Distributionally Robust Optimal Allocation with Costly Verification

Allocation with Costly Verification under Ambiguity In “Distributionally Robust Optimal Allocation with Costly Verification,” Bayrak, Koçyiğit, Kuhn, and Pınar examine the mechanism design problem faced by a principal allocating a single good to one of several agents with costly verification and without monetary transfers, adopting a distributionally robust optimization perspective. Each agent desires the good and generates value for the principal, who does not initially know these values but can verify them at a cost. This problem arises in various scenarios, such as a venture capitalist selecting a start-up for funding or a procurement manager choosing a supplier. Many such allocation problems occur infrequently, leaving the principal with limited knowledge about the distribution of the agents’ values. The authors model these allocation problems as distributionally robust mechanism design problems, explicitly addressing distributional ambiguity. They introduce the first robustly (and Pareto-robustly) optimal mechanisms in the literature. These mechanisms are not only robust but also simple and interpretable.

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Publication Details

Journal
Operations Research
Published
2025-02-28
DOI
https://doi.org/10.1287/opre.2022.0662
Primary Topic
Risk and Portfolio Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Distributionally Robust Optimal Allocation with Costly Verification

Mustafa Ç. Pı̆nar, Daniel Kühn, Halil İ. Bayrak, Çağıl Koçyiğit
Operations Research
Risk and Portfolio Optimization
article

Distributionally Robust Optimal Allocation with Costly Verification

Mustafa Ç. Pı̆nar, Daniel Kühn, Halil İ. Bayrak, Çağıl Koçyiğit
article en

Abstract

Allocation with Costly Verification under Ambiguity In “Distributionally Robust Optimal Allocation with Costly Verification,” Bayrak, Koçyiğit, Kuhn, and Pınar examine the mechanism design problem faced by a principal allocating a single good to one of several agents with costly verification and without monetary transfers, adopting a distributionally robust optimization perspective. Each agent desires the good and generates value for the principal, who does not initially know these values but can verify them at a cost. This problem arises in various scenarios, such as a venture capitalist selecting a start-up for funding or a procurement manager choosing a supplier. Many such allocation problems occur infrequently, leaving the principal with limited knowledge about the distribution of the agents’ values. The authors model these allocation problems as distributionally robust mechanism design problems, explicitly addressing distributional ambiguity. They introduce the first robustly (and Pareto-robustly) optimal mechanisms in the literature. These mechanisms are not only robust but also simple and interpretable.

Operations ResearchVol. 73(6)
Bilkent University (TR), University of Luxembourg (LU), École Polytechnique Fédérale de Lausanne (CH)
Openalex Percentile: Top 96%
Risk and Portfolio Optimization
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