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".
Competences
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.