We model the design of a benchmark fixing as an estimator of fair market value. The fixing data are the transactions of agents whose profits depend on the fixing, implying incentives for manipulation. We derive the optimal linear fixing under an assumption that transaction weights are unidimensional. We also axiomatically characterize the unique linear fixing that is robust to a certain form of collusion among traders. Our analysis provides a foundation for the commonly used volume-weighted average price (VWAP) and its analogue based on unidimensional weights. We characterize the relative advantages of these fixing designs, depending on market characteristics.

We propose a price-theoretic approach to Bayesian persuasion by establishing an analogy between the sender’s problem and finding Walrasian equilibria of a persuasion economy. The sender, who acts as a consumer, purchases posterior beliefs at their prices using the prior distribution as her endowment. A single firm has the technology to garble the state. Welfare theorems provide a verification tool for optimality of a persuasion scheme and characterize the structure of prices that support the optimal solution. This approach yields a tractable solution method for persuasion problems in which the sender’s utility depends only on the expected state.

We characterize the role of benchmarks in price transparency of over‐the‐counter markets. A benchmark can raise social surplus by increasing the volume of beneficial trade, facilitating more efficient matching between dealers and customers, and reducing search costs. Although the market transparency promoted by benchmarks reduces dealers' profit margins, dealers may nonetheless introduce a benchmark to encourage greater market participation by investors. Low‐cost dealers may also introduce a benchmark to increase their market share relative to high‐cost dealers. We construct a revelation mechanism that maximizes welfare subject to search frictions, and show conditions under which it coincides with announcing the benchmark.

Policymakers frequently use price regulations as a response to inequality in the markets they control. In this paper, we examine the optimal structure of such policies from the perspective of mechanism design. We study a buyer‐seller market in which agents have private information about both their valuations for an indivisible object and their marginal utilities for money. The planner seeks a mechanism that maximizes agents' total utilities, subject to incentive and market‐clearing constraints. We uncover the constrained Pareto frontier by identifying the optimal trade‐off between allocative efficiency and redistribution. We find that competitive‐equilibrium allocation is not always optimal. Instead, when there is inequality across sides of the market, the optimal design uses a tax‐like mechanism, introducing a wedge between the buyer and seller prices, and redistributing the resulting surplus to the poorer side of the market via lump‐sum payments. When there is significant same‐side inequality that can be uncovered by market behavior, it may be optimal to impose price controls even though doing so induces rationing.

Many scarce public resources are allocated at below-market-clearing prices and sometimes for free. Such “nonmarket” mechanisms sacrifice some surplus, yet they can potentially improve equity. We develop a model of mechanism design with redistributive concerns. Agents are characterized by a privately observed willingness to pay for quality, a publicly observed label, and a social welfare weight. A market designer controls allocation and pricing of a set of objects of heterogeneous quality and maximizes the expectation of a welfare function. The designer does not directly observe individuals’ social welfare weights. We derive structural insights about the form of the optimal mechanism, leading to a framework for determining how and when to use nonmarket mechanisms.