algorithmic game theory

Tighter Bounds for the Random-Offerer Mechanism in Bilateral Trade

arXiv:2607.13959

summary

The paper establishes tighter lower and upper bounds on the efficiency of the random-offerer mechanism for bilateral trade, improving the known approximation ratio to about 0.318 for the lower bound and to 0.460 for the upper bound.

Abstract

The random-offerer mechanism for bilateral trade selects the seller or the buyer uniformly and lets the selected agent make a profit-maximizing take-it-or-leave-it offer. Let be the infimum, over independent value distributions, of the mechanism's gains from trade divided by first-best gains from trade. We prove . For the lower bound, we improve the previous guarantee from approximately to . The proof uses a parameterized Lagrangian bound for pointwise-monotone allocations. At multiplier one, this bound has coefficient , and the Lagrangian separates into two terms controlled by the optimal seller-offering and buyer-offering profits. For the upper bound, we construct an explicit family consisting of a truncated equal-revenue buyer and a seller distribution with a tilted power-law lower tail and a constant-virtual-cost segment. The family satisfies , improving the previous explicit ratio ; rigorous interval arithmetic certifies the numerical inequality.

27 pages, 1 table

Topics & keywords

#bilateral trade#mechanism design#random-offerer#approximation bounds#incentive compatibility#distributional analysisrandom-offerer mechanismgains from tradefirst-bestLagrangian boundpointwise-monotone allocationtruncated equal-revenue distributionpower-law tailinterval arithmetic
Tighter Bounds for the Random-Offerer Mechanism in Bilateral Trade · wovepaper