KECD 2310 - EMPIRICAL INDUSTRIAL ORGANIZATION

The aim of this course is to provide a solid understanding of the modern empirical tools useful to learn about strategic behaviour of firms, the structure of markets, and consumer demand. While the questions of interest are empirical in nature (e.g., what happens to consumer welfare if two car manufacturers would merge?), modern empirical organization makes use of an elaborate quantitative apparatus to convincingly answer such questions. The first part of the course focuses on demand estimation. Starting from a simple regression model we work towards the central method in recent academic literature and the policy world. Step-by-step we discuss how elements of an empirical demand model contribute to generating the realistic demand elasticities we need. A second element of the course is practical: you will learn how to perform demand estimation on actual data in Matlab. We will cover data requirements, types of instruments, computation, simulation. Finally, we discuss a wide range of applications in the empirical industrial organization literature that also include questions related to market entry and two-sided markets. This class is best suited for those interested in pursuing a Ph.D. in this area or those looking to work in competition policy after graduating.

Marleen MARRA

Séminaire

English

Students are expected to come to class prepared, interrupt with questions if things are unclear, help each other in practicals (computer room) with coding issues, and provide constructive feedback after presentations. This all counts towards class participation. Students are also asked to present in detail a journal article that uses demand estimation, and answer questions about it. For the final exam students are evaluated on their understanding of modelling choices, estimation strategy, and empirical application of the methods learned in class. Students select one journal article from Moodle for their presentation; all selected articles are required reading as well.

A basic understanding of: calculus (derivatives), statistics (regression), probability theory (e.g. what a probability distribution is), game-theory (e.g. what an equilibrium is).

Autumn and Spring 2022-2023

Class participation: 20%, Presentation: 25%, Final exam: 55%.

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