Fair Equilibria in Sponsored Search Auctions: The Advertisers' Perspective

TL;DR

This paper introduces fair division mechanisms integrated with GSP auctions to promote fairness among advertisers, analyzing their strategic behavior, equilibrium properties, and real-world performance.

Contribution

It proposes two novel fair GSP mechanisms, proves their equilibrium and budget balance properties, and evaluates their effectiveness with real-world data.

Findings

Mechanisms reach equilibria with high social welfare

Payments are budget balanced and reflect total compensation

Fairness criteria improve allocation quality in experiments

Abstract

In this work we introduce a new class of mechanisms composed of a traditional Generalized Second Price (GSP) auction and a fair division scheme, in order to achieve some desired level of fairness between groups of Bayesian strategic advertisers. We propose two mechanisms, $\beta$-Fair GSP and GSP-EFX, that compose GSP with, respectively, an envy-free up to one item, and an envy-free up to any item fair division scheme. The payments of GSP are adjusted in order to compensate advertisers that suffer a loss of efficiency due the fair division stage. We investigate the strategic learning implications of the deployment of sponsored search auction mechanisms that obey to such fairness criteria. We prove that, for both mechanisms, if bidders play so as to minimize their external regret they are guaranteed to reach an equilibrium with good social welfare. We also prove that the mechanisms are budget balanced, so that the payments charged by the traditional GSP mechanism are a good proxy of the total compensation offered to the advertisers. Finally, we evaluate the quality of the allocations through experiments on real-world data.