**Course descriptions for the summer
semester 2013**

**040027 Advanced Econometrics**

UK,
4 hours per week (8 ECTS)

Language of instruction: **English**

**Time and location:**

Tuesday
11:00-12:30 Seminarraum 1 Hohenstaufengasse
9

Thursday 11:30-13:00 Hörsaal 26 Hauptgebäude

**Starts**: March 5, 2013

**Course description: **The course focuses on econometric
methods whose knowledge is expected at the Master level, but which are not
covered in the econometric core instruction. In particular, time-series methods
such as unit-root testing and cointegration analysis
are in focus, as well as some extension to panel data. Thus, the course
material corresponds roughly to the sections 8 to 10 of the textbook by **Verbeek****: A Guide to Modern Econometrics (Wiley, 4 ^{th}
edition 2012)**. The methods are highlighted in empirical applications in Stata.

**Plan of the course**: The definitive plan will be convened in the first
unit and may depend on the number of participants. A suggestion is that the
course grade comprises two tests (35% each) and an empirical project (30%) that
can be done in groups of up to three persons. The second test should be in
early June, such that participants can focus on their project afterwards.

**390022 PhD-E: Working with panel data**

UK, 2 hours per week (4 ECTS)

Language
of instruction: **English**

**Time and location:**

Friday 11:30-13:00 Prominentenzimmer Hauptgebäude, Tiefparterre

**Starts**: March 1, 2013

**Course description**: The lecture course surveys econometric techniques
that are used on two-dimensional data sets, one dimension of which is time.
Such data sets, generally named panels or sometimes longitudinal data, occur in
macroeconomics, for example in inter-country comparisons, where the time
dimension dominates, as well as in labor economics, where a short time
dimension and a large cross-section dimension is the rule.

The following topics could be
covered:

Models for panel data (fixed and random
effects, one-way and two-way)

Estimation procedures for panels (LSDV or
within-groups estimator, GLS)

Tests (poolability,
Hausman test)

Heteroskedasticity and autocorrelation

Dynamic panels (Nickell
bias, instrumental variable estimation)

Panel tests for unit roots

The methods are explained
using empirical examples that use the by computer software Stata.
As important literature related to this course, I would recommend the textbooks
by **Hsiao: Analysis of Panel Data** (Cambridge University Press, 2003) and
by **Baltagi****: Econometric Analysis of Panel
Data** (Wiley, 2005).

In line with the course form
UK, the allocation of grades to participants is to be composed of several
parts. The definitive form will be convened at the first meeting. It may also
depend on the number of participants. In recent comparable courses, the course
grade was a weighted average of a written test (40%) in May, and of a
presentation of an advanced topic from the above list or of an independent empirical
project on panel data (60%). For the latter point, joint work in groups of two
or three participants is encouraged. Grades will be based on the written report
of the presented project to be submitted by the end of the course. For
literature presentations, the report may consist of elaborate presentation
slides. For empirical projects, the report will indicate clearly the aim of the
project and its potential conclusions. Printouts of software results or screen
shots are not acceptable as reports.

**390022 PhD-E: Non-linear Time Series Analysis**

UK,
2 hours per week (4 ECTS)

Language
of instruction: **English**

**Time and location:**

Tuesday,
14:00-15:30 Seminarraum 2 Hohenstaufengasse
9

**Starts**: March 5, 2013

**Course description: **While the
supply of nonlinear time-series models is almost limitless, this course will focus
on three parametric model classes that are used in empirical economics and are
treated in the monograph by **Fan & Yao: Nonlinear time series**
(Springer 2005, Chapter 4):

**Fan & Yao** or from comparable monographs, in particular:

**Teräsvirta****, Tjostheim, and Granger: Modelling
Nonlinear Economic Time Series (Oxford University Press, 2010)**

Written versions of all presentations should be handed in by
June 30, 2013.