Can Market Participants Report Their Preferences Accurately (Enough)?

Eric Budish () and Judd B. Kessler ()
Additional contact information
Eric Budish: Booth School of Business, University of Chicago, Chicago, Illinois 60637
Judd B. Kessler: The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104

Management Science, 2022, vol. 68, issue 2, 1107-1130

Abstract: In mechanism design theory it is common to assume that agents can perfectly report their preferences, even in complex settings in which this assumption strains reality. We experimentally test whether real market participants can report their real preferences for course schedules “accurately enough” for a novel course allocation mechanism, approximate competitive equilibrium from equal incomes (A-CEEI), to realize its theoretical benefits. To use market participants’ real preferences (i.e., rather than artificial “induced preferences” as is typical in market design experiments), we develop a new experimental method. Our method, the “elicited preferences” approach, generates preference data from subjects through a series of binary choices. These binary choices reveal that subjects prefer their schedules constructed under A-CEEI to their schedules constructed under the incumbent mechanism, a bidding points auction, and that A-CEEI reduces envy, suggesting subjects are able to report their preferences accurately enough to realize the efficiency and fairness benefits of A-CEEI. However, preference-reporting mistakes do meaningfully harm mechanism performance. One identifiable pattern of mistakes was that subjects had relatively more difficulty reporting cardinal as opposed to ordinal preference information. The experiment helped to persuade the Wharton School to adopt the new mechanism and helped guide aspects of its practical implementation, especially around preference reporting.

Keywords: market design; experiments; matching theory; course allocation; preference elicitation; combinatorial assignment; combinatorial allocation (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.2020.3937 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:68:y:2022:i:2:p:1107-1130

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().