Universität Wien
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040033 KU Econometrics II (MA) (2022S)

10.00 ECTS (5.00 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. 50 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Lecture:
Dienstags (01.03.2022-28.06.2022) 15:00-16:30; Raum siehe Termine
Donnerstags (03.03.2022-30.06.2022) 15:00-16:30; Raum siehe Termine

Tutorial:
Donnerstags (03.03.2022-28.06.2022) 13:15-14:45; Raum siehe Termine

  • Dienstag 01.03. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 03.03. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 03.03. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 08.03. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 10.03. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 10.03. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 15.03. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 17.03. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 17.03. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 22.03. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 24.03. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 24.03. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 29.03. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 31.03. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 31.03. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 05.04. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 07.04. 08:00 - 09:30 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 07.04. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 26.04. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 28.04. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 28.04. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 03.05. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 05.05. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 05.05. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 10.05. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 12.05. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 12.05. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 17.05. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 19.05. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 19.05. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 24.05. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 31.05. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 09.06. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 09.06. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 14.06. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 21.06. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 23.06. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 23.06. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Dienstag 28.06. 15:00 - 16:30 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 30.06. 13:15 - 14:45 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Donnerstag 30.06. 15:00 - 16:30 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Freitag 01.07. 09:45 - 16:30 Seminarraum 8 Oskar-Morgenstern-Platz 1 2.Stock
    Seminarraum 9 Oskar-Morgenstern-Platz 1 2.Stock
    Seminarraum 9 Oskar-Morgenstern-Platz 1 2.Stock
  • Montag 18.07. 09:45 - 16:30 Seminarraum 8, Kolingasse 14-16, OG01
    Seminarraum 9, Kolingasse 14-16, OG01

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

This course provides students a deeper understanding of theory and practice of major parametric estimation and testing techniques in econometrics. The course will cover the class of extremum estimators and their asymptotic properties, with a special focus on (pseudo) maximum likelihood, nonlinear least squares as well as generalized methods of moments (GMM) estimation. Moreover, students will learn basic principles of bootstrap methods as well as simulation-based methods and (Bayesian) filtering techniques.
After following this course, students will have a good working knowledge of statistical inference as applied in various areas in modern econometrics, including time series econometrics, micro econometrics, panel econometrics as well as financial econometrics. In the tutorials, students will deepen the material based on exercises, examples and applications using the open-source software R.

The course will be taught in class. If required due to Covid regulations, the course will be done remotely via Zoom. All necessary information and possible short-term announcements will be provided through the Moodle site of the course.

Prerequisites
Students need to have basic econometric knowledge as taught in the course “Introductory Econometrics” or a similar course. Moreover, basic knowledge in R is required.

Sign-In
Students have to sign in during the first week of the semester. Signing off is only possible until at latest until March 15, 2022. Students who are still signed in after March 15, 2022 will be graded!

Art der Leistungskontrolle und erlaubte Hilfsmittel

The assessment consists of the following parts:

i) One small test, ca. 30 min, without or with short advance notice during the semester. Can consist of multiple-choice questions, analytical derivations and interpretations of empirical results. Depending on the pandemic situation, the tests might be done via Moodle.

ii) Exam, 60 min, on all topics covered in the course. Can consist of multiple-choice questions, analytical derivations and interpretations of empirical results. Depending on the pandemic situation, the exam might be carried out via Moodle. Depending on the number of course participants, part of the exams might be done in oral form during the first 2 weeks after the end of the term. The written part of the exam will take place during the regular lecture on 23.6. 2022.

iii) Take-home assignments. Students have to solve and have to hand in weekly or bi-weekly written assignments. They can consist of multiple-choice questions, analytical derivations and interpretations of empirical results. The solutions may also have to be presented in the tutorials.

Permitted material: No additional material except a calculator.

Mindestanforderungen und Beurteilungsmaßstab

Grading:
For the final grade the individual assignments count as follows:
i) Test: 20%
ii) Exam: 45%
iii) Assignments: 35%

Important: Aside from the three assignments, there will be no additional examination possibilities afterwards.

To pass the course, a minimum level of 45% has to be reached.

Rating:
[85%; 100%]: 1.0
[70%; 85%): 2.0
[55%;70%): 3.0
[45%; 55%): 4.0
[0; 45%): 5.0

Examination language: Students can do the examinations in English or German, but have to stick to one language.

Prüfungsstoff

All topics covered in the course

Literatur

Adda, J. and R. W. Cooper (2003): Dynamic Economics – Quantitative Methods and Applications. MIT Press.

Davidson, R. and J. MacKinnon (2004): Econometric Theory and Methods, Oxford University Press

Gouriéroux, C. and A. Monfort (1995): Statistics and Econometric Models, Cambridge University Press.

Gouriéroux, C. and A. Monfort (1996): Simulation-Based Econometric Methods, Oxford University Press.

Greenberg, E. (2008): Introduction to Bayesian Econometrics, Cambridge University
Press.

Hansen, Bruce E. (2019): Econometrics. Freely available at: http://www.ssc.wisc.edu/~bhansen/econometrics/

Hayashi, F. (2000): Econometrics, Princeton University Press.

Newey, W. K. (1993). “Efficient Estimation of Models with Conditional Moment Restrictions, “ Handbook of Statistics, 11, 419-453.

Newey, W. K. and D. McFadden (1994): “Large Sample Estimation and Hypothesis Testing”, in Handbook of Economtrics, e.d by R. F. Engle and D. L. McFadden, Elsevier, Chap. 36, 2111-2245.

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Di 14.06.2022 16:47