Universität Wien

040122 UK Applied Econometrics 2 (2024S)

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

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

  • Dienstag 07.05. 13:15 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 14.05. 13:15 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 21.05. 13:15 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 23.05. 13:15 - 14:45 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 28.05. 13:15 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 04.06. 13:15 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 06.06. 13:15 - 14:45 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 11.06. 13:15 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 13.06. 13:15 - 14:45 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 18.06. 13:15 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 20.06. 13:15 - 14:45 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Dienstag 25.06. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 27.06. 13:15 - 14:45 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Ziele und Inhalte
Ziel des Kurses ist es, den Studierenden ein Verständnis der theoretischen Grundlagen und der richtigen Anwendung der instrumentellen Variablenschätzung und ökonometrischer Techniken für Paneldaten und mikroökonometrische Daten zu vermitteln. Der Kurs behandelt die Methode der Zweistufige kleinsten Quadrate, spurious Regression, Fixed-Effects- und Random-Effects-Panel-Schätzung sowie ökonometrische Modelle für kategoriale Daten und für begrenzte abhängige Variablen.
Beispiele und Anwendungen werden anhand der Open-Source-Software R veranschaulicht. In einem begleitenden Tutorium vertiefen die Studierenden den Stoff anhand von Übungen und Anwendungen mit R.
Alle notwendigen Informationen und mögliche kurzfristige Ankündigungen werden über die Moodle-Seite des Kurses bereitgestellt.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Assessment
The assessment consists of the following parts:

(i) Three Exams, a 45 min:
Part I, June 4, 2024, (HS 1, 13:15-14:00), on the correspond. topics covered in the course.
Part II, June 25, 2024 (HS 1 13:15-14:00); on the corresponding topics covered in the course.
Part III, June 27, 2024 (HS 4, 13:15-14:00); 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. Hence, it is necessary to have your laptops with you!

ii) Take-home assignments. Students have to solve and have to hand in written assignments. They can consist of multiple-choice questions, analytical derivations, and interpretations of empirical results. Solved exercises have to be uploaded to the Moodle system before the start of the exercise part on Tuesday, no matter whether you choose to attend the exercise part Tuesday or on Thursday.

Necessary material for (i-iii): you need a laptop, for all exams moodle will be used.

Grading:
For the final grade the individual assignments count as follows:
i) Three exams: 75%, 25% each
ii) Assignments: 25%
iii) 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, a minimum level of 50% has to be reached.

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

Examination language: Students can do the examinations in English.

Mindestanforderungen und Beurteilungsmaßstab

Assessment
The assessment consists of the following parts:

(i) Three Exams, a 45 min:
Part I, June 4, 2024, (HS 1, 13:15-14:00), on the correspond. topics covered in the course.
Part II, June 25, 2024 (HS 1 13:15-14:00); on the corresponding topics covered in the course.
Part III, June 27, 2024 (HS 4, 13:15-14:00); 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. Hence, it is necessary to have your laptops with you!

ii) Take-home assignments. Students have to solve and have to hand in written assignments. They can consist of multiple-choice questions, analytical derivations, and interpretations of empirical results. Solved exercises have to be uploaded to the Moodle system before the start of the exercise part on Tuesday, no matter whether you choose to attend the exercise part Tuesday or on Thursday.

Necessary material for (i-iii): you need a laptop, for all exams moodle will be used.

Grading:
For the final grade the individual assignments count as follows:
i) Three exams: 75%, 25% each
ii) Assignments: 25%
iii) 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, a minimum level of 50% has to be reached.

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

Examination language: Students can do the examinations in English.

Prüfungsstoff

1. Instrumentvariablen
2. Paneldatenmodelle
3. Modelle für qualitative und beschränkte abhängige Variablen

Literatur

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

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mi 31.07.2024 11:25