Optimal Dynamic Allocation: Simplicity through Information Design

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Abstract/Contents

Abstract: We study dynamic nonmonetary markets where objects are allocated to unit-demand agents with private types. An agent’s value for an object is supermodular in her type and the quality of the object, and her payoff is quasilinear in her waiting cost. We identify the welfare-maximizing mechanism in the class of direct-revelation mechanisms that elicit agents’ types and assign them to objects over time. When the social planner can design the information disclosed to the agents about the objects, this mechanism can be implemented by a first-come first-served wait-list with deferrals. The optimal disclosure policy pools adjacent object types. Moreover, the hazard rate of the distribution of the agents' types determines the structure of the optimal disclosure policy, when the agents' utility function is separable. A single-peaked (single-dipped) hazard rate leads to the optimality of a lower censorship (upper censorship) policy.

Type of resource	text
Date created	August 18, 2021

DOI	https://doi.org/10.25740/jm546bh4382
Location	https://purl.stanford.edu/jm546bh4382

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License: This work is licensed under a Creative Commons Attribution 4.0 International license (CC BY).

Preferred citation: Ashlagi, I., Monachou, F., and Nikzad, A. (2022). Optimal Dynamic Allocation: Simplicity through Information Design. Stanford Digital Repository. Available at https://purl.stanford.edu/jm546bh4382

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