Robust Contracting for Sequential Search

2025-04-24

AI Summary

This paper studies how a principal, aware of only one alternative project, designs a robustly optimal sequential search contract to prevent premature termination by an agent. Method: Under a worst-case evaluation framework—where the principal assesses contracts based on their performance under the most adverse environment—the authors fully characterize the set of robustly optimal contracts. Contribution/Results: They establish that the minimal debt-threshold mechanism—paying the agent only when the search reward exceeds an endogenously determined threshold—is both necessary and central to incentive alignment. This mechanism unifies real-world contractual forms, including pure debt, debt-equity hybrids, and tiered contracts. The paper refutes the optimality of linear contracts, provides sufficient conditions under which various debt-based contracts constitute the unique equilibrium, and develops a verifiable, robust design principle for dynamic search settings.

Technology Category

• Multiagent Systems: Mechanism Design
• Search and Optimization: Mixed Discrete/Continuous Search
• Game Theory and Economic Paradigms: Mechanism Design

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Search and Retrieval-Augmented AI: Agentic search
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

A principal contracts with an agent who can sequentially search over projects to generate a prize. The principal knows only one of the agent's available projects and evaluates a contract by its worst-case performance. We characterize the set of robustly optimal contracts, all of which involve a minimum debt level, i.e., the agent only receives payment if the prize exceeds a certain threshold. This debt requirement is essential to prevent the agent from terminating the search too early. Our characterization encompasses several commonly observed contract formats, including pure debt, debt-plus-equity, and tranches. We also study situations where each of these contracts emerges as the unique prediction. In contrast to much of the existing robust contracting literature, linear contracts are strictly sub-optimal because they dampen the agent's search incentive.

Problem

• Characterizing robustly optimal contracts for sequential search
• Ensuring agent continues search via minimum debt requirement
• Demonstrating sub-optimality of linear contracts in search incentives

Innovation

• Contracts include minimum debt level requirement
• Encompasses debt, debt-plus-equity, and tranches
• Linear contracts are sub-optimal for search incentives