Zafeira Kastrinaki EC Competition Enforcement Data ACLE, 10-11 April, 2008 Amsterdam

1. Does EC balances efficiency gains against anti-competitive effects?A Preliminarily Empirical Evaluation Zafeira Kastrinaki EC Competition Enforcement Data ACLE,10-11 April, 2008 Amsterdam

2. Motivation In the past EC has received criticism for not making proper economic analysis, for example in 2002, the EC lost three merger cases in court: Airtours/ First Choice, Schneider/Legrand and TetraLaval/Sidel. In all three cases, the CFI strongly criticised the Commission’s economic analyses. The Commission has now formally stated that it will take account of substantiated efficiency claims that are merger-specific, verifiable, and beneficial to consumers In theory, this shift in attitude provides merging parties with an additional layer of arguments to overcome a presumption of adverse competitive effects created by high combined shares. Can such arguments also make a real difference in practice?

3. Research Objectives • Against this background, it seems worthwhile to evaluate whether the Commission have historically place an emphasis on economic factors such as anticompetitive effects or efficiency gains when investigating and prohibiting mergers • We also examine whether EC is forward looking is a sense of considering future merger when investigating a given merger case . The efficiency offence argument does not find any justification under a forward looking AA (Motta and Vasconcelos, 2005)

4. Earlier Literature • Lindsay et al. (2003) using a sample of 245 mergers for the period 1990–2002, the authors find that high market shares and barriers to entry are the main causes of prohibitions, while dummies indicating that the parties were incorporated in the USA or in a Nordic country have no significant effects • Bergman et al. (2005) using a random sample of 96 mergers for the period 1990-2002 find that the probability of a phase-2 investigation and of a prohibition of the merger increases with the parties’market shares. The probabilities increase also when the Commission finds high entry barriers or that the post-merger market structure is conducive to collusion Some additional empirical studies of EU’s merger regime • Roller and Neven (2002), Aktas et al. (2003),and Duso et al. (2003) analyze the relation between the Commission’s decisions and the movements of the share prices on the stock market

5. The Empirical Model (1) rate of phase I (1) rate of prohibitions (2) rate of clearance in phase II (3)

6. The Empirical Model (2): a proportional hazard model (4) Eq. 4 gives the hazard function or rate (or probability) of transition is a baseline hazard measuring the effect of time past It is assumed constant within pre-specified n groups However, it may differ across them is a vector of covariates is a parameter vector is a random variable (>0) which summarises the impact of unobservable firm specific effect that scales the no-frailty component with unit mean, finite variance

7. Definition of Explanatory Variables • Cumulative Abnormal Return of merging firm (CARm) which equals 1 if CARm>0 and 0 otherwise • Cumulative Abnormal Return of competitors (CARc) which equals 1 if CARc>0 and 0 otherwise • Efficiency gains of merging firms which equals to 1 if CARm>0 , CARc<0 and 0 otherwise ( eg. Banerjee and Eckard, 1998) • Expected change in the cumulative number of mergers in sector j in the interval [t, t+1], measured by {S(t+1)-S(t)} Where, S(t): Cumulative number of acquisitions in sector j up to and including time t However, there is a possibility that the merger announcement signals that a rival is more likely to become a merger target in which case the implied sign pattern would be the same as for the collusion or efficiency hypotheses, (McGuckin et al. 1992) Thus, Likely targets among rivals are not considered when above variables are calculated

8. Sampling and Data The sample consists of mergers examined by EC: • All phase II mergers over the period 1990-2007 • A randomly matched sample of phase I mergers over the period 1990-2007 Identity of merging firms and competitors is obtained from EC merger decisions However, due to difficulties in identifying necessary data the final sample consists of 880 firms: • 102 phase II cases (of which 15 prohibitions) • 123 phase I cases • 655 competitors Data are sourced from the Official Journal publications of the EC as well as Datastream database.

9. Abnormal Returns Estimation (an event study methodology) 1. Estimation of the market model: Ri,t =α+βRm,t+εi,t (5) where, Ri,t : firm i’s stock price at time t Rm,t: market index for the sector and country that firm i belongs to Over 180 trading days, starting from 30 days prior to the merger announcement day (Scholes-Williams (1977) method) 2.Firm i’s abnormal return around the announcement day t is calculated: (6) Under the null hypothesis of efficient markets, abnormal returns have zero mean and finite variance 3. Firm i’s cumulative average abnormal is then calculated: (7)

10. Results (1): Competing risks hazard estimation

11. Results (2): Competing risks hazard estimation

12. Concluding Remarks • EC seems to consider efficiency gains claimed by merging firms. However, there is no strong evidence in favour of EC balancing efficiency gains against anticompetitive effects • It seems that EC has a myopic behaviour as it does not consider expected mergers when it judges a given merger case • EC does not consider merging firms interests . However, rivals gains influence the decision process • These preliminarily results trigger a more detailed examination as regards the role of efficiency issues (for example, using more direct measures of efficiency gains) in merger control, especially after the 2004 reform