Making Collusion Hard: Asymmetric Information as a Counter-Corruption Measure

51 Pages Posted: 6 Jun 2014

See all articles by Juan Ortner

Juan Ortner

Boston University

Sylvain Chassang

New York University (NYU) - Department of Economics

Date Written: May 31, 2014


We study the problem of a principal who relies on the reports of a monitor to provide incentives to an agent. We allow for collusion, so that the agent and monitor can side-contract on what report to send. We show that the principal can benefit from creating endogenous asymmetric information between the agent and the monitor, thereby making side-contracting more difficult. Specifically, it may be optimal to randomize the incentives given to the monitor, and let the magnitude of her incentives serve as her private information vis a vis the agent.

Plausible numerical computations in simple environments suggest that the potential efficiency gains from random incentives can be large. However, in general, the optimality of random incentives will depend on patterns of pre-existing asymmetric information: it is not always effective to add new sources of asymmetric information. We solve for both the Bayesian and max-min optimal policies, as well as provide an experiment-ready framework for prior-free policy evaluation. We show that even though monitors' reports do not provide a reliable measure of actual corruption, it is possible to evaluate local policy changes using only unverified report data.

Keywords: corruption, monitoring, collusion, endogenous asymmetric information, random incentives, bargaining failure, prior-free policy evaluation, structural experiment design

Suggested Citation

Ortner, Juan and Chassang, Sylvain, Making Collusion Hard: Asymmetric Information as a Counter-Corruption Measure (May 31, 2014). Princeton University William S. Dietrich II Economic Theory Center Research Paper No. 064-2014, Available at SSRN: or

Juan Ortner

Boston University ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States

Sylvain Chassang (Contact Author)

New York University (NYU) - Department of Economics ( email )

19 West 4th Street
New York, NY 10012
United States

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

Paper statistics

Abstract Views
PlumX Metrics