Bidding to the Top: VCG and Equilibria of Position-Based Auctions
Gagan Aggarwal, S. Muthukrishnan, Jon Feldman

TL;DR
This paper introduces a position-based auction model where advertisers specify position preferences, and demonstrates that a simple mechanism achieves VCG-like outcomes with envy-free equilibria, improving auction efficiency.
Contribution
It proposes a new position-based auction mechanism that generalizes existing models and achieves VCG-like equilibrium outcomes with desirable properties.
Findings
The auction has an envy-free Nash equilibrium matching VCG outcomes.
The equilibrium maximizes advertisers' profits within the model.
The mechanism extends current auction designs to include position preferences.
Abstract
Many popular search engines run an auction to determine the placement of advertisements next to search results. Current auctions at Google and Yahoo! let advertisers specify a single amount as their bid in the auction. This bid is interpreted as the maximum amount the advertiser is willing to pay per click on its ad. When search queries arrive, the bids are used to rank the ads linearly on the search result page. The advertisers pay for each user who clicks on their ad, and the amount charged depends on the bids of all the advertisers participating in the auction. In order to be effective, advertisers seek to be as high on the list as their budget permits, subject to the market. We study the problem of ranking ads and associated pricing mechanisms when the advertisers not only specify a bid, but additionally express their preference for positions in the list of ads. In particular, we…
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Taxonomy
TopicsAuction Theory and Applications · Consumer Market Behavior and Pricing · Merger and Competition Analysis
