Near-Optimal Mechanisms for Resource Allocation Without Monetary Transfers
Moise Blanchard, Patrick Jaillet

TL;DR
This paper investigates how a central planner can efficiently allocate resources over time without monetary transfers, achieving near-optimal utility with convergence rates depending on utility distribution properties and planning horizon.
Contribution
It introduces general tools and mechanisms for resource allocation without money, providing convergence rate analysis for various utility distributions and horizons.
Findings
Convergence rates range from 1/√T to 1/T in finite horizon settings.
Faster convergence rates are achieved with smooth utility distributions.
Exponential convergence is possible in infinite-horizon scenarios as agents become more patient.
Abstract
We study the problem in which a central planner sequentially allocates a single resource to multiple strategic agents using their utility reports at each round, but without using any monetary transfers. We consider general agent utility distributions and two standard settings: a finite horizon and an infinite horizon with discounts. We provide general tools to characterize the convergence rate between the optimal mechanism for the central planner and the first-best allocation if true agent utilities were available. This heavily depends on the utility distributions, yielding rates anywhere between and for the finite-horizon setting, and rates faster than , including exponential rates for the infinite-horizon setting as agents are more patient . On the algorithmic side, we design mechanisms based on the promised-utility…
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Taxonomy
TopicsEconomic theories and models
