Cartel dating

Abstract

The begin and end dates of cartels are often ambiguous, despite competition authorities stating them with precision. The legally established infringement period(s) from documentary evidence need not coincide with the period(s) of actual cartel effects. In this paper, we show that misdating cartel effects leads to a (weak) overestimation of but-for prices and an underestimation of overcharges. Total overcharges based on comparing but-for prices to actual prices are a (weak) underestimation of the true amount overcharged, irrespective of the type and size of the misdating. The bias in antitrust damage estimation based on predicted cartel prices can have either sign. We extend the before-during-and-after method with an empirical cartel dating procedure, which infers structural breaks of unknown number and dates that mark the actual begin and end dates of the collusive effects. Empirical findings in the European Sodium Chlorate cartel corroborate our theoretical results.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Algorithmic Pricing and Competition: Empirical Evidence from the German Retail Gasoline Market

“…This is an increase of about 9% relative to the average non-adopter margin of 7.9 cents. 47 Column (6) shows that the 25th percentile of margins increases by 0.9 cents after algorithmic adoption. Column (7) shows that the 75th percentile of margins remains the same for adopters and non-adopters.…”

“…We take the adoption date to be the average between the adoption date of E10 and the Diesel adoption date. Column (6) in each of Tables A14 and A15 present results using this definition of adoption. We find that the results are qualitatively and quantitatively the same as the baseline results at the station level.…”

“…Conditional on local demographic characteristics broadband quality should not depend on stationspecific unobservables, but stations should be more likely to adopt algorithmic pricing software once their local area has access to reliable high speed internet. 6 Using brand-adoption as an IV we find that mean station-level margins increase by 0.7 cents per litre, or roughly 9%, after adoption. 7 We observe heterogeneity in outcomes based on market structure.…”

Hub-and-Spoke Cartels: Theory and Evidence from the Grocery Industry

“…For this, we take advantage of our outlet-level panel to analyze price changes within and across markets during the 2009-2018 period, which includes both the last seven years of the coordination phase 20 The test was developed by Quandt (1960) and distributional properties were established by Andrews (1993). This test has been suggested and used in previous work involving collusive behaviour (see for instance Harrington (2008), Clark and Houde (2014), Boswijk, Bun, and Schinkel (2018), Crede (2019)). 21 We have redone our difference-in-differences analysis below using this alternative break timing and our results are comparable, although the average price decline is slightly larger.…”