Universität Wien
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040327 KU Introductory Econometrics (MA) (2025S)

8.00 ECTS (4.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung
VOR-ORT
Mo 03.03. 11:30-13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock

Details

max. 200 Teilnehmer*innen
Sprache: Englisch

Lehrende

    Termine (iCal) - nächster Termin ist mit N markiert

    • Donnerstag 06.03. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Montag 10.03. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Donnerstag 13.03. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Montag 17.03. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Donnerstag 20.03. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Montag 24.03. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Donnerstag 27.03. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Montag 31.03. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Donnerstag 03.04. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Freitag 04.04. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
    • Montag 07.04. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Donnerstag 10.04. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Montag 28.04. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Freitag 02.05. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
    • Dienstag 06.05. 15:00 - 16:30 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
      Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
    • Montag 12.05. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Donnerstag 15.05. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Freitag 16.05. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
    • Montag 19.05. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Donnerstag 22.05. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Montag 26.05. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Freitag 30.05. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
    • Montag 02.06. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Donnerstag 05.06. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Donnerstag 12.06. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Montag 16.06. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Freitag 20.06. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
    • Montag 23.06. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
      Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
    • Montag 30.06. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock

    Information

    Ziele, Inhalte und Methode der Lehrveranstaltung

    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, and big data among others.

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

    Art der Leistungskontrolle und erlaubte Hilfsmittel

    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 either failed (i.e., obtained less than 50%) or missed one of the two exams during the semester 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.

    Mindestanforderungen und Beurteilungsmaßstab

    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: English.

    Prüfungsstoff

    Examination Topics
    All material covered in the course.

    Literatur

    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.

    Zuordnung im Vorlesungsverzeichnis

    Letzte Änderung: Mi 15.01.2025 08:45