders).

Abstract: We study the price of anarchy of the generalized second-price auction where bidders are value maximizers (i.e., autobidders). We show that in general the price of anarchy can be as bad as $0$. For comparison, the price of anarchy of running VCG is $1/2$ in the autobidding world. We further show a fined-grained price of anarchy with respect to the discount factors (i.e., the ratios of click probabilities between lower slots and the highest slot in each auction) in the generalized second-price auction, which highlights the qualitative relation between the smoothness of the discount factors and the efficiency of the generalized second-price auction.

Track: Economics, Online Markets, and Human Computation

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Submission Number: 288