Universität Wien

040012 UE Econometric Programming in Economics (MA) (2023S)

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

An/Abmeldung

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

Details

max. 50 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Montag 06.03. 11:30 - 13:00 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Freitag 10.03. 09:45 - 11:15 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 17.03. 09:45 - 11:15 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Montag 20.03. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 24.03. 09:45 - 11:15 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 31.03. 09:45 - 11:15 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Montag 17.04. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 21.04. 09:45 - 11:15 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Montag 24.04. 09:45 - 11:15 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 28.04. 09:45 - 11:15 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 05.05. 09:45 - 11:15 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Freitag 12.05. 09:45 - 11:15 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Montag 15.05. 09:45 - 11:15 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

NOTE: The course will be offered in hybrid format (in-class and via live stream) if the class size exceeds the maximum capacity of the computer labs.

Content:

This course provides students with the skill set to conduct econometric analysis. Building upon the introductory course of econometrics, students will get a deeper understanding of the relevant methods used in contemporary empirical analysis and they will learn how to implement these methods using the statistical software R. While the techniques and methods are also introduced and discussed in class, the emphasis of the course is on their application in R.Typical questions of this course are, among others: What methods are available to estimate coefficients and standard errors of a specific regression model? What are the implications of missing data or measurement error? Which techniques are suitable for the analysis of duration data? How can (local) average treatment effects be estimated? What methods are available to exploit quasi-experimental variation?

Course goals:

At the end of the course, students will be familiar with the relevant techniques and tools used for empirical analysis in applied economics. This will allow them to critically read, understand and replicate empirical research. For a given research question and dataset, students will be able to choose appropriate econometric methods and conduct empirical analysis using R.

Prerequisites:

- Knowledge of statistics and applied econometrics (MA course “Introductory Econometrics” or equivalent)
- Basic knowledge of R or similar statistical software

Art der Leistungskontrolle und erlaubte Hilfsmittel

The course assessment consists of a take-home assignment (45%), an empirical research project (45%) and participation in class (10%).

Mindestanforderungen und Beurteilungsmaßstab

Students are encouraged to regularly attend the course sessions. The final grade will be a weighted average of grade points obtained for the three assessment parts that are listed above.

Prüfungsstoff

Econometric methods and statistical programming with R (see course content).

Literatur

Methods:

- Joshua D. Angrist and Jörn-Steffen Pischke. Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press, 2008.
- Colin A. Cameron and Pravin K. Trivedi. Microeconometrics: Methods and Applications. Cambridge University Press, 2005.

Statistical programming:

- Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer. Introduction to Econometrics with R, 2021. (E-book)
- Florian Heiss. Using R for Introductory Econometrics. Second edition, 2020. (E-book)

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mi 01.03.2023 09:48