Quantitative Benefitcost Analysis of Mergers

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Quantitative Benefit-cost Analysis of Mergers

• Luke Froeb
• Oct. 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

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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 marginalization?price effect
• Two-part tariffs, and option of exclusivity?no
  price effect

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Simple approach What about advertising?

• FOCs if qq(a,p)
• 0q(p-mc)dq/dp, 0-1(p-mc)dq/da
• FOC if qq(a(p),p)
• 0q(p-mc)dq/dp mcmc(da/dp)/(dq/dp)
• Pre-merger Price-only model with mc
  priceadvertising 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

• (multiple) dimensions of differentiation
• Implies substitution patterns

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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 dont 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 dont use them
• Individual choice data exist
• but we dont use them