040265 UK Empirical Methods in Antitrust (BA) (2019S)

Course description: This course covers empirical methods in competition economics and antitrust at the Bachelor level. We discuss the estimation of price models and continuous demand models. The focus is on empirical applications that investigate competition and antitrust cases. Particular examples are how to estimate the effect of market structure and mergers on prices, empirical models of (internet) auctions, estimation of demand for food, assessment of cartel damages and vertical relations.

Aim: The aim of this course is to expand students' knowledge of advances in the field of industrial organization and competition economics at the bachelor level. A particular emphasis is put on empirical applications and the discussion of papers. This course provides lectures on the empirical implantation of price and demand models. The lectures are supplemented with empirical studies to learn how to apply these models to real world situations. The topics are discussed in the context of antitrust cases such as assessments of market power, definition of markets, merger analysis and calculation of damages.

Learning Goals: After taking the course students should also be able to read and understand how to estimate price and demand models and how these models can be used in competition and antitrust cases. Graduates should be also able to read and understand project reports and journal articles that make use of the concepts and methods that are introduced in the course. Students should also learn how to apply empirical concepts in competition economics and antitrust to real world cases. Students should further extend their ability to effectively structure and communicate economic content in written form to audiences from academia, government and business.

Method: The course will be taught through a combination of lectures, problem sets presented by students and discussions. Students are asked to solve three problem sets and to write a final exam. The problem sets will include the analysis of actual data sets and replications of previous work. Students should make sure to have access to the relevant computer programs such as Stata or similar software.