5394 Econometrics II
Jan Greve, M.Sc.
Contact details
Weekly hours
Language of instruction
02/16/23 to 02/22/23
Registration via LPIS
Notes to the course
Day Date Time Room
Wednesday 03/01/23 01:30 PM - 03:30 PM TC.2.03
Wednesday 03/08/23 01:30 PM - 03:30 PM TC.2.03
Wednesday 03/22/23 01:30 PM - 03:30 PM TC.2.03
Wednesday 03/29/23 01:30 PM - 03:30 PM TC.2.03
Wednesday 04/12/23 01:30 PM - 03:30 PM TC.2.03
Wednesday 04/19/23 01:30 PM - 03:30 PM TC.2.03
Wednesday 04/26/23 01:30 PM - 03:30 PM TC.2.03
Wednesday 05/10/23 01:30 PM - 03:30 PM TC.2.03
Wednesday 05/17/23 11:00 AM - 01:30 PM TC.0.04
Wednesday 06/14/23 01:30 PM - 05:00 PM D5.0.002
Wednesday 06/21/23 01:30 PM - 04:00 PM TC.3.03

This course covers econometrics methods beyond linear models. We discuss time series data with a focus on stationarity and non-stationarity. ARMA and ARIMA models are introduced and their application to estimation and forecasting is being illustrated. In the second part of the course, we cover limited dependent variable models (logit and probit models) as well as count data regression. If time allows, we also look into instrumental variables regression as a means to deal with endogeneity.

Learning outcomes

After this course, students are able to critically discuss empirical studies using the econometric methods covered in this course. Moreover, students can independently conduct their own analyses of economic data.

Attendance requirements

For this lecture participation is obligatory. Students are allowed to miss a maximum of 20% (no matter if excused or not excused).

Teaching/learning method(s)

In-class, content is presented using the whiteboard and presentation slides. Moreover, the methods are illustrated via case studies using R. To ensure the in-depth applicability of the material presented, the students will work in groups on three extensive case studies and on a project.

The solutions must be handed in in form of written reports. The project will be presented in form of an oral presentation during the last two lectures.



The assessment is based on 5 components:
(1) Case Study 1(10 points)
(2) Case Study 2 (10 points)
(3) Case Study 3 (10 points)
(4) Final exam (30 points)
(5) Final Presentation ( 20 points)

Attendance is mandatory.


Grading scheme:

1: 72 – ∞

2: 64 – 71.99

3: 56 – 63.99

4: 48 – 55.99

5: 00 – 47.99



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Recommended previous knowledge and skills

Successful completion of Econometrics I.

Last edited: 2022-11-03