Topics in Econometrics - Causal Inference and Networks (bachelor)
Lecture/Exercise: Wednesday, 10am – 12pm, Thursday, 12 – 2pm
LSF link
Tutor: Vincent Starck (V.Starck@lmu.de)
Teaching Content:
The course consists of two parts:
- The first one is devoted to causal inference and aims to give a solid understanding of the main concepts and modern methods.
- The second part of the course covers networks, especially networkdescription and representation as well as the study of network formationmodels. If time permits, we will discuss causal inference issues in thepresence of a network, e.g., the problem of interference.
Requisites: Basic knowledge of probability theory and statistics is assumed. Familiarity with regression, possibly stochastic convergence is useful but is not necessary.
Audience: 3rd year of Bachelor statistics or economics students (other groups are welcome).
Evaluation: Grading is based on a written 2-hour exam on February 7th, 2024, 10am.
ETC points: 6 ECTS