Robust Scale-Free Auctions
2026-08-03 • Computer Science and Game Theory
Computer Science and Game Theory
AI summaryⓘ
The authors study how to design auctions when the seller knows very limited information about the bidders’ value distribution, only certain shape properties but not exact values. They show that in many cases, a simple auction where the highest bidder wins without a minimum price (second-price auction without reserve) works best against the worst-case scenarios. For two bidders, they find a more complex auction mixing known types performs slightly better. They also show that sometimes giving the item to a lower bidder can improve outcomes, but this depends on the type of assumptions made on the bidders’ value distributions.
auctionsprior-independentdominant-strategy incentive-compatiblesecond-price auctionmaximin optimalitymonotone hazard rateregularityworst-case ratioallocation rulesBayesian optimum
Authors
Jerry Anunrojwong
Abstract
We study prior-independent auction design when bidder values are independently and identically distributed and the seller knows only a scale-invariant shape restriction on their distribution, but neither the distribution nor the scale of values. We show that the maximin problem over a broad class of dominant-strategy incentive-compatible mechanisms reduces without loss to scale-free mechanisms. For any $n\ge 2$ monotone-hazard-rate bidders, the second-price auction without a reserve is maximin optimal over this class, including randomized mechanisms that may allocate to a lower bidder. We derive its exact guarantee for every $n$ and the sharp exponential rate at which its loss relative to the Bayesian optimum vanishes. Many familiar auctions are standard: they allocate only to a highest bidder, although incentive compatibility does not require this. For two regular bidders, we solve the standard problem exactly: its optimal mechanism mixes the second-price auction with a relative-markup auction and achieves a worst-case ratio of approximately $0.524413$. We construct a nonstandard mechanism that sometimes allocates to the lower bidder and achieves approximately $0.524829$, proving that standardness is strictly costly. The contrast is driven by tail restrictions: monotone hazard rate makes lower-rank allocation unhelpful, whereas regularity permits it to improve worst-case revenue.