Transcript The Role of Econometric Analysis in Antitrust

Quantitative Benefit-cost
Analysis of Mergers
Luke Froeb
Oct. 26, 2001
Federal Trade Commission
Vanderbilt University
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References
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mba.vanderbilt.edu/luke.froeb/papers/
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Coauthors, Tschantz & Werden
Simulating Merger Effects Among Capacityconstrained 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
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Goal: quantitative estimate of merger
effect.
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Necessary to weigh efficiencies against loss
of competition
Two methodologies
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Empirical comparisons, e.g. Staples/Office
Depot
Model-based simulations
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Empirical Comparisons
e.g., Staples-Office Depot
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Good natural
experiments or
comparisons
Benefit-cost analysis
still requires structural
estimate of pass
through
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Depends on demand
curvature
big pass-through iff big
anticompetitive effect
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Model-based simulation
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Model current competition
Estimate model parameters
Simulate loss of competition from
merger
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e.g. Parking Merger
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y
Key parameters
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cost of walking
Sensitivity of
choice to price
location of
merging lots
location of nonmerging lots
capacity of lots
location of office
buildings
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B:$1 .29
2
1
A:$1 .4
C:$1 .46
1000
z
500
0
1
2
3
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Simple approach:
Bertrand Price-setting game
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Static game
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Price-setting competition
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What about product, promotion, placement?
Unilateral Effects
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What about dynamic strategies?
What about coordinated effects?
Does retail sector matter?
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Kroger-Winn Dixie vs. Quaker-Pepsi
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Simple approach:
Modeling Critique
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How well does model capture loss of
competition from merger?
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Coke strategy is “share of throat”
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MCI-Sprint
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More about placement and product than price
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?
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When is retail sector transparent?
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Constant or constant percentage markup
two-part tariffs, and retail sector must
carry profitable products
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Retail sector earns no profit
When does it matter?
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Double marginalizationprice effect
Two-part tariffs, and option of
exclusivityno price effect
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Simple approach:
What about advertising?
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FOC’s if q=q(a,p)
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FOC if q=q(a(p),p)
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{0=q+(p-mc)dq/dp, 0=-1+(p-mc)dq/da}
0=q+(p-mc’)dq/dp;
mc’=mc+(da/dp)/(dq/dp)
Pre-merger: Price-only model with mc’
≈ price+advertising model
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Does advertising increase with quantity?
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Simple approach:
Implementation
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Estimate AIDS demand
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Scanner data
Instruments
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None needed for weekly data
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Prices in other cities
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LR vs. SR elasticities (Nevo & Hendel)
Correlated through costs
Results
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High variance
Inelastic demand?
Goods are complements?
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Implementation Critique:
too many parameters
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AIDS has too many parameters
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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)
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But all goods are substitutes
Only fool would admit post-merger price rise to FTC
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Agencies discount efficiencies as not merger-specific
So parties are reluctant to admit even small price increase.
Proposal: assume 5% MC reduction
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Then simulate post-merger prices
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PD GEV
Bresnahan & Stern
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(multiple) dimensions of differentiation
PDGEVDimension 0.8
,
List prod1, prod2
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prod1 Q
prod2 Q
prod3 Q
prod4 Q
COLUMN
List prod3, prod4
Implies substitution patterns
prod1 P
1.56
0.313
0.125
0.125
0.25
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prod2 P
0.313
1.56
0.125
0.125
0.25
prod3 P
0.125
0.125
1.56
0.313
0.25
prod4 P
0.125
0.125
0.313
1.56
0.25
ROW
1.
1.
1.
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1.
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Implementation Critique:
Higher derivatives of demand
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f(x),f’(x), and f’’(x) influence predicted price rise.
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Need location, velocity, and acceleration
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If we cannot estimate f’(x)
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but observe only location
Product margins
Hall vs. Hausman in MCI-Sprint
If we cannot estimate f’’(x)
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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
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Average revenue is quantity share-weighted
price index.
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Leads to inelasticity bias
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Price changes cause weights to change.
Use fixed weight index when possible.
Or use disaggregated data
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store-level data exist
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but we don’t use them
Individual choice data exist
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but we don’t use them
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