Revenue monotonicity in deterministic, dominant-strategy combinatorial auctions

Authors:
Baharak Rastegari;Anne Condon;Kevin Leyton-Brown
Affiliations:
Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver, B.C., Canada, V6T 1Z4;Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver, B.C., Canada, V6T 1Z4;Department of Computer Science, University of British Columbia, 2366 Main Mall, Vancouver, B.C., Canada, V6T 1Z4
Venue:
Artificial Intelligence
Year:
2011

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Abstract

In combinatorial auctions using VCG, a seller can sometimes increase revenue by dropping bidders. In this paper we investigate the extent to which this counterintuitive phenomenon can also occur under other deterministic, dominant-strategy combinatorial auction mechanisms. Our main result is that such failures of ''revenue monotonicity'' can occur under any such mechanism that is weakly maximal-meaning roughly that it chooses allocations that cannot be augmented to cause a losing bidder to win without hurting winning bidders-and that allows bidders to express arbitrary known single-minded preferences. We also give a set of other impossibility results as corollaries, concerning revenue when the set of goods changes, false-name-proofness, and the core.