• Dorota Galeza

Student thesis: Phd


While the antitrust approaches of the EU and US seek to address similar concerns, they also exhibit material differences. This is surprising given that we might expect that an optimal approach to antitrust would prevail, with the EU and US learning from each other and becoming more similar over time. Looking at this more closely, the thesis looks at the issue of convergence and the reasons behind the persistence of differences across the two approaches. This shows that the issue remains underexplored in the literature, and that by drawing upon path dependence and path creation theory it is possible to advance an explanation for the two sets of practices. The EU and US approaches to antitrust are similar to the extent that they are federal in structure and are decentralised, yet they also differ, particularly in terms of their control of state regulation. Alongside this, they are seen as competing networks, with questions on issues such as requisite levels of structural and allocative efficiency and support for internationalisation being keenly debated. This turns out to be important as it conflates two issues. At one level, it reinforces the difference between the two networks, with the debate being about the identification and adoption of superior elements from either system. From a different perspective, the competition drives convergence since the adoption of superior elements should make the networks more similar. While the thesis does consider superior elements and how their adoption would improve antitrust practice, the main concern is with the latter – with why this has not made the networks more similar. The analysis shows why each network finds it difficult to learn from the other. Examples are provided on what can be considered more effective practice and the failure of the competing network to adopt that practice. Finding normative solutions is therefore insufficient of itself as it is necessary to understand the path dependence and path creation aspects of the antitrust networks, and how learning occurs in those networks, before better practice can migrate from one system to another. The thesis then posits that this has wider applicability and can therefore inform regulatory practice more generally.
Date of Award1 Aug 2019
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorDavid Williamson (Supervisor) & Liza Lovdahl Gormsen (Supervisor)

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