Efficient Division When Preferences are Private: Using the Expected Externality Mechanism

31 Pages Posted: 12 Apr 2019

See all articles by Christina Aperjis

Christina Aperjis

Hewlett-Packard Enterprise - Social Computing Lab

Maciej H. Kotowski

Harvard University - Harvard Kennedy School (HKS)

Richard J. Zeckhauser

Harvard University - Harvard Kennedy School (HKS); National Bureau of Economic Research (NBER)

Date Written: April 1, 2019

Abstract

We study the problem of allocating multiple items to two agents whose cardinal preferences are private information. If money is available, Bayesian incentive compatibility and ex-ante Pareto efficiency can be achieved using the Expected Externality Mechanism (EEM). Absent money, under certain reasonable conditions, Bayesian incentive compatibility and ex-post Pareto efficiency remain achievable with a modified EEM that uses one good as a numeraire in lieu of money. We study this modified EEM’s properties and compare it with other allocation procedures.

Keywords: Expected Externality Mechanism, Object Allocation, Fair Division

JEL Classification: D82

Suggested Citation

Aperjis, Christina and Kotowski, Maciej H. and Zeckhauser, Richard J., Efficient Division When Preferences are Private: Using the Expected Externality Mechanism (April 1, 2019). HKS Working Paper No. RWP19-014. Available at SSRN: https://ssrn.com/abstract=3370394 or http://dx.doi.org/10.2139/ssrn.3370394

Christina Aperjis

Hewlett-Packard Enterprise - Social Computing Lab ( email )

1501 Page Mill Road
Palo Alto, CA 9434
United States

Maciej H. Kotowski (Contact Author)

Harvard University - Harvard Kennedy School (HKS) ( email )

79 John F. Kennedy Street
Cambridge, MA 02138
United States

Richard J. Zeckhauser

Harvard University - Harvard Kennedy School (HKS) ( email )

79 John F. Kennedy Street
Cambridge, MA 02138
United States
617-495-1174 (Phone)
617-384-9340 (Fax)

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States
617-495-1174 (Phone)
617-496-3783 (Fax)

Register to save articles to
your library

Register

Paper statistics

Downloads
17
Abstract Views
139
PlumX Metrics