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EU Merger Policy after the 2004 Reform: More Economic Approach, Fewer Challenges

 |  July 24, 2017

Posted by Social Science Research Network

EU Merger Policy after the 2004 Reform: More Economic Approach, Fewer Challenges

By Federico Mini

Abstract:     I conduct an empirical analysis of European Commission’s decisions on horizontal mergers before and after the 2004 reform, which introduced a “more economic approach” to merger control. The new approach did not change the way the EC deals with mergers to monopoly or quasi-monopoly (almost always challenged) and mergers in very unconcentrated markets (almost never) — although the switch to the “significant impediment to effective competition” test resulted in more frequent challenges when the combined entity is not the firm with the largest market share. The reform changed EC’s stance toward mergers falling between quasi-monopoly and unconcentrated markets. The EC had been, on average, much tougher against these in-between mergers before the reform. Afterwards, the chance of a challenge to a merger with the same features — concentration levels and other objectively measurable characteristics — fell by double digits, often by 20% points or more. Post-reform, the observed probability of a challenge rises above a 50-50% chance only when the merged firm has a 70% market share or more. These results are obtained via a methodology that that builds on previous work relying on public data and extends it along three dimensions. First, the dataset consists of the complete public record on merger decisions, rather than a sample of them. Second, HHI and share variables included in the regression are free from the bias that would be present had they been based on the mid-point of the published market share ranges (shares are reported as ranges because of business secrecy concerns). Third, the study accounts for measurement error by giving more weight to observations corresponding to cases when the EC fully discloses market shares, or the measurement errors have smaller variance. For most regression specifications, accounting for the measurement error makes the results differ from those one would obtain ignoring it.

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