STAPLES-OFFICE DEPOT:NATURAL “EXPERIMENTS” VS. THEORETICAL

MODELS

LUKE M. FROEBVANDERBILT UNIVERSITY

3 October, 20112pm Vanderbilt Law

FTC Merger Enforcement Data1996-2003, “Other Industries”

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Significant Competitors

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Enforced Closed

What’s Wrong w/Structural Presumptions?• Market delineation draws bright lines

even when there may be none– No bright line between “in” vs. “out”

• Market Shares may be poor proxies for competitive positions of firms

• Market shares and concentration may be poor predictors of merger effects

How do we know that market structure (concentration) matters?

• Concentration is obviously correlated with merger enforcement– Oil & supermarkets have lower thresholds

• Horizontal Merger Guidelines and judges demand more– Evidence of competitive effects

• How do we draw inference about the “but-for” world?

One answer:price-concentration regression

• Policy uses of price-concentration regression– Delineate antitrust markets in merger cases– Identify market power in monopolization cases– Estimate effects of mergers

• Staples-Office Depot merger was successfully challenged by FTC using price comparisons– Prices 7.5% higher in one-office superstore cities than in two-

office superstore cities– With a 15% estimated pass-through rate, would imply a 50%

mc reduction to offset merger effect.• Would you block merger based on these data?

What could go wrong?

• Experiment is “polluted,” i.e., something else accounts for results– Unobserved demand could increase price and increase

number of firms (spurious negative correlation)– Unobserved costs could increase price and decrease

number of firms (spurious positive correlation)– Example: movie tickets (Davis, 2005)

• Measure of concentration: competitor >.5 mile away• Finding: Price is $0.90 higher with nearby competitor

• How does this manifest in Staples case?

What could go wrong? (cont.)

• Experiment might be bad metaphor for merger– Merger changes ownership concentration– Are changes in entry/exit across cities are good

metaphor for changes in ownership concentration?

• However: “some number beats no number”– “possibilities” are not enough to defeat analysis– Need alternative “positive” story

Natural Experiments are “Empirical” Models

• Compare control vs. treatment group

• Try to hold everything else constant– Backcast is the “control” group

Merger Retrospective:Marathon/Ashland Joint Venture• Combination of marketing and refining assets

of two major refiners in Midwest• First of recent wave of petroleum mergers

– January 1998• Not Challenged by Antitrust Agencies• Change in concentration from combination of

assets less than subsequent mergers that were modified by FTC

Merger Retrospective (cont.):Marathon/Ashland Joint Venture• Examine pricing in a region with a large change in

concentration– Change in HHI of about 800, to 2260

• Isolated region– uses Reformulated Gas– Difficulty of arbitrage makes price effect possible

• Prices did NOT increase relative to other regions using similar type of gasoline

Difference Between Louisville's Retail Price and Control Cities' Retail Price

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What else can we do?

• Use a theoretical model• how do firms compete and how does merger change

competition?• Price, quantity, capacity, bidding, bargaining competition

• Models as “blueprints” for enforcement: • blueprint governs the assembly of the facts• facts govern the selection of the blueprint.

• Model tells you: 1. What matters2. Why it matters3. How much it matters

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Example: Altivity-Graphic (2008):

• What matters: Nicholas Hill (DOJ) “Mergers w/capacity closure,”

• Elasticity of demand for CRB; elasticity of foreign supply; closing costs

• Why it matters: Mergers increase profitability of shutdown

• Altivity (35%) + Graphic (17%) of North American capacity

• How Much it matters:• Divest 2 plants representing 11% of capacity

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Model of Parking Merger

• 1999 Central Parking $585 million acquisition of Allright.

• Remedy: divestitures if merged share >35% in 4X4 block area is

• Divestitures in 17 cities

• Results– Capacity constraints on

merging lots attenuate merger effects

– By more than consraints on non merging lots amplify them

• Super-premium ice cream in North America– Nestlé 36.5% + Dreyer 19.5% revenue share

• Remedy: divest 3 brands to new entrant

FTC v. Nestlé and Dreyer (2002)

Models help delineate markets

• Question: Is super-premium a relevant product market?

• Answer: Simulate merger-to-monopoly of four super-premium ice cream producers

• If price goes up by 5% then it is a relevant product market

17FTC

Inputs to unilateral effects analysis: Own- and Cross-Elasticity Estimates

Tenn et al., “Mergers when firms compete using price and promotion,” Int’l. J. Ind. Org.

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)

Models help interpret data

• Question: did new entrant Dreyer obtain a 20% share without affecting incumbent price?– Does this mean that super-premium is not a

relevant antitrust market?• Answer: Build a model of post-merger world,

simulate exit (by raising Dreyer’s MC), and see what happens to price– Does incumbent pricing change?

Models help interpret data (continued)

• Question: How does promotional activity affect merger analysis and tools that economists use?– What happens if we ignore promotional activity?

• Answer: Build a model of promotion + price.– If promotion affects elasticity, then it matters; if

not then it doesn’t

Demand, prices, and promotion level1.None, 2.display, 3.feature, 4.both

•

21FTC

Table 4: Elasticity Varies with Promotion

• Own-price

NoPromotion

DisplayOnly

FeatureOnly

Feature & Display

Brand A -1.62 -1.87 -1.88 -2.29(0.07) (0.24) (0.15) (0.23)

Brand B -1.66 -1.96 -1.94 -2.30(0.06) (0.24) (0.15) (0.22)

Brand C -1.56 -1.80 -1.75 -2.24(0.07) (0.22) (0.14) (0.22)

Brand D -1.80 -2.31 -2.19 -2.70(0.08) (0.28) (0.18) (0.25)

Answer: promotion matters in this case

• Price-only merger models under-predict (5% instead of 12%) the price effects of mergers in industries where firms compete using price and promotion– Estimation bias: demand is too elastic– Extrapolation bias: promotion decreases 31%

in post-merger equilibrium

22Vanderbilt

Estimation Bias vs. Extrapolation Bias

23Vanderbilt

Control for Promotions in: % Change Price % Change QuantityDemand

Estimation?Merger

Simulation? Brand A Brand B Brand C Brand DCategory

Index Brand A Brand B Brand C Brand DCategory

IndexYes Yes 10.3% 19.9% 9.4% 17.0% 11.7% -13.3% -26.9% -11.9% -24.4% -15.3%Yes No 8.9% 16.2% 8.1% 14.5% 10.0% -11.5% -21.6% -10.1% -20.6% -12.9%No No 4.4% 7.8% 4.1% 7.2% 4.9% -9.3% -15.6% -8.2% -16.0% -10.1%

• B,C merge

• Merger to monopoly

Control for Promotions in: % Change Price % Change QuantityDemand

Estimation?Merger

Simulation? Brand A Brand B Brand C Brand DCategory

Index Brand A Brand B Brand C Brand DCategory

IndexYes Yes 0.1% 8.1% 2.4% -0.1% 2.2% 0.7% -13.5% -3.4% 1.2% -3.0%Yes No 0.1% 6.3% 2.0% 0.0% 1.8% 0.5% -10.0% -2.8% 0.7% -2.3%No No 0.0% 3.3% 1.1% 0.0% 0.9% 0.4% -7.4% -2.4% 0.5% -1.9%

Conclusion

• Natural experiments change focus of investigation/litigation– Did we hold everything else constant?– Is the experiment a good metaphor for merger?

• Models change focus of investigation/litigation– How well does the model explain the pre-merger

observed world?– Do the model assumptions bias its predictions for

the unobserved post-merger world?