Universität Wien

040111 KU Introductory Econometrics (MA) (2021W)

8.00 ECTS (4.00 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. 100 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Dienstag 05.10. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 07.10. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 12.10. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 14.10. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 19.10. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 21.10. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 28.10. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 04.11. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 09.11. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 11.11. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 16.11. 16:45 - 18:15 Digital
  • Donnerstag 18.11. 16:45 - 18:15 Digital
  • Dienstag 23.11. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 25.11. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 30.11. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 02.12. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 07.12. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 09.12. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 14.12. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 16.12. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 11.01. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 13.01. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 18.01. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 20.01. 16:45 - 18:15 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 25.01. 16:45 - 18:15 Digital
  • Donnerstag 27.01. 16:45 - 18:15 Digital

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Aims and Contents
The course provides an understanding of basic 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.

The course emphasizes the application of econometric techniques as well as the
interpretation of models and outcomes of estimation and testing procedures. The students practice this by analyzing economic data by means of the open-source software R. They also learn to implement basic matrix-based formulas and to interpret theoretical results by simulating data generating processes and estimators based on small programming tasks in R. Econometric applications based on R will be illustrated in class and trained in tutorials accompanying the course.

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, among others.

Form of Teaching:
The course will be taught in a “hybrid” way. Lectures take place in the lecture hall and students can enter according to current Covid regulations. All students who cannot enter the lecture hall (due to covid regulations) can follow the course at the same time remotely via Zoom. Corresponding links will be provided on the Moodle site of the course.
If necessary due to Covid regulations, the lecture will be held in an entirely digital form via Zoom. Corresponding announcements will be done via Moodle.

Art der Leistungskontrolle und erlaubte Hilfsmittel

The assessment consists of the following parts:

i) 2 small tests, 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. In case of hybrid teaching, students, who cannot be present in class, have to do an equivalent test at the same time remotely via Moodle.

ii) Written exam, 60 min, 27.1. 2022, 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 (completely or partly) remotely via Moodle.

iii) Empirical take-home project, 21.2.-27.2. 2022. Students will receive datasets and have to perform econometric analyses in R in order to address certain economic questions. The analysis and results have to be documented in a research report (max. 7 pages), and R codes used in the study have to be uploaded. All results must be easily replicable in R. Students have to work remotely in groups of 3 or 4 persons (will be announced in due time depending on the number of students in the course). The effective working time corresponds approximately to one working day, but students have one week to perform the analysis. Download of data and instructions as well as upload of reports and R codes are performed through Moodle.

Permitted material: No additional material except a calculator.

Mindestanforderungen und Beurteilungsmaßstab

All material covered in class and in the tutorials.

Prüfungsstoff

Grading:
For the final grade the individual assignments count as follows:
i) 2 Tests: 25% each
ii) Exam: 50%
iii) Take-home project: 50%
Out of these three assignments, only the two best ones count for the final grade.

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

Literatur

Literature

Angrist, J.D. and Pischke, J.-S. (2009): Mostly Harmless Econometrics: An Empiricst's Companion, Princeton University Press.

Brockwell, P.J., and Davis, R.A. (2002): Introduction to Time Series and Forecasting, 2nd edition, Springer.

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.

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Fr 12.05.2023 00:12