On the Optimal Fixed-Price Mechanism in Bilateral Trade

TL;DR

This paper analyzes fixed-price mechanisms in bilateral trade, improving approximation ratios for social welfare maximization under various information settings, including full prior, mean-only, and sample-based information.

Contribution

It establishes new upper and lower bounds for fixed-price mechanisms' approximation ratios, showing they can achieve near-optimal welfare with limited information.

Findings

Optimal fixed-price mechanism achieves at least 0.72 of optimal welfare with full prior information.

No fixed-price mechanism can surpass approximately 0.7381 of optimal welfare.

With only mean information, fixed-price mechanisms can attain 2/3 of the optimal welfare, which is optimal in that setting.

Abstract

We study the problem of social welfare maximization in bilateral trade, where two agents, a buyer and a seller, trade an indivisible item. We consider arguably the simplest form of mechanisms -- the fixed-price mechanisms, where the designer offers trade at a fixed price to the seller and buyer. Besides the simple form, fixed-price mechanisms are also the only DSIC and budget balanced mechanisms in bilateral trade. We obtain improved approximation ratios of fixed-price mechanisms in different settings. In the full prior information setting where the designer has access to the value distributions of both the seller and buyer, we show that the optimal fixed-price mechanism can achieve at least $0.72$ of the optimal welfare, and no fixed-price mechanism can achieve more than $0.7381$ of the optimal welfare. Prior to our result the state of the art approximation ratio was $1 - 1/e + 0.0001 \approx 0.632$. Interestingly, we further show that the optimal approximation ratio achievable with full prior information is identical to the optimal approximation ratio obtainable with only one-sided prior information. We further consider two limited information settings. In the first one, the designer is only given the mean of the buyer's (or the seller's) value. We show that with such minimal information, one can already design a fixed-price mechanism that achieves $2/3$ of the optimal social welfare, which surpasses the previous state of the art ratio even when the designer has access to the full prior information. Furthermore, $2/3$ is the optimal attainable ratio in this setting. In the second one, we assume that the designer has sample access to the value distributions. We propose a new family mechanisms called order statistic mechanisms and provide a complete characterization of their approximation ratios for any fixed number of samples.