Universität Wien
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040211 KU Forecasting (MA) (2021W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
ON-SITE

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

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

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

Information

Aims, contents and method of the course

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

Assessment and permitted materials

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.

Minimum requirements and assessment criteria

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

Examination topics

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

Reading list

- 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

Association in the course directory

Last modified: We 06.10.2021 18:48