Syllabus
Registration via LPIS
Research Seminar in Main Subject I - Empirical Business Research
Research Seminar in Main Subject II - Economics
Research Seminar in Main Subject II - Empirical Business Research
Research Seminar in Main Subject III - Economics
Research Seminar in Main Subject III - Empirical Business Research
Research Seminar in Main Subject IV - Economics
Research Seminar in Main Subject IV - Empirical Business Research
Dissertation-relevant theories - Economics
Dissertation-relevant theories - Empirical Business Research
Research Seminar - Economics
Research Seminar - Empirical Business Research
Research Seminar - Economics
Research Seminar - Empirical Business Research
Academic Writing
Methodology and Theory
Research Seminar - Participating in scientific discourse I
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.
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.
PhD Students of Economics
Microeconomics, Microeconometrics
Knowledge of microeconomics and microeconometric methods including panel data, instrumental variable estimation, discrete choice and treatment effects
Email: stiebale@dice.hhu.de
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