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Quantitative Benefit-cost Analysis of Mergers Luke Froeb Oct. 26, 2001 Federal Trade Commission Vanderbilt University 1 References mba.vanderbilt.edu/luke.froeb/papers/ 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] Vanderbilt University 2 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 Vanderbilt University 3 Empirical Comparisons e.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 Vanderbilt University 4 Model-based simulation Model current competition Estimate model parameters Simulate loss of competition from merger Vanderbilt University 5 e.g. Parking Merger 4 y Key parameters cost of walking Sensitivity of choice to price location of merging lots location of nonmerging lots capacity of lots location of office buildings 3 B:$1 .29 2 1 A:$1 .4 C:$1 .46 1000 z 500 0 1 2 3 Vanderbilt University x 4 6 Simple approach: Bertrand Price-setting game Static game Price-setting competition What about product, promotion, placement? Unilateral Effects What about dynamic strategies? What about coordinated effects? Does retail sector matter? Kroger-Winn Dixie vs. Quaker-Pepsi Vanderbilt University 7 Simple approach: Modeling Critique How well does model capture loss of competition from merger? Coke strategy is “share of throat” MCI-Sprint 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? Vanderbilt University 8 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 Vanderbilt University 9 Simple approach: What about advertising? FOC’s if q=q(a,p) FOC if q=q(a(p),p) {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 Does advertising increase with quantity? Vanderbilt University 10 Simple approach: Implementation Estimate AIDS demand Scanner data Instruments None needed for weekly data Prices in other cities LR vs. SR elasticities (Nevo & Hendel) Correlated through costs Results High variance Inelastic demand? Goods are complements? Vanderbilt University 11 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 Vanderbilt University 12 PD GEV Bresnahan & Stern (multiple) dimensions of differentiation PDGEVDimension 0.8 , List prod1, prod2 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 Vanderbilt University 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. 1. 1. 13 Implementation Critique: Higher derivatives of demand f(x),f’(x), and f’’(x) influence predicted price rise. Need location, velocity, and acceleration If we cannot estimate f’(x) but observe only location 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 Vanderbilt University 14 Implementation Critique: Average revenue instead of price Average revenue is quantity share-weighted price index. Leads to inelasticity bias Price changes cause weights to change. 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 Vanderbilt University 15