The estimation of cartel overcharges lies at the heart of antitrust policy on cartel prosecution as it constitutes a key element in the determination of fines. Connor and Lande (2008) conducted a survey of cartels and found a mean overcharge estimate in the range of 31% to 49%. By examining more sources, Connor (2010) finds a mean of 50.4% for successful cartels. However, the data used in those studies are estimates obtained from different methodologies, sources and contexts rather than from direct observations. Therefore, these data are subject to model error, estimation error, endogeneity bias, and publication bias. An examination of the Connor database reveals that the universe of overcharge estimate is asymmetric, heterogenous and contains a number of influential observations. Beside the fact that overcharge estimates are potentially biased, fitting a linear regression model to the data without providing a carefull treatment of the problems raised above may produce distorted results. We conduct a meta-analysis of cartel overcharge estimates in the spirit of Connor and Bolotova (2006) while providing a sound treatment of these matters. We find bias-corrected mean and median overcharge estimates of 15.47% and 16.01%. Clearly, our results have significant antitrust policy implications.
Antitrust; Cartel overcharges; Heckman; Heckit; Kullback-Leibler divergence; Meta-analysis;
TSE Working Paper, n. 14-462, January 31, 2014, revised July 2015