(6 ECTS/4 Bonus Points)

Lecturer: PD Dr. Stefan Klößner
Tutor: M.Sc. Sandra Baar

Lecture Tutorial
Weekday & Time Thursday 10 – 12 Tuesday 08:30 – 10
Building C3 1 C3 1
Room 3.01 3.01
Start October 26, 2017 October 24, 2017

Educational objectives

The first objective is to provide students with a rigorous grounding in econometrics and to develop a critical awareness of the importance of any assumptions that are made in economic modelling. Another objective is to introduce students to applied econometrics, including basic techniques in regression analysis and some of the variety of extensions that are used when the linear model appears to be inappropriate. The intended application of econometric methods includes the use of databases and statistical/econometric software.


Course prerequisites include introductory probability theory and statistics, as well as calculus and matrix algebra. Additionally, an introductory econometrics course is very useful.


  1. The classical multiple linear regression model
  2. Functional form and structural change
  3. Specification analysis and model selection
  4. Generalized regression model and heteroscedasticity
  5. Models for panel data
  6. Instrumental variables estimation
  7. Maximum likelihood estimation
  8. Serial correlation and models with lagged variables


  Author Title Link
Greene, William H Econometric Analysis (2012)
Stock, James H. / Watson, Mark Introduction to Econometrics (2012)
Farnsworth, Grant Econometrics in R (2008) Free PDF

Page was last modified on:
February 14, 2018 – 10:32:49