Dynamic Decoupling in Multidimensional Screening

2025-12-29

AI Summary

This paper studies optimal contract design for a monopolist screening agents with multi-dimensional private information revealed sequentially: agents first report an initial type, and later realize valuations across multiple dimensions. Focusing on valuation distributions satisfying “invariant dependence”—where the initial signal does not alter the inter-dimensional coupling structure—we propose a *dynamic decoupling* mechanism. This mechanism extracts expected residual surplus ex ante, fully decomposing the multi-dimensional joint optimization into independent, dimension-wise optimal sequential screening problems. It fully recovers information rents, drastically reduces computational complexity, and yields the first analytically tractable characterization of the globally optimal mechanism. Our contribution lies in overcoming a fundamental bottleneck in traditional multi-dimensional dependence modeling, establishing a general-purpose simplification paradigm for high-dimensional mechanism design with temporally structured private information.

Technology Category

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

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Security and Privacy: Large-scale security measurements

Abstract

I study multidimensional sequential screening. A monopolist contracts with an agent endowed with private information about the distribution of their eventual valuations of different goods; a contract is written and the agent reports their initial private information before drawing and reporting their valuations. In these settings, the monopolist frontloads surplus extraction: Any information rents given to the agent to elicit their post-contractual valuations can be extracted in expectation before valuations are drawn. This significantly simplifies the multidimensional screening problem. If the agent's valuations satisfy invariant dependencies (valuations can be dependent across dimensions, but how valuations are coupled cannot vary in their initial private information), the optimal mechanism coincides with independently offering the optimal sequential screening mechanism for each good, regardless of the dependency structure.

Problem

• The paper studies multidimensional sequential screening with private information.
• It addresses surplus extraction before valuation draws in monopolist-agent contracts.
• It simplifies screening when valuations have invariant dependencies across dimensions.

Innovation

• Dynamic decoupling simplifies multidimensional screening
• Frontloading surplus extraction reduces information rents
• Invariant dependencies enable independent sequential mechanisms per good