Universität Wien

040211 KU Forecasting (MA) (2021W)

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

http://homepage.univie.ac.at/robert.kunst/teaching.html
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

  • Donnerstag 07.10. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 14.10. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 21.10. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 28.10. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 04.11. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 11.11. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Donnerstag 25.11. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Donnerstag 02.12. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Donnerstag 09.12. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Donnerstag 16.12. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Donnerstag 13.01. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Donnerstag 20.01. 16:45 - 18:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

The course aims at an understanding of currently used techniques for prediction in empirical economics. It focuses on the following topics:

(1) General introduction (Aims of forecasting, types of forecasts: technical extrapolation, time-series forecasts, theory- and model-based forecasts)
(2) Technical model-free extrapolation (exponential smoothing, ad-hoc prediction etc.)
(3) Univariate time-series techniques (one variable on its own)
(4) Multivariate time-series techniques (several variables together: vector autoregressions, cointegration)
(5) Criteria for assessing forecasting accuracy

Art der Leistungskontrolle und erlaubte Hilfsmittel

A written closed-book test (40% weight) and a small empirical forecasting project (60%); a positive grade on the course requires taking part in the test and at least 50% of the maximum achievable score.
At this time, restrictions in place due to the virus situation in Austria are unknown. If necessary, tests will be virtual, on-line, and open-book.

Mindestanforderungen und Beurteilungsmaßstab

Participants are familiar with the main procedures that are currently used in empirical economic forecasting and also with the main issues of the related research field

Prüfungsstoff

Lectures and a small empirical project that is elaborated by participants, preferably in small groups of up to three participants

Literatur

- Michael P. Clements and David F. Hendry: Forecasting Economic Time Series. Cambridge University Press.
- Michael P. Clements and David F. Hendry: Forecasting Non-Stationary Economic Time Series. Cambridge University Press.
- Michael P. Clements: Evaluating Econometric Forecasts of Economic and Financial Variables. Palgrave-Macmillan.
- Philip H. Franses, Dick van Dijk, Anne Opschoor: Time Series Models for Business and Economic Forecasting. Cambridge University Press.
- Rob J. Hyndman and George Athanasopoulos: Forecasting: principles and practice. On-line open access.
- David Hendry, Jennifer Castle, Michael Clements: Forecasting

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mi 06.10.2021 18:48