How Far Can Screens Go in Distinguishing Explicit from Tacit Collusion? New Evidence from the Libor Setting
Rosa M. Abrantes-Metz
Global Economics Group, LLC; New York University - Leonard N. Stern School of Business - Department of Economics
Albert D. Metz
Moody's Investors Service
March 13, 2012
CPI Antitrust Chronicle, Vol. 1, March 2012
Recently, large-scale investigations have been launched around the world on allegations of possible collusion and manipulation of the London Interbank Offered Rate (“Libor”). These investigations followed empirical research that highlighted anomalous patterns in the Libor data. The Libor is determined from sealed daily quotes submitted by sixteen member banks. Empirical research has shown that for a period of nearly a year, the Libor was essentially constant. This is the first anomaly. The second anomaly, which is less well understood, is the virtual unanimity of individual quotes submitted by the member banks. These anomalies lead us to ask whether coordination of some type may have been involved.
While screens can highlight such anomalous patterns, it is unclear whether they can differentiate between the various possible causes of those patterns. In principle, this unanimity in quotes across banks could simply reflect a non-cooperative outcome, or it could be the result of collusion. But whether that collusion was explicit, or a form of tacit or strategic collusion, is not immediately obvious.
Though distinguishing explicit from tacit collusion may be very difficult through screening, this is the challenge we take up in this article. We explore, in the context of the Libor, whether screens can move one step further and distinguish illegal (explicit) from legal (tacit) collusion. While we have always argued that a purely empirical analysis of market outcomes can never be the final proof of illegal behavior, under particular circumstances screens can indeed provide additional evidence to assess the more likely form of collusion.
Number of Pages in PDF File: 9
Keywords: Libor, collusion, manipulation, screening, detection
JEL Classification: C10, C22, G14, G24, K20
Date posted: March 13, 2012
© 2015 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo3 in 0.484 seconds