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This article by Gregory J. Werden explores the applications of calibrated economic models in antitrust cases, focusing on merger and non-merger situations. The text emphasizes the importance of selecting and calibrating models to increase accuracy and persuasiveness in economic analysis, helping experts reach informed conclusions based on real-world data and established facts. It discusses the use of standard economic tools, monopoly and oligopoly models, consumer demand models, and merger simulation techniques to assess competitive effects in different scenarios. Additionally, the article delves into critical aspects of modeling a hypothetical monopolist, evaluating market power issues, and conducting merger simulations using various oligopoly models like Cournot and Bertrand.
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Antitrust Analysis Using Calibrated Economic Models Gregory J. Werden Senior Economic Counsel Antitrust Division U.S. Department of Justice The views expressed herein are not purported to reflect those of the U.S. Department of Justice
Calibrated Economic Models Are: • Standard economic tools • Monopoly and oligopoly models • Consumer demand models • Applied in a straightforward way • Using known facts (e.g., prices and shares) • Making reasonable assumptions
Applications of Calibrated Economic Models In Merger Cases • Market delineation Modeling the hypothetical monopolist with the standard model of monopoly • Merger simulation Modeling oligopoly interaction with a standard model of oligopoly
Applications of Calibrated Economic Models In Non-Merger Cases • Market delineation Non-merger cases may present prospective market power issues just as mergers do • Analyzing competitive effects Modeling can shed light on the impact of many exclusionary practices
Selection and Calibration of Models • Select a model that generally describes the actual competitive interaction • Make necessary assumptions that are (1) supported by data, (2) unimportant, or (3) biased against the modeler • Calibrate the model by fitting it precisely to a “pre-merger equilibrium”
Calibrated Economic Models Sharpen Focus • Models are built on assumptions • Assumptions can and should be tested against the established facts • Modeling indicates: • why price effects are large or small • how experts reached different conclusions • where resources should be concentrated
Calibrated Economic ModelsIncrease Accuracy • Calculation replaces intuition • Expert intuition on quantitative matters is a highly unreliable black box • Modeling replaces the black box with transparent calculations • Measurement replaces assumption • Real-world data is the basis for calculations
Calibrated Economic ModelsEnhance Persuasiveness • The analysis is firmly anchored in facts • Model assumptions are tested against facts • Model parameters are based on data • The analysis employs economic science • The models are standard economic theory • Econometrics may be used • Economists do what they normally do
Artful Construction ofCalibrated Economic Models • Highly realistic models are useless • Calibration most likely is infeasible • Predictions most likely are unclear • Useful models capture what matters most over the relatively short run • The essence of the competitive process • Critical firm and product attributes
Critical Elasticity of Demandand Critical Sales Loss • Indicate how much substitution is too much for the hypothetical monopolist • Qualitative application Providing a lens for viewing qualitative evidence of substitutability • Quantitative application Using demand elasticities estimated from transaction or survey data
Modeling a Hypothetical Monopolist • Demand models • Multiple uses with significantly differing elasticities of demand • Cost models • Marginal costs that vary with output • Fixed costs for blocks of capacity • Multiple prices • Disproportionate price increases
Modeling the Unilateral Competitive Effects of Mergers • Select a standard oligopoly model capturing important industry features • Calibrate the model so it perfectly predicts the pre-merger equilibrium • Compute the post-merger equilibrium, which internalizes the competition among merging products
Presumptions of Merger Simulation • Merger simulation presumes that the fundamental nature of the competitive interaction is not changed by a merger. • Merger simulation presumes that everything “outside the model” is unaffected by the merger.
Oligopoly Models CommonlyUsed in Merger Simulation • Dominant firm Monopoly with respect to residual demand • Cournot Quantity setting with a homogeneous product • Bertrand Price setting with differentiated products • Auctions Non-cooperative bidding
Bertrand Merger Simulation:Model Calibration • Calibrate prices and shares • Normally use those prevailing pre merger • May project changes “but for” the merger • Calibrate demand elasticities • Commonly estimated from scanner data • Can be inferred from price-cost margins
Bertrand Merger Simulation: Modeling Demand • Every demand model is restrictive Each has inherent “curvature” properties • Flexibility is a blessing and a curse Trading off bias and variance • The logit model Substitution proportionate to shares
Bertrand Merger Simulation:Checking the Bertrand Assumption • Compare Bertrand price-cost margins with “actual” price-cost margins • Examine substantial differences for the merging products and major rivals • Intensity of competition may not be as implied by the Bertrand assumption
Bertrand Merger Simulation:Continuing Controversies • Multifaceted marketing strategies • Product repositioning • The retail sector • Demand estimation problems
Merger Simulation in Perspective I • Merger simulation is simply a useful device for clarifying the implications of established facts and plausible market conditions. • Merger simulation combines what is known with reasonable assumptions about what is not known, and evaluates their significance in a precise, objective manner by substituting calculation for intuition.
Merger Simulation in Perspective II • Models simplify the world • Models are tractable because they simplify • Modeling is as much art as science • Calibration is inexact • Assumptions fill gaps in measurement • Measurement is inherently imperfect • Predictions are useful rough estimates