Designing Package Markets to Eliminate Exposure Risk

22 Pages Posted: 28 Apr 2012

See all articles by Jacob K. Goeree

Jacob K. Goeree

University of Zurich

Luke Lindsay

University of Exeter Business School - Department of Economics

Date Written: April 16, 2012


This paper reports results from a series of laboratory experiments designed to evaluate the impact of exposure risk on market performance. Exposure risk arises when there are complementarities between trades, e.g. when the purchase of a new house requires selling the old one. The continuous double auction (CDA), which has proven to be remarkably effective in a wide variety of settings, performs poorly in a treatment with high exposure risk: overall market efficiency is only 20% and there are many instances of no trade. In a parallel treatment with lower exposure risk, efficiency under the CDA is higher (55%) but is dominated, for instance, by a top-trading-cycles procedure that uses no money. The CDA's poor performance does not depend on whether house values are private information or common knowledge, indicating that exposure risk is due to strategic uncertainty not objective uncertainty about others' preferences. We introduce a simple package market and show that it effectively resolves exposure risk: efficiency levels are 82% and 89% respectively for the low and high exposure treatments. The proposed package market is a simple extension of the CDA and could potentially be applied in a variety contexts.

Keywords: exposure risk, package markets, market design, laboratory experiments

JEL Classification: C92

Suggested Citation

Goeree, Jacob K. and Lindsay, Luke, Designing Package Markets to Eliminate Exposure Risk (April 16, 2012). Available at SSRN: or

Jacob K. Goeree (Contact Author)

University of Zurich ( email )

Rämistrasse 71
Zürich, CH-8006


Luke Lindsay

University of Exeter Business School - Department of Economics ( email )

Streatham Court
Exeter, EX4 4RJ
United Kingdom


Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics