Course descriptions for the winter semester 2015/2016


040131 Introductory econometrics


UK, 4 hours per week (8 ECTS)


Language of instruction: English


Time and location:


Monday, 16:45-18:15, Hörsaal 6, Oskar Morgenstern Platz

Wednesday, 18:30-20:00, Hörsaal 6, Oskar Morgenstern Platz


(at some dates different rooms and times)


Starts: October 5, 2015


Course description: The course provides an introduction to the most common statistical methods that are used in empirical economics. This includes linear regression (ordinary least squares, generalized least squares, instrumental variables) and the corresponding hypothesis tests (restriction tests as well as diagnostic tests). The basic literature used for the course is Jeffrey M. Wooldridge: Introductory Econometrics (South-Western, 4th edition). The methods are highlighted in empirical applications using Stata.


Plan of the course: Assessment is based on three written tests in the last units of October, November, and January. No alternative dates for these tests can be provided. The tests carry increasing weights of 25 %, 35 %, 45 % in the final grade (which includes a 5 % bonus). A positive grade requires at least 50 % of the maximum achievable score of 100 and attendance at the first written test. Dropping the course without a grade is not possible after the first written test.



040064 Forecasting


UK, 2 hours per week (4 ECTS)


Language of instruction: English


Time and location:


Tuesday, 13:15-14:45, Hörsaal 5, Oskar Morgenstern Platz


Starts: October 6, 2015


Course description: The course aims at an understanding of currently used techniques for prediction in empirical economics. We focus 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) Forecasting using econometric models

(6) Criteria for assessing forecasting accuracy


In line with the course form UK, the evaluation should be based on several parts. The course grade is determined by a weighted average of a written test (in early December, 40 %) and a lesser empirical forecasting project or a short presentation of some advanced piece of literature that is related to econometric forecasting (60 %). Presentations take place in the time after the written test. For empirical projects, presentations are not mandatory but they carry an additional 5 % bonus.


Recommended literature for this course:

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.



390055 Econometrics of Seasonality (PhD-E)


UK, 2 hours per week (4 ECTS)


Language of instruction: English


Time and location:


Monday, 11:30-13:00, Seminarraum 3, Oskar Morgenstern Platz


Starts: October 5, 2015


Description of course contents:

This course focuses on the topic of seasonality in time series. It is based on the monograph “The Econometric Analysis of Seasonal Time Series” by Eric Ghysels and Denise R. Osborn (Cambridge University Press, 2001). Another related book is Philip H. Franses and Richard Paap: “Periodic Time Series Models” (Oxford University Press, 2004). In particular, the following issues will be addressed:

1.     Introduction to seasonal processes (basic concepts of diverse models of seasonality)

2.     Deterministic seasonality (seasonal dummies, tests with dummy seasonality as the null hypothesis, e.g. the Canova-Hansen test)

3.     Seasonal unit-root processes (seasonal random walk, tests with complex unit roots as their null, e.g. the HEGY test)

4.     Periodic models

5.     Seasonal adjustment


The definite form of this course will be determined in the preliminary meeting and it may also depend on the number of participants. A suggestion is as follows. In the first half of the term, the instructor will present the topics listed above. In early December, this part closes with a short midterm test (45% weight in the final grade). In the second half of the term, participants take over and give presentations. The topics of these presentations can be a more advanced analysis of already addressed topics, parts of the monographs that have not yet been covered, or small empirical projects on seasonal data. Presenters will turn in written summaries of their work by the end of the term. This part carries 55% weight in the final grade.


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