S TAPLES -O FFICE D EPOT : N ATURAL “E XPERIMENTS ” VS. T HEORETICAL M ODELS L UKE M. F ROEB V ANDERBILT U NIVERSITY 3 October, pm Vanderbilt Law

FTC Merger Enforcement Data , “Other Industries”

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

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 matters 2.Why it matters 3.How much it matters 12

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 13

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 14

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

17 FTC 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.

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 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 level 1.None, 2.display, 3.feature, 4.both

21 FTC Table 4: Elasticity Varies with Promotion Own-price

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 22 Vanderbilt

Estimation Bias vs. Extrapolation Bias 23 Vanderbilt B,C merge Merger to monopoly

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?