To content
Department of Business and Economics

Causal analysis: Economics meets Data Science

Module: Module 8a-d: Microeconomics I
Lecturer: Prof. Dr. Lukas Buchheim
M. Sc. Marcel Vögele
Scope / Credits: 4 SWS / 7,5 Credits
Course type: Lecture and exercise
Language: German 
Date and place: Lecture: Monday, 2 p.m. - 3:30 p.m., SRG 1.023
Exercise: Wednesday, 12:15 p.m. - 1:45 p.m., M134
Beginning: April 8, 2024
Exam: Oral or written exam

Contents overview

This course provides an introduction to causal analysis. Causal analysis examines the extent to which the causal effect of a certain measure (e.g. minimum wage) on a certain variable (e.g. unemployment) can be derived from observable data. For this purpose, methods of microeconometrics and data science are used, which have a broad field of application in economics, data science, or strategic management. The course combines the theory of causal analysis with its application within the framework of the statistics programme "R".



You will acquire the competence to interpret empirical findings in terms of whether - and under which conditions - a causal relationship or merely a correlation is measured. Furthermore, students will be enabled to empirically test causal questions independently.

Contact person