Course descriptions for the winter semester 2014

 

040131 Introductory econometrics

 

UK, 4 hours per week (8 ECTS)

 

Language of instruction: English

 

Time and location:

 

Monday, 15:00-16:30, Hörsaal 14, Oskar Morgenstern Platz

Wednesday, 16:45-18:15, Hörsaal 14, Oskar Morgenstern Platz

 

(at some dates different rooms and times)

 

Starts: October 6, 2014

 

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, 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 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 7, 2014

 

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.