Data on merger and procedural characteristics were collected from the case reports of the Commission. Secondly, internet news archives were scoured through in order to find relevant information for the analysed cases. These included merging parties’ expectations regarding the financial effects of their merger and the valuation of the merger transaction (more detailed explanation of data collection methods can be found under the introduction of each of the individual variables). The sources used for this latter part of the data: (1) Merging parties' annual reports: the relevant information (pre-merger synergy expectations) was found in the report of the year of the merger announcement. (2) Company press releases: these short informational articles are a brief and prompt signalling means. They are normally available on the merging parties' websites or in their online archives. (3) Business-and-law search engines such as Lexis–Nexis. (4) Google news archives were used to double-check the information acquired through the first three steps, or if the annual report was not detailed enough or simply because there was no annual report available. To eliminate any measurement error, the data was only used if there were at least three different news sources reporting the same figure, around the same time.The ESRC Centre for Competition Policy (CCP) at the University of East Anglia (UEA) undertakes interdisciplinary research into competition policy and regulation that has real-world policy relevance without compromising academic rigour. It prides itself on the interdisciplinary nature of the research and the members are drawn from a range of disciplines, including economics, law, business and political science. The Centre was established in September 2004, building on the pre-existing Centre for Competition and Regulation (CCR), with a grant from the ESRC (Economic and Social Research Council). It currently boasts a total of 26 faculty members (including the Director and a Political Science Mentor), 4 full- and part-time researchers and 23 PhD students.
Text analysis