Advanced Econometrics

Course Description

The goal is to familiarize students with advanced regression techniques. After a short revision of the basic concepts of the linear regression model, further methods are beeing presented. Students learn how to estimate these models, interpret the estimation results and evaluate the models diagnostically. In addition students deal critically with the methods they have learned.


  • Basic education in statistics and mathematics from the Bachelor program is required.
  • Basic knowledge from the Econometric course is recommended, but not necessarily required.


  • Credit Points: 6
  • Semester: Wintersemester
  • Scope: Lecture: 2 SH, Tutorial: 2 SH
  • Language: English
  • Exam: Depending on the number of participants, either written (120 min.) or oral exam (20 min.) at the end of the semester. The type of examination will be communicated at the beginning of the semester.


  • Lecture:
    • Date: Tuesday, 14:00 - 16:00
    • Location: Bldg. C3 1, Room 3.01
    • Start: 24.10.2023
  • Tutorial:
    • Date: Thursday, 10:00 - 12:00
    • Location: Bldg. C3 1, Room 3.01
    • Start: 26.10.2023


Lecture and tutorial notes can be found on Moodle.


Chapter 1: A Reminder of Linear Regression Basics
Chapter 2: Classical Linear Regression Model Assumptions and Diagnostics
Chapter 3: Limited Dependent Variable Models
Chapter 4: Simulation Methods
Chapter 5: Further Advanced Methods


  • Brooks, C.: Introductory Econometrics for Finance, current edition. Cambridge University Press.
  • Greene, W.H.: Econometric Analysis, current edition. Pearson.