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Quantitative Benefit-cost Analysis of Mergers

Luke FroebOct. 26, 2001

Federal Trade Commission

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References mba.vanderbilt.edu/luke.froeb/papers/

Coauthors, Tschantz & Werden Simulating Merger Effects Among

Capacity-constrained Firms Pass Through rates and the Price Effects

of Mergers Merger Effects When Firms Compete by

Choosing Both Price and Advertising Does retail sector matter for

manufacturing mergers? [very preliminary]

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Quantitative benefit-cost analysis

Goal: quantitative estimate of merger effect. Necessary to weigh efficiencies

against loss of competition Two methodologies

Empirical comparisons, e.g. Staples/Office Depot

Model-based simulations

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Empirical Comparisonse.g., Staples-Office Depot Good natural

experiments or comparisons

Benefit-cost analysis still requires structural estimate of pass through

Depends on demand curvature

big pass-through iff big anticompetitive effect

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Model-based simulation Model current competition Estimate model parameters Simulate loss of competition from

merger

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e.g. Parking Merger Key parameters

cost of walking Sensitivity of

choice to price location of

merging lots location of non-

merging lots capacity of lots location of

office buildings 1

2

3

4

x

1

2

3

4y

0

500

1000

z

A:$1.4

B:$1.29

C:$1.46

1

2

3

4

x

1

2

3

4y

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Simple approach: Bertrand Price-setting game Static game

What about dynamic strategies? Price-setting competition

What about product, promotion, placement? Unilateral Effects

What about coordinated effects? Does retail sector matter?

Kroger-Winn Dixie vs. Quaker-Pepsi

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Simple approach: Modeling Critique How well does model capture loss of

competition from merger? Coke strategy is “share of throat”

More about placement and product than price MCI-Sprint

Tele-market new plans to rivals’ customers More about promotion than price

Is Bertrand a good metaphor for loss of competition?

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Simple approach: Does retail sector matter? When is retail sector transparent?

Constant or constant percentage markup two-part tariffs, and retail sector must

carry profitable products Retail sector earns no profit

When does it matter? Double marginalizationprice effect Two-part tariffs, and option of

exclusivityno price effect

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Simple approach: What about advertising? FOC’s if q=q(a,p)

{0=q+(p-mc)dq/dp, 0=-1+(p-mc)dq/da} FOC if q=q(a(p),p)

0=q+(p-mc’)dq/dp; mc’=mc+(da/dp)/(dq/dp)

Pre-merger: Price-only model with mc’ ≈ price+advertising model Does advertising increase with quantity?

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Simple approach: Implementation Estimate AIDS demand

Scanner data Instruments

None needed for weekly data LR vs. SR elasticities (Nevo & Hendel)

Prices in other cities Correlated through costs

Results High variance Inelastic demand? Goods are complements?

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Implementation Critique: too many parameters AIDS has too many parameters

Confidence intervals include both pro- and anti- scenarios. Elasticity matrix for merging products is most important.

Alternatives: Logit, nested logit, PD GEV (Bres.&Stern), mixed logit (BLP) + census data (Nevo)

But all goods are substitutes Only fool would admit post-merger price rise to FTC

Agencies discount efficiencies as not merger-specific So parties are reluctant to admit even small price increase.

Proposal: assume 5% MC reduction Then simulate post-merger prices

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PD GEVBresnahan & Stern

prod1P prod2P prod3P prod4P ROWprod1Q 1.56 0.313 0.125 0.125 1.prod2Q 0.313 1.56 0.125 0.125 1.prod3Q 0.125 0.125 1.56 0.313 1.prod4Q 0.125 0.125 0.313 1.56 1.COLUMN 0.25 0.25 0.25 0.25 1.

(multiple) dimensions of differentiation

Implies substitution patterns

PDGEVDimension0.8Listprod1, prod2,Listprod3, prod4

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Implementation Critique: Higher derivatives of demand f(x),f’(x), and f’’(x) influence predicted price rise.

Need location, velocity, and acceleration but observe only location

If we cannot estimate f’(x) Product margins Hall vs. Hausman in MCI-Sprint

If we cannot estimate f’’(x) Sensitivity analysis; or Use linear or logit for extrapolation to be conservative;

or compensating cost differentials don’t depend on

acceleration

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Implementation Critique: Average revenue instead of price Average revenue is quantity share-

weighted price index. Price changes cause weights to change.

Leads to inelasticity bias Use fixed weight index when possible.

Or use disaggregated data store-level data exist

but we don’t use them Individual choice data exist

but we don’t use them