Counterbalancing Learning and Strategic Incentives in Allocation Markets

TL;DR

This paper analyzes how strategic agents and herding behavior impact allocation efficiency in markets with scarce objects, proposing batching mechanisms to improve incentives and reduce waste, with applications to organ allocation.

Contribution

It introduces incentive-compatible batching mechanisms that mitigate herding and improve efficiency in allocation markets with strategic agents.

Findings

Herding causes inefficiency and waste in sequential allocation.

Batching mechanisms can incentivize truthful reporting and improve allocation efficiency.

Adaptive batching reduces wastage in organ allocation by addressing herding behavior.

Abstract

This paper considers the problem of offering a scarce object with a common unobserved quality to strategic agents in a priority queue. Each agent has a private signal over the quality of the object and observes the decisions made by other agents. We first show that, under the widely-used first-come-first-served sequential offering mechanism, herding behavior emerges: initial rejections create an information cascade resulting in inefficient waste. To address this issue, we then introduce a class of batching mechanisms. Agents in each batch report whether they would be willing to accept or reject the object based on their private signals and prior information. If the majority opts to accept, the object is randomly allocated within that batch. We prove that suitable batching mechanisms are incentive-compatible and improve efficiency. A key property of the mechanism is the gradual increase of the batch size after each failed allocation; the size is chosen so that it elicits as much information as possible without distorting the incentives of agents to report truthfully. Additionally, from a healthcare policy perspective, our results can shed light on the large wastage in organ allocation. In particular, wastage that arises due to herding may be reduced by applying adaptive simultaneous offering mechanisms.