Universität Wien

040327 KU Introductory Econometrics (MA) (2025S)

8.00 ECTS (4.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
Moodle
Mo 28.04. 11:30-13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 200 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Monday 03.03. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 06.03. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 10.03. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 13.03. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 17.03. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 20.03. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 24.03. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 27.03. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 31.03. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 03.04. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 07.04. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 10.04. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Friday 02.05. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Tuesday 06.05. 15:00 - 16:30 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 12.05. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Friday 16.05. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 19.05. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 22.05. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 26.05. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Friday 30.05. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 02.06. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 05.06. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 12.06. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 16.06. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Friday 20.06. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Monday 23.06. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
    Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Tuesday 08.07. 09:45 - 11:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
    Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß

Information

Aims, contents and method of the course

Aims and Contents
The course is a first-year master-level course in econometrics for students who already have a background in statistics and are familiar with the basic principles of probability theory, mathematical statistics and linear regression. The course provides an understanding of standard econometric methods. Knowledge of these methods allows one to understand modern empirical economic literature and to perform one's own analysis of cross-sectional, time series, and panel data. After following this course, students will have a good working knowledge of the key properties of standard econometric methods, including Least Squares Estimation, Instrumental Variables Estimation, and Maximum Likelihood, and their use in various applications.

Topics include foundations of least squares estimation, applications of linear regression, endogeneity and instrumental variable estimation, stationary ARMA models, non-stationary time series models, fixed effects and random effects estimation, logistic regression, regression with limited dependent variables, experiments and quasi-experiments among others.

If not compulsory, it is highly recommended to also attend the weekly TA session, which takes place in parallel to the lecture.

Assessment and permitted materials

Unexcused absence from the first session will automatically lead to deregistration in order to allow students on the waiting list to move up. If you are unable to attend the first session, you must notify me in advance via email in order to continue attending the course.

Assessment: The assessment consists of 2 tests during the semester (midterm, final exam – each 45%) and homework (2 exercises in groups of up to 4, each 5%).

The tests will take place on following days:
06.05.2025: 15.00-16.30h
23.06.2025: 11.30-13.00h

The tests will take 60 minutes. The questions will refer to general material covered in the course, analytical derivations, and interpretations of empirical results. Each test will count for 45% and homework for 10%.

Students who failed the course (i.e., obtained less than 50% after the two exams and the homework) are eligible to participate in the retake exam. The retake exam takes place on 08.07.2025. Students who want to participate in the retake exam need to register by 01.07.2025 the latest. The result of the retake exam replaces the worse of the two exams during the semester.

Minimum requirements and assessment criteria

To pass the course, a minimum level of 50% has to be reached.

Grades:
[87.5%; 100%]:1.0
[75%; 87.5%): 2.0
[62.5%;75%): 3.0
[50%; 62.5%): 4.0
[0; 50%): 5.0

Examination language: English.

Examination topics

Examination Topics
All material covered in the course.

Reading list

Main books:
Greene, W.H. (2019): Econometric Analysis, 8th edition, Pearson.
Stock, J. H., and Watson, M. W. (2020), Introduction to Econometrics, Global Edition. Pearson Education Limited
Wooldridge, Jeffrey M. Introductory econometrics: A modern approach. 7th edition, Cengage learning, 2020.

Additional books:
Angrist, J.D. and Pischke, J.-S. (2009): Mostly Harmless Econometrics: An Empiricst's Companion, Princeton University Press.
Cunningham, Scott. Causal inference: The mixtape. Yale university press, 2021.
Wooldridge, Jeffrey M. Econometric analysis of cross section and panel data. MIT press, 2010.
Hanck, C., Arnold, M., Gerber, A., and Schmelzer, M. (2020): Introduction to Econometrics with R, Online book on : https://www.econometrics-with-r.org/. Based on Stock, J. H., and Watson, M. W. (2015), Introduction to Econometrics, Global Edition. Pearson Education Limited.
Heiss, F. (2020): “Using R for Econometrics”. Online book on http://www.urfie.net/. Based on Wooldridge, J.M. (2019), Introductory Econometrics, Cengage Learning, Boston, MA.

Association in the course directory

Last modified: Mo 03.03.2025 15:46