Inefficient Offers to an Agency Subject to Judicial Review: an econometric test of remedy agreement in EC merger regulation Luke Garrod Bruce Lyons Andrei Medvedev

Bargaining theory suggests mutually beneficial early agreement If both parties are rational and have complete information, mutually beneficial agreement will… Definitely be reached and Be reached immediately Incomplete information can explain some delay… Screening for other’s type Signalling of own type Evidence from… Experiments Labour bargaining EC remedy agreements involve… Bargaining strategy from firms More passive competition agency

Merger remedies are agreements over the line between good and harmful parts of a merger ECMR allows merger unless it impedes competition Firms self-select mergers to avoid proposals that would certainly fail this test Nearly all merger proposals either cannot be shown to impede competition or can be modified to this effect Agency (DG Competition) has power to either Prohibit merger or Accept an offer to remedy harmful parts of merger (e.g. divestment) Cannot make counter-offers

The institutions of EC remedy agreement provide a natural experiment to test theory of strategic offers Two parties Competition agency and merging firms Discrete ‘rounds’ (2-phase investigation) More information gathered in second round Allows early or late agreement (or no agreement) Legally specified… Time limits to each phase (i.e. limited evidence gathering) Order of who can make offers and who can accept/reject Administrative system with judicial review Agency decision must be based on evidence No signalling in offers – would not stand up to JR Strategic behaviour only on one side Isolates strategy of firms – agency more passive

29% of remedies accepted only after delay 7% qualifying mergers are remedied As opposed to either no competition problem (89%) or withdrawn during proceedings (3%) or complete prohibition (0.6%) Given remedies are agreed (in either Phase I or Phase II)… …Probability of Phase I = 71% ( )

1998 ECMR revision formalised Phase I remedies; modest upward trend in early agreement

The EC procedure lends itself to simple modelling: assumptions Timing of moves Phase I remedy offer α O (firms)  accept or Phase II (agency)  Phase II remedy offer α OO (firms)  accept or prohibit (agency) Representation of remedies where higher α T means more of merger is OK Information Common knowledge of variance of agency’s evidence: uniform with range 2σ ; but only firms know α T Agency More evidence in Phase II: σ 2 < σ 1 Evidence supports agency estimates: JR-robust decision rule: accept Phase I offer iff: α O < α 1 (or α OO < α 2 ) Objective of merging firms

Phase I approval probabilities and expected decision errors are directly related Probability of approval If offer accepted in Phase I Type 1 error (too much remedy) if α O < α T Type 2 error (too little remedy) if α O > α T

Optimal offers and consequent probability of delayed agreement are determined by same factors Offers depend on whether firms find it optimal to make ‘for sure’ acceptable offer or risk disagreement 3 ranges depending on whether play completely safe in both phases, or only in Phase I, or to risk Phase II prohibition Example of intermediate case: Optimal offer and Type of error if agreement in Phase I Probability of failure to agree in Phase I  Same factors determine: (1) optimal offers; (2) type of error in Ph.I approvals; and (3) probability of failure to agree in Ph.I

Empirical predictions from the model Delay to Phase II more likely if Complex or imprecise merger appraisal (high σ 1 ) High number of markets raising concern Inexperienced agency (few previous cases) Vertical issues, coordinated effects, entry barriers, …? Delay is relatively less costly to the firms (K/π) Large proportion of markets raising concern Model does not predict any effect of Obvious harm of the merger (α T ) Combined market shares; rival shares Political impact Merger size per se Nationality of merging parties

Data Sample EU remedied mergers N = 133 i.e. all remedied mergers except 27 due to lack of reported data or predominantly vertical Unit = merger Aggregated from many markets per merger Mean 13; max 142 Variables expressed as: Market count (e.g. 13 markets under review) Share of markets (e.g. 52% markets created ‘concern’) Average across markets (e.g. mean combined market share = 64%)

Treatment of potential reporting bias Different style of reports in Phase I and II Reporting of barriers to entry more likely in Phase II Selection of markets for which market shares are reported seems higher in Phase I To derive a consistent figure for markets under review, we applied a market share filter Only count markets for which combined market share >25% Consistent with EC ‘checklist’ filter Applying filter drops more Ph.I than Ph.II markets 25% supported by sensitivity analysis

The filter removes more markets in Phase I, thus supporting our worry of reporting bias

The market share filter mainly removes markets without concern

As predicted, Phase II mergers are more complex and have higher share of controversial markets VariablePhase IPhase II Markets Mkts with concern6.1 (53%) 10.5 (72%) High barriers2½ (25%) 8 (45%) Vertical concern12% mergers 28% mergers

Also as predicted, only negligible differences relating to size and mkt share VariablePhase IPhase II Combined revenue€40b€38b Combined mkt share59%63% Share of leading rival & concern 21%16% Share lead rival & no concern 25%27%

Probit regression results to look out for Delay if… Complexity of appraisal by agency many markets to appraise Lower opportunity cost of delay for forms high proportion of merger under scrutiny

dependent variable: Phase II = 1 (1)(2) coefficient (standard error) marginal effects coefficient (standard error) marginal effects constant (0.5391)(0.6900) number of markets (non-coordinated) ** ** (0.0070)(0.0069) number of markets (coordinated) (0.0713)(0.0716) coordinated effects† (0.6208)(0.6329) merger number * * (0.0001)(0.0002) % markets with concern1.4407*** *** (0.4333)(0.4354) US only† (0.4624)(0.4658) EEA and US† * * (0.3999)(0.4025) merged entity’s mean market share (0.0080) R-squared

Market Share Threshold 0%20%30% Dependent variable: phase II (1)(2)(1)(2)(1)(2) constant * (0.5013)(0.6654)(0.5226)(0.6808)(0.5763)(0.7582) number of markets (non-coordinated) *0.0093*0.0122* **0.0164** (0.0054)(0.0537)(0.0063) (0.0079)(0.0078) number of markets (coordinated) (0.0590)(0.0592)(0.0656)(0.0658)(0.0897)(0.0920) coordinated effects (0.6537)(0.6665)(0.6091)(0.6226)(0.6013)(0.6216) merger number * * * (0.0002) (0.0001) % markets with concern1.5903***1.5681***1.5057***1.4837***1.0795***1.1167** (0.4084)(0.4102)(0.4290)(0.4307)(0.4484)(0.4518) US only (0.4651)(0.4699)(0.4634)(0.4674)(0.4529)(0.4575) EEA and US * * * * * * (0.3970)(0.3991)(0.3973)(0.3997)(0.3914)(0.3950) merged entity’s mean market share (0.0080)(0.0079) R-squared

Conclusions Delay in reaching agreement arises when competition issues are complex and delay is costly to the firms Firms act strategically Not just greater potential harm merger (e.g. high shares) Remedies agreed in Phase I are likely to be Insufficient (Type 2 error) if competition issues are complex and/or much for the firms to fight for But too stringent (Type 1 errors) if competition issues are relatively straightforward and/or delay is costly to firms

Issues on which we would particularly welcome discussion Any improvements on this paper! Consistency of Ph.I and Ph.II reports as data sources E.g. our market share filter, reporting of entry barriers Appropriate econometric techniques for our dataset Including when we move to direct use of market data c150 mergers * ave.14 markets per merger = >2,000 obs.