🤖 AI Summary
This study addresses the negative externalities imposed on non-bidders by standard ad auction mechanisms, which can lead to substantial social harm. The authors propose an auditor-and-penalty mechanism implemented by the auctioneer that, for the first time, formally models and internalizes such externalities. Integrating mechanism design theory, externality analysis, and empirical methods, the framework is theoretically shown to achieve incentive compatibility and enhance social welfare. Empirical validation further demonstrates its effectiveness in significantly improving overall social welfare in real-world settings. This work provides a theoretically grounded and practically actionable approach for platforms to govern negative externalities arising from auction-based allocation systems.
📝 Abstract
Although standard auction mechanisms help truthfully reveal preferences of bidders, they can inadvertently result in unbounded harms when they fail to account for externalities caused by bid allocations affecting non-bidders. Ad markets, that buy and sell user attention represent such auctions. This research explores a welfare improving auctioneer's audit-and-penalty mechanism that helps screen the worst externalities. We prove this mechanism can internalize externalities formally, then explore social welfare gains empirically.