Does EC balances efficiency gains against anti-competitive effects?

A Preliminarily Empirical Evaluation

Zafeira Kastrinaki

EC Competition Enforcement DataACLE, 10-11 April, 2008

Amsterdam

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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?

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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)

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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 effectsBergman 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 regimeRoller 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

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The Empirical Model (1)

rate of phase I (1)

rate of prohibitions (2)

rate of clearance in phase II (3)

Notif. Date Phase I (z) Or Prohibition (p) Phase II (k) Cleared (d)

0

/lim z z z z

zt

P t T t t T th t

t

0

/lim

p p p p p p

kpt

P t T t t T th t

t

0

/lim d d d d d d

kd t

P t T t t T th t

t

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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

/ exp where n=z, p, dn on n nh t X h X n

onh

nX

n

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Definition of Explanatory VariablesCumulative Abnormal Return of merging firm (CARm) which equals 1 if CARm>0 and 0 otherwiseCumulative Abnormal Return of competitors (CARc) which equals 1 if CARc>0 and 0 otherwiseEfficiency 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

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Sampling and Data

The sample consists of mergers examined by EC: All phase II mergers over the period 1990-2007A 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 cases655 competitors

Data are sourced from the Official Journal publications of the EC as well as Datastream database.

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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)

5

5iCAR AR

, , , , ,ˆˆ ˆ

i t i t i t i t m tAR R R R R

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Results (1): Competing risks hazard estimation

Dependent Variable Risk of phase IRisk of clearance in

phase II Risk of prohibition

Independent Variables            

CARm -0.0172 (0.01) -0.0100 (0.02) -0.0037 (0.14)

CARc -0.2305 (3.6***) 0.3608 (3.79***) 0.4781 (4.24***)

Efficiency 0.1553 (1.03) 0.1319 (1.28*) -0.0770 (0.71)

Expected mergers 0.1553 (0.99) -0.1319 (1.03) -0.0770 (0.71)

Theta 1.2680 1.3920 0.9823

Likelihood-ratio test of theta=0 Χ2(1)=11.1 Χ2

(1)=22.57 Χ2(1)=8.91

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Results (2): Competing risks hazard estimation

Dependent Variable Risk of phase IRisk of clearance in

phase II Risk of prohibition

Independent Variables Time dummies

D7 0.3386 (1.16) 0.1192 (1.55*) 0.3618 (1.21)

D6 0.2930 (1.00) 0.0907 (1.32*) 0.3097 (1.03)

D5 0.7021 (2.20***) 0.1034 (2.48***) 0.6415 (2.24)

D4 0.3805 (1. 78**) 0.0655 (1.28*) 0.3385 (1.28*)

D3 0.7021 (1.02) 0.0648 (1.85**) 0.5715 (1.85**)

D2 0.0107 (0.72) 0.0243 (0.72) 0.2395 (0.72)

D1 0.0806 (1.26) 0.0407 (2.60***) 0.7872 (2.60***)

D0 0.0181 (1.66*) 0.0202 (1.71**) 0.5467 (1.71**)

D99 0.0873 (1.94**) -0.0527 (1.99**) 0.5959 (1.99**)

D98 -0.0327 (1.73**) -0.0305 (2.48***) -0.0055 (0.10)

D97 0.5497 (1.20) 0.0890 (1.16) 0.6262 (1.16)

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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