4851 Econometrics I
Lucas Darius Konrad, M.Sc.
Contact details
Weekly hours
Language of instruction
02/16/23 to 03/01/23
Registration via LPIS
Notes to the course
Day Date Time Room
Monday 03/06/23 10:00 AM - 12:00 PM TC.5.18
Monday 03/13/23 10:00 AM - 12:00 PM TC.5.18
Monday 03/20/23 10:00 AM - 12:00 PM TC.5.18
Monday 03/27/23 10:00 AM - 12:00 PM EA.5.040
Monday 04/17/23 10:00 AM - 12:00 PM TC.5.18
Monday 04/24/23 10:00 AM - 12:00 PM TC.5.18
Monday 05/08/23 10:00 AM - 12:00 PM TC.5.18
Monday 05/15/23 10:00 AM - 12:00 PM TC.5.18
Monday 05/22/23 10:00 AM - 12:00 PM TC.5.18
Monday 06/05/23 10:00 AM - 12:00 PM TC.5.18
Monday 06/12/23 10:00 AM - 12:00 PM TC.5.18
Monday 06/19/23 10:00 AM - 12:00 PM TC.5.18
Monday 06/26/23 10:00 AM - 12:00 PM TC.5.18

The econometrics teaching program is offered in a cycle over 3 terms. In Econometrics I, the foundations of the subject are dealt with: causality, correlation, assumptions of the linear regression model, OLS estimation, asymptotic tests, misspecification, outliers, heteroskedasticity and an introduction to R. In Econometrics II, advanced subjects are covered: Time series analysis, endogeneity, instrumental variable estimation, panel data and limited dependent variable models. In Applied Econometrics, a deeper analysis of selected topics is offered and students are required to write an empirical, applied-econometric essay.

'Econometrics I' comprises chapters 1-8 of Wooldridge's “Introductory Econometrics. A Modern Approach”, in particular:

  • Univariate regression model and the ordinary least squares estimator (OLS)
  • Multivariate regression model (application, interpretation)
  • Properties of the OLS estimator (classical assumptions, finite sample properties, asymptotic behaviour, Gauss-Markov theorem)
  • Regression model inference (hypothesis testing, confidence intervals, model selection)
  • Assumption failures (heteroskedasticity, serial correlation, multicollinearity)
  • Functional forms (log-transformations, dummy variables, interaction terms)
Learning outcomes

This course provides an introduction to the analysis of economic data using econometric methods. After having taken the course, students should be able to understand empirical studies published in scientific journals and carry out econometric work by themselves.

Attendance requirements

Attendance is compulsory. Students are allowed to miss up to two units.

Teaching/learning method(s)

The lectures are based on a slideset and are complemented by 4 empirical homework assignments.


Midterm exam (40%), final exam (40%), assignments (20%). A positive combined exam mark (average of midterm and final) is required to be positive in the course.


The grading scheme is:

  1. [90, 100]
  2. [78, 90)
  3. [65, 78)
  4. [50, 65)
  5. [0, 50)
Prerequisites for participation and waiting lists

If you have a valid registration for the lecture, but will not participate, please deregister during the registration period of LPIS. Your place will be available for other students.

During the registration period, free places are filled according to the “first-come, first-served” principle. After the end of the registration period, the number of places is increased and students on the waiting list will be registered for the lecture. Students in the BBE-program will be added first, should places remain, they will be filled by BaWiSo-students based on their progress in their studies.

Attendance in the first session is necessary, any absence will lead to deregistration! Any remaining places in the classes will be allocated to students attending the first session according to the waiting list. No places will be allocated by email or by phone.

Registration for the lecture cannot be guaranteed. Any student dropping out of the course who has already submitted a gradable task will receive a negative grade.


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Recommended previous knowledge and skills

Sound knowledge of statistics and mathematics

Availability of lecturer(s)


Supplementary Literature:

Baltagi, B. (2008). Econometrics, New York: Springer.

Greene, W. (2003). Econometric analysis, 5. ed., U.S.River, N.J.: Prentice Hall.

Gujarati, D.N., Porter, D.C. (2009). Basic Econometrics, New York: McGraw Hill.

Hackl, P. (2005). Einführung in die Ökonometrie. München: Pearson Studium.

Last edited: 2022-11-28