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Cartel Overcharges and Optimal Cartel Fines

16 Pages Posted: 16 Nov 2007 Last revised: 20 Nov 2007

Robert H. Lande

University of Baltimore - School of Law

John M. Connor

American Antitrust Institute (AAI)

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Date Written: November 12, 2007


This Article examines whether the current penalties in the United States Sentencing Guidelines are set at the appropriate levels to deter illegal price fixing cartels optimally. The authors analyze two data sets to determine how high on average cartels raise prices. The first consists of every published scholarly economic study of the effects of cartels on prices in individual cases. The second consists of every final verdict in a U.S. antitrust case in which a neutral finder of fact reported collusive overcharges. They report average overcharges of 49% and 31% for the two data sets, and median overcharges of 25% and 22%. They also report separate results for domestic cartels, international cartels, more recent cartels, and bid‑rigging.

The authors conclude that the current Sentencing Commission presumption that cartels overcharge on average by 10% is much too low, and that principles of optimal deterrence indicate that current levels of cartel penalties should be increased significantly. The Sentencing Commission should consider raising the presumption to 15% for domestic cartels and 25% for international cartels. Alternatively, if the policymakers decide this distinction is unwise, a 20% overall presumption would be appropriate. This is a conservative and modest proposal in light of this article's results.

Keywords: antitrust, cartel, deterrence, overcharges, price fixing, fines

JEL Classification: K21, K14, L41, L44, L65, L11, L13, N60

Suggested Citation

Lande, Robert H. and Connor, John M., Cartel Overcharges and Optimal Cartel Fines (November 12, 2007). Available at SSRN: or

Robert H. Lande

University of Baltimore - School of Law ( email )

1420 N. Charles Street
Baltimore, MD 21218
United States

John M. Connor (Contact Author)

American Antitrust Institute (AAI) ( email )

1730 Rhode Island Avenue, NW
Suite 1100
Washington, DC 20036
United States
202-536-3408 (Phone)


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