Auction Design with a Bit of Information

2026-08-06

AI Summary

This study addresses revenue maximization in a two-bidder auction setting where the seller observes only a binary signal about bidders’ valuations. Focusing on three canonical signal types—aggregate demand (reflecting overall valuation levels), relative strength (indicating which bidder is stronger), and anonymized dispersion (capturing competition intensity)—the authors derive optimal auction mechanisms under symmetry and monotonicity constraints through joint design of allocation rules and information structures. Their analysis provides the first systematic comparison among these signal types, showing that, under standard regularity conditions, the competition-based signal strictly dominates both demand and ranking signals in terms of achievable revenue. Moreover, within the class of monotone allocation rules, this signal outperforms any arbitrary binary signal. These findings offer both theoretical foundations and practical guidance for auction design under severe informational constraints.

Abstract

Consider a revenue-maximizing seller who can access a binary signal about two bidders` joint values. We explore what kind of information is most valuable to the seller by studying three classes of signals, each capturing a distinct dimension of bidders` values: their overall level (demand), their relative strength (ranking), and their dispersion while preserving bidder anonymity (competitiveness). We characterize the optimal signal and corresponding auction mechanism within each class, and find that competitiveness signals are particularly effective. Under certain regularity conditions, the optimal competitiveness signal yields at least as much revenue as any ranking signal or demand signal. Moreover, for signals that induce a monotone allocation, the optimal competitiveness signal yields at least as much revenue as any other binary signal.

Problem

• auction design
• information structure
• revenue maximization
• binary signal
• bidder valuation

Innovation

• auction design
• binary signal
• competitiveness signal
• revenue maximization
• information structure