This course covers empirical methods in industrial organization and firm behavior at the PhD level. We start with an overview of recent advances in estimation techniques for production functions and how these tools can be applied to estimate markups and product quality from production data. Further topics include empirical models of innovation, investment and firm performance. Applications of these tools in the context of mergers and acquisitions, multinational firms and industrial policy will be discussed. Students are asked to solve problem sets and to complete a take home assignment. The problem sets will include the analysis of actual data sets and replications of previous empirical studies. Students should make sure to have access to the relevant computer programs such as Stata or similar software. The take home assignment will be based on the readings.

Learning outcomes

The course is designed to enable doctoral students to understand and critically evaluate the empirical literature on various topics in empirical industrial organization (IO) and related fields. It also prepares students to conduct their own empirical analyses using firm-level data.

Attendance requirements

Regarding attendance, consult the Professor

Teaching/learning method(s)

Lectures and tutorials


Class participation, problem sets and take home assignment

Prerequisites for participation and waiting lists

PhD Students of Economics

Microeconomics, Microeconometrics

Recommended previous knowledge and skills

Knowledge of microeconomics and microeconometric methods including panel data, instrumental variable estimation, discrete choice and treatment effects

Availability of lecturer(s)
Unit details
Unit Date Contents
1 25.3.2019

Estimation of production functions

2 26.3.2019

Productivity, markups and multi-product firms

3 27.3.2019

Investment, R&D and Innovation

4 28.3.2019

Empirical studies of mergers & acquisitions

5 29.3.2019

Multinational firms and foreign direct investment

Last edited: 2019-06-04