Evaluating MergerEnforcement1

CRESSE Panel Discussion:Identifying the Impact of Competition Policy

Luke M. Froeb†

† Owen School of Management, Vanderbilt

1-3 July 2016

1This version: 27 June, 2016 CRESSE Conference in Rhodes Greeceluke.froeb@vanderbilt.edu

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Acknowledgements: colleagues

Michael Doane, Competition Econ., LLC

Arturs Kalnins, Cornell University

Mike Shor, University of Conneticut

Steve Tenn, Bates-White

Steve Tschantz, Vanderbilt Mathematics

Greg Werden, US Dept of Justice

FTC and DOJ Economists and Attorneys

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Talk Outline

Question: How to measure effects of policy?Decision Analysis:

False Convictions?2000 Baby Food merger2000 Parking lot merger2005 Paris Hotel Cartel

False Acquittals?2011 Ice Cream Merger2013 Rental Cars2009 Hospitals

Enforcement R&D: How do we getacademics to do this?

Replication is crucial, but ...will journals publish?

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What should we measure?

Enforcement: number or revenue of “wins”

Political Legitimacy: is antitrust asubstitute for price regulation?Deterrence: under-deterrence vs.over-deterrence

compared to what?

Decision Errors:False convictionsFalse acquittals

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How do we measure Decision Errors?

Decision Errors:False convictions are hard to observe

Use failed challenges or small mergers

False acquittals (easier to observe)

ToolsNatural “experiments,” but ...Ironically, we need structural models to interpretthem

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2000 Heinz & Beech-nut ��������XXXXXXXXMerger

Market SharesFirms 2000 2003 2006

Gerber 73 80 81*Beech-nut 13 10 11

*Heinz (Del Monte after 2002) 11 7 4

*Merging Firm

Synergy ClaimHeinz’s new factory + Beech-Nut brands

vs. 3 → 2 Merger“Not a mistake,” Dagen & Richard (2006),“The Baby-Food Case Reconsidered”

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Gravity Choice Model: Parking Merger

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Structural Modeling

Models tell us:What matters: Location of demand, locationsof merging and non merging lots, travel costs,and capacity constraints.Why it matters: these factors determinestrength of substitution; mergers internalize this.How much it matters: compute price effectsof mergers, divestitures, efficiencies, capacityconstraints.

Concern: Does the model “fit” theindustry?

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1999 Central Parking & Allright ������XXXXXXMerger

(merger challenge → divest 74 lots in 18 cities)

Critique: divestitures in 16-block square“markets”

taxi-cab distance metric implies iso-distance“diamonds”

Critique: ignored effects of capacityconstraints:

non-merging constraints amplify, but...merging constraints attenuate, and...latter effect is much bigger than former

Froeb et al., “Mergers Among Parking Lots,”J. Econometrics

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2005 Paris Luxury Hotel Cartel

France’s Conseil de la Concurrence: :“Although the six hotels did not explicitly fixprices, . . ., they operated as a cartel thatexchanged confidential information which had theresult of keeping prices artificially high”

Info: occupancy, price (avg. revenue)

Justification: “to bring more people to the areaand to maximize hotel utilization”

Shared info → better forecasts → fewerpricing errors → higher occupancy

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60 80 100 120 140PRICE

500

1000

1500

2000

2500

3000

3500

PROFIT

TARGET PRICEOPTIMAL PRICE

Abbildung: Information Sharing Increases Price: Expected(solid line) and target (dashed line) profit functions,exaggerated variance

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60 80 100 120 140PRICE

500

1000

1500

2000

2500

3000

3500

PROFIT

OPTIMAL PRICETARGET PRICE

Abbildung: Information Sharing Decreases Price: Expected(solid line) and target (dashed line) profit functions,exaggerated variance

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Evidence from US Hotel MergersLike parking, another Rev. Mgt. industry

small MC; big Fixed Cost

But demand less certain

898 Hotel MergersDifference-In-Differences: (Pre- vs.Post-merger) vs. (In- vs. Out-of-market)

to remove merger effects not related tocompetition

Result: occupancy, price increasebut only in capacity constrained andhigh uncertainty markets

–Kalnins et al., “Can Mergers Increase Output?,”RAND

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Ice Cream Merger

With respect to a price increase by:Brand A Brand B Brand C Brand D

Brand A -1.67 0.08 0.13 0.03(0.06) (0.01) (0.02) (0.00)

Brand B 0.20 -1.76 0.16 0.03(0.02) (0.06) (0.03) (0.01)

Brand C 0.13 0.06 -1.61 0.02(0.02) (0.01) (0.06) (0.00)

Brand D 0.16 0.07 0.14 -1.90(0.03) (0.01) (0.02) (0.07)

Question: is super-premium a relevant market?What: Elasticity matrixWhy: measures lost competitionHow much: → merger-to-monopoly raisesprice by 5%.

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Ice Cream Merger (cont.)

Question: Tenn et al., Mergers when firmscompete using Price and Promotion, IJIO

Promotion makes demand more elasticPost-merger promotion goes down→ merger-to-monopoly raises price by 12%.

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Car Rental Mergers

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Car Rental Data

Abbildung: Ownership Concentration Varies by Market

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Hertz/Budget-Thrifty Merger Predictions

Abbildung: Merger Predicitons by Market

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2009 FTC’s Hospital MergerRetrospectives

Courts found BIG markets: made it difficultto block hospital mergers

→ lots of consummated hospital mergers tostudy

Methodology: D-I-D

Vita and Sacher (2001), Competitive Effectsof Not-for-Profit Hospital Mergers, JIE

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2009 FTC’s Findings

Courts found BIG markets: made it difficultto block hospital mergers

Mergers between not-for-profit hospitals canresult in substantial anticompetitive priceincreases

Mospital competition can be highly localized

Allows us to evaluate methodology forevaluating proposed mergers

Elzinga-Hogarty is not a good structuralindicator of hospital competition

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Rise of Bargaining Models

Between providers and payers

How do provider mergers create marketpower?

Big idea: payers create competition amongproviders by threatening to “steer” patients tohospitals with lower pricesMergers can eliminate this competition.

Bargaining theory: If merger makes payersmore eager to reach agreement (by makingthe alternative worse) then merger createsmarket power.

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Predicting hospital merger effects

Estimate Hospital Choice Model using“travel time” as a proxy for the “price” thatpatients “pay”

Hospitals’ bargaining power is measured bypatient’s willingness to pay (WTP) forinclusion into network, measured in minutesof travel time.

Estimate relationship between hospital WTPand negotiated prices (Price Model)

Use Price Model to simulate price effect ofproposed merger given predicted change inWTP.

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Example: Hospital 1 is worth 12.5 min.

(1)  Choice  

(2)  Travel  Time  (min)  

(3)  Pr  (hospital  chosen)  

(4)  =  (2)  ×  (3)  Expected  Travel  Time  

Hospital  1   10   0.6   6  

Hospital  2   20   0.3   6  

Hospital  3   30   0.1   3  

Total   1.0   10  

(1)  Choice  

(2)  Travel  Time  (min)  

(3)  Pr  (hospital  chosen)  

(4)  =  (2)  ×  (3)  Expected  Travel  Time  

Hospital  1   10   0.6   6  

Hospital  2   20   0.75   15  

Hospital  3   30   0.25   7.5  

Total   1.0   22.5  

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Two hospitals in Philadelphia

Draw Area

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Two hospitals in Philadelphia (cont)

Change in WTP of 14%

0   200000   400000   600000  

Thomas  Jefferson  

U  Penn  

Combined  

WTP  

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Conclusion: Enforcement R&D is aprocess

Follow up on decisions

Publish results

Replication

Debate

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