Optimal Dynamic Allocation: Simplicity through Information Design

72 Pages Posted: 2 Jul 2020 Last revised: 13 Mar 2023

See all articles by Itai Ashlagi

Itai Ashlagi

Stanford University - Department of Management Science & Engineering

Faidra Monachou

Harvard University

Afshin Nikzad

University of Southern California, Department of Economics

Date Written: February 15, 2020

Abstract

We study dynamic nonmonetary markets where objects are allocated to unit-demand agents with private types; such as in the allocation of public housing or deceased-donor organs. 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. The social planner's objective is a linear combination of allocative efficiency (i.e., the sum of values) and welfare (i.e., the sum of payoffs). We identify the optimal mechanism in the class of direct-revelation mechanisms that elicit agents’ types and assign them to objects over time. We show that, when the social planner can design the information disclosed to the agents about the objects, the optimal mechanism has a simple implementation: a first-come first-served waitlist with deferrals. In this implementation, the information disclosed about each object is an interval containing the object quality, rather than the exact quality. These intervals partition the quality space. We also show that when the planner's objective weight on welfare increases, these intervals become coarser, and optimal disclosure policies less informative. A direct corollary is that mechanisms that achieve higher welfare also induce lower distributional inequality, in terms of the Lorenz order.

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

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
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

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
1,005
Abstract Views
7,013
Rank
42,079
PlumX Metrics