Amino Acid Lysine Antitrust Litigation Seth DePoint Chuck Fort Hadley Heath

Introduction Players: 5 Collusive Firms Ajinomoto, Kyowa Hakko, Archer-Daniels-Midland, Sewon, Cheil Sugar Governing Agencies FBI, U.S. Department of Justice (DOJ), European Commission and antitrust authorities of Canada, Mexico, Brazil

Introduction (2) Strategies Collusive Firms: Maximize profits by price-fixing Agencies: Maintain competitive markets by enforcing antitrust law

The Game

Introduction (3) Considerations Collusive Firms “Optimal Deterrence Theory” Penalty should be gains from collusion divided by the probability of detection

Timeline of Events 1970’s and 1980’s February 1991 Feb – Mid 1992 April 1992 Early 1993 October 1993 June 1995 Ajinomoto and Kyowa Hakko dominate ADM enters the market Predatory pricing period Collusion begins Price war Resolution FBI raid, Collusion ends

Prices Over Time (Graph)

Market Factors “Trade association” as cover up HHI >3500 Low buyer concentration Product homogeneity High barriers to entry

Market Factors (2) Should the market be considered an oligopoly instead of perfect competition? Are lysine prices seasonal?

Overcharge (Calculation Strategies) Before-and-After Method Costs-Based Approach Econometrics Method Yardstick Method Game Theory

Overcharge (Definition) Overcharge = Actual price charged minus the price had there been no collusion. Or, price minus “but-for” price

Before and After Strengths Simple to measure Ability to approximate costs trends Weaknesses Supply and Demand Length of before and after periods (sample sizes) Prices were seasonal? Before prices should be oligopoly based? Defines Noncollusive and Collusive periods of time and compares prices

Costs Strengths Supports evidence from other methods Weaknesses (Not used at time of case) Cost data valid? Source? Determines what a firm would charge given an estimate of its average costs and quantity produced. In ADM case, costs could be estimated to be between $.77 and $.83

Econometrics Strengths Many variables used to estimate changes in demand A “forecast” / “backcast” Weaknesses Long process to gather necessary data – “data hungry” Method too complicated for non-economists when presented in court Compiles data into a model that predicts what prices should have been given no collusion

Yardstick Strengths Could be very accurate in approximating “but-for” prices Weaknesses Often no similar markets to compare because cartels sell well-defined products Compares prices in market controlled by collusion with prices in market unaffected by collusion, either because of a different geographic location or a different product

Game Theory Strengths Weaknesses Author suggests negative prices would result Do the other methods of overcharge calculation make sense in the light of game theory?

Author’s Position John M. Connor Economic expert for certain plaintiffs who purchased lysine

Additional Questions Would the players have colluded if they knew they would get caught? Are the penalties for collusion harsh enough? Which of the overcharge calculation strategies works best in this case? Why?

Conclusion Collusive offenders  jail ADM paid $70 million to government $49 million to direct buyers $15 million to indirect buyers “Blue collar” used in “White collar” crime First successful conviction of a global cartel in more than four decades

The End