Universität Wien
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040122 UK Applied Econometrics 2 (BA) (2026S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 60 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Donnerstag 07.05. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Dienstag 12.05. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 19.05. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 21.05. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Dienstag 26.05. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 28.05. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Dienstag 02.06. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 09.06. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 11.06. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Dienstag 16.06. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 18.06. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
  • Dienstag 30.06. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Mittwoch 08.07. 13:15 - 14:45 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Aims and Contents

The aim of the course is to provide students a thorough understanding of theoretical foundations and proper applications of instrumental variable estimation and econometric techniques for panel data and microeconometric data. The course will cover two-stage least squares, seemingly unrelated regression, fixed-effects and random-effects panel estimation as well as econometric models for categorical data and for limited dependent variables. Examples and applications will be illustrated using the open-source software R.
In an accompanying tutorial, students will deepen the material based on exercises and applications using R.

Form of Teaching

The course will be taught in class. All necessary information and possible short-term announcements will be provided through the Moodle site of the course.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Assessment

Three closed-book exams, a 45 min:
Part I, June 2, 2026 (HS 1, 16:45-17:30), on the correspond. topics covered in the course.
Part II, June 30, 2026 (HS 1 16:45-17:30); on the corresponding topics covered in the course.
Part III, June 30, 2026 (HS 1, 17:30-18:15); on R.

Questions can consist of multiple-choice questions, analytical derivations and interpretations of empirical results.
For the Exam the Moodle system will be used (at least for the R exam). Hence, it is necessary to have your laptops with you!

Mindestanforderungen und Beurteilungsmaßstab

Grading:

For the final grade the individual assignments count as follows:
i) Three exams: 100%, 30% for exam 1 and 2, 40% for the R exam
ii) Extra points for class room participation in the “exercise block”, 3% per participation.

Important: Aside from the three assignments, there will be no additional examination possibilities afterwards.
To pass the course, the attendance in the first session is mandatory and a minimum level of 50% of the total points.

Grading scheme:

[86%; 100%]: 1.0
[74%; 86%): 2.0
[62%;74%): 3.0
[50%; 62%): 4.0
[0; 50%): 5.0

Examination language: English.

Prüfungsstoff

1. Instrumental variables
2. Panel model
3. Models with qualitative variables

Literatur

Sile - see Moodle

Dougherty, C., “Introduction to Econometrics”, 3rd ed., Oxford University Press, 2007.
Franses, P. H., van Dijk, D., and Opschoor, A., “Time Series Models for Business and Economic Forecasting”, 2nd ed., Cambridge University Press, 2014.
Heij, De Boer, Franses, Kloek, and Van Dijk, ''Econometric Methods with Applications in Business and Economics'', Oxford University Press, 2004.
Stock, J.H., Watson, M.W., ''Introduction to Econometrics'', 3rd edition, Pearson, 2012.
Studenmund, A. H. “Using Econometrics”, 6th ed., Pearson, 2011

Online Literatur basierend auf R:
Heiss, F., “Using R for Introductory Econometrics”, 2016, http://www.urfie.net
Hanck, C., Arnold, M., Gerber, A., and Schmelzer, M., 2019, https://www.econometrics-with-r.org/index.html

R Studio Cloud Projekt Link: https://rstudio.cloud/project/950163, and tutorial

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mo 27.07.2026 09:26