Optimal Dynamic Allocation: Simplicity through Information Design

49 Pages Posted: 2 Jul 2020 Last revised: 13 Feb 2021

See all articles by Itai Ashlagi

Itai Ashlagi

Stanford University - Department of Management Science & Engineering

Faidra Monachou

Stanford University, Department of Management Science & Engineering

Afshin Nikzad

University of Southern California, Department of Economics

Date Written: February 15, 2020

Abstract

We study mechanism design in 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 quasi-linear in her waiting cost. Social welfare is defined as the agents’ average payoff. We consider a general class of mechanisms that determine the joint distribution of the object assigned to each agent and the agent’s waiting time. We identify the welfare-maximizing mechanism and show that it can be implemented by a simple policy when the market maker can design the information disclosed about the objects: by a first-come, first-served waitlist that allows agents to accept or decline offers paired with an information disclosure scheme that pools adjacent object types. From a technical perspective, standard ironing techniques in mechanism design are not directly applicable, due to the concurrence of two complicating factors: the supermodularity of the agents’ values for objects and the capacity constraints of the heterogeneous object types. We take a different approach by characterizing the set of monotone, non-wasteful, and implementable interim allocation rules through a majorization condition, using the Bauer’s Maximum Principle [Bauer, 1958] to show that the optimal rule is an extreme point of this set, and then applying the extreme point characterization results of Kleiner et al. [2020].

JEL Classification: C78, D47

Suggested Citation

Ashlagi, Itai and Monachou, Faidra and Nikzad, Afshin, Optimal Dynamic Allocation: Simplicity through Information Design (February 15, 2020). Available at SSRN: https://ssrn.com/abstract=3610386 or http://dx.doi.org/10.2139/ssrn.3610386

Itai Ashlagi

Stanford University - Department of Management Science & Engineering ( email )

473 Via Ortega
Stanford, CA 94305-9025
United States

Faidra Monachou

Stanford University, Department of Management Science & Engineering ( email )

473 Via Ortega
Stanford, CA 94305-9025
United States

Afshin Nikzad (Contact Author)

University of Southern California, Department of Economics ( email )

Los Angeles, CA 90066
United States

HOME PAGE: http://afshin-nikzad.com

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