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This presentation by Farasat Bokhari was made at the 2014 Global Forum on Competition (27-28 February) at the session on competition issues in the distribution of pharmaceuticals. Find out more at http://www.oecd.org/competition/globalforum
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EVALUATING WHOLESALE AND RETAIL MERGERS IN
PHARMACEUTICALS
Farasat A.S. Bokhari Franco Mariuzzo
ESRC Centre for Competition PolicySchool of Economics
University of East Anglia
[email protected]@uea.ac.uk
http://www.uea.ac.uk/economics
OECD’s 13th Global Forum on Competitionfor “Competition Issues in the Distribution of Pharmaceuticals”
Paris, FranceFebruary 27-28, 2014
MOTIVATIONEVALUATING MERGERS FOR DIFFERENTIATED PRODUCTS
Role of wholesalers and retailers (pharmacies)
Differentiated products
Demand estimation using retail level sales data
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MOTIVATIONEVALUATING MERGERS FOR DIFFERENTIATED PRODUCTS
Role of wholesalers and retailers (pharmacies)
obtain drugs from manufacturers and pass downstreamadd services to otherwise similar products
wholesalers: e.g. number and location of warehouses, differences in storage capacities,delivery frequency to pharmaciespharmacies: e.g. number of stores per market, location of stores, hours of operation,queuing time, advice from trained pharmacist, electronic patient records, automatic refillreminders
Differentiated products
Demand estimation using retail level sales data
1 / 6
MOTIVATIONEVALUATING MERGERS FOR DIFFERENTIATED PRODUCTS
Role of wholesalers and retailers (pharmacies)
obtain drugs from manufacturers and pass downstreamadd services to otherwise similar products
wholesalers: e.g. number and location of warehouses, differences in storage capacities,delivery frequency to pharmaciespharmacies: e.g. number of stores per market, location of stores, hours of operation,queuing time, advice from trained pharmacist, electronic patient records, automatic refillreminders
Differentiated products
the same drug in two different pharmacies not the samefor non-homogenous products, analyzing pre-merger market shares usingconcentration ratios, herfindahl index, etc. are not reliable tools for evaluating pre-or post-merger market power (price cost margins)
Demand estimation using retail level sales data
1 / 6
MOTIVATIONEVALUATING MERGERS FOR DIFFERENTIATED PRODUCTS
Role of wholesalers and retailers (pharmacies)
obtain drugs from manufacturers and pass downstreamadd services to otherwise similar products
wholesalers: e.g. number and location of warehouses, differences in storage capacities,delivery frequency to pharmaciespharmacies: e.g. number of stores per market, location of stores, hours of operation,queuing time, advice from trained pharmacist, electronic patient records, automatic refillreminders
Differentiated products
the same drug in two different pharmacies not the samefor non-homogenous products, analyzing pre-merger market shares usingconcentration ratios, herfindahl index, etc. are not reliable tools for evaluating pre-or post-merger market power (price cost margins)
Demand estimation using retail level sales data
provides pre-merger measures of market powercan be used to predict changes in prices and price-cost marginsevaluates changes in consumer welfare due to proposed mergers at the wholesale orretail level
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A STYLIZED MODELAND HORIZONTAL MERGER PREDICTIONS
Manufacturer sells the same drug tomultiple wholesalers at ex-manufacturerprice pm
Wholesalers allowed a maximummark-up over the ex-manufacturerprice, and decide level of discounts topharmacies (modeled as homogenousservice/product providers)
Pharmacies choose quantity to obtainfrom wholesalers, set price and quality(R,N) at their pharmacy
Patients choose which pharmacy to visitbased on differences in price, qualityand location of stores (pharmacies arevertically and horizontallydifferentiated)
Some predictions of the model ...
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A STYLIZED MODELAND HORIZONTAL MERGER PREDICTIONS
Merger at Wholesale Level Merger at Pharmacy Level
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A STYLIZED MODELAND HORIZONTAL MERGER PREDICTIONS
Merger at Wholesale Level
discounts to pharmacies decreasepharmacy prices increase (unambiguously)a one dollar decrease in discounts (typically)implies a less than dollar increase inpharmacy prices (pass-through rate less thanone)when pass-through rate is less than one,quality at pharmacies also decreases
Merger at Pharmacy Level
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A STYLIZED MODELAND HORIZONTAL MERGER PREDICTIONS
Merger at Wholesale Level
discounts to pharmacies decreasepharmacy prices increase (unambiguously)a one dollar decrease in discounts (typically)implies a less than dollar increase inpharmacy prices (pass-through rate less thanone)when pass-through rate is less than one,quality at pharmacies also decreases
Merger at Pharmacy Level
prices increasequality decreases
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A STYLIZED MODELAND HORIZONTAL MERGER PREDICTIONS
Merger at Wholesale Level
discounts to pharmacies decreasepharmacy prices increase (unambiguously)a one dollar decrease in discounts (typically)implies a less than dollar increase inpharmacy prices (pass-through rate less thanone)when pass-through rate is less than one,quality at pharmacies also decreases
Merger at Pharmacy Level
prices increasequality decreases
How much the quantity and prices change at the pharmacy level is an empirical issue anddepends on, among other things, consumer demand for pharmacy services
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EMPIRICAL STRATEGYDEMAND ESTIMATION AND MERGER SIMULATIONS
Data – pharmacy sales data
Estimation – obtain demand parameters
Simulation – predict post-merger prices
Calculation – compute welfare effect
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EMPIRICAL STRATEGYDEMAND ESTIMATION AND MERGER SIMULATIONS
Data – pharmacy sales data
convert sales of individual drugs to sales of standard units (SU) (using defined dailydosage of different drugs)aggregate standard units (quantity and prices) to pharmacy-chain level (K number oftotal chains) per market (national or sub-national level and time periods)obtain observable characteristics of pharmacy-chains per market (e.g. number ofstores, trained pharmacists, average open hours, etc. per city)
Estimation – obtain demand parameters
Simulation – predict post-merger prices
Calculation – compute welfare effect
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EMPIRICAL STRATEGYDEMAND ESTIMATION AND MERGER SIMULATIONS
Data – pharmacy sales data
Estimation – obtain demand parameters
specify a demand system where demand for SUs from a given pharmacy chain (q) isa function of own and competitor’s prices (R), quality (N)and other exogenousdemand shifters Z (e.g. demographic differences in cities or trends over time)
qk = Dk(Rk,R−k,Nk,N−k, Z, εk; θk)
standard demand models can be used (logit/nested-logit/random-coefficients-logit ormulti-stage budgeting with AIDS specifications)∗
Simulation – predict post-merger prices
Calculation – compute welfare effect
∗See accompanying note DAF/COMP/GF(2014)4 for details.4 / 6
EMPIRICAL STRATEGYDEMAND ESTIMATION AND MERGER SIMULATIONS
Data – pharmacy sales data
Estimation – obtain demand parameters
Simulation – predict post-merger prices
use profit maximization conditions for each pharmacy chain to back out effectivemarginal costs c for each chain
R = c −(
O · Ω)−1
q and N =(
O · Ψ)(R − c)
where Ω and Ψ are functions of estimated demand parameters, and O is the K × K joint 1/0 pharmacy
ownership matrix with ones in the leading diagonals and the off-diagonal terms are zero or one if two chains
are co-owned
simulations: change marginal cost from estimated value to higher values (10%,25%, 50% etc. higher values) and use equations above to obtain predicted values ofpharmacy prices and quality (R and N) for simulated wholesale merger;alternatively change values of ownership matrix to simulate pharmacy level merger∗
Calculation – compute welfare effect
∗See accompanying note DAF/COMP/GF(2014)4 for details.5 / 6
EMPIRICAL STRATEGYDEMAND ESTIMATION AND MERGER SIMULATIONS
Data – pharmacy sales data
Estimation – obtain demand parameters
Simulation – predict post-merger prices
Calculation – compute welfare effect
given observed prices/quality pre-merger and predicted post-merger prices andquality, compute welfare effectswhat level of monetary compensation would leave a representative consumer aswell-off at new prices/qualities as she was at the pre-merger prices/qualities?
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EMPIRICAL STRATEGYDEMAND ESTIMATION AND MERGER SIMULATIONS
Data – pharmacy sales data
Estimation – obtain demand parameters
Simulation – predict post-merger prices
Calculation – compute welfare effect
5 / 6
TAKE AWAY MESSAGEHORIZONTAL MERGERS IN PHARMA
The final product that reaches a consumer via different routes is highly differentiated dueto the nature of services attached to these products (e.g., frequency of delivery bywholesalers or advice by pharmacist and physical location of outlets)
Analyses based on pre-merger market shares alone do not provide good measures ofmarket power (price-cost margins)
Sales data of individual drugs is typically available, and can be aggregated up to sales atpharmacy-chain level
Standard demand estimation methods and merger simulations from the empirical IOliterature can be adapted to (i) infer price-cost margins at the pharmacy level, (ii) back-outeffective marginal costs for the pharmacies, and (iii) predict changes in retail level pricesand quality due to a proposed merger
These (observed and predicted values) can be used to obtain measures of changes inconsumer welfare – which can then be compared to changes in profits to assess the overalleffect of a proposed merger
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