Course
descriptions for the winter term 2009/2010
040131 UK Einführung in die empirische
Wirtschaftsforschung
UK, 2 Wochenstunden
Zeit und Ort:
Montag 14:30–16:00 Hörsaal 23, Hauptgebäude
Beginn: Montag, 5. Oktober 2009
Beschreibung
des Kurses: Die
Studierenden sollen in leicht fasslicher Form mit den Methoden und Begriffen
empirischen ökonomischen Arbeitens bekannt gemacht werden. Als Grundlage möge
das Lehrbuch von Ramu Ramanathan "Introductory Econometrics with Applications" (5th edition, South-Western) dienen. Das Buch enthält eine
umfangreiche Sammlung von Daten und Anwendungsbeispielen. Der Kurs bereitet
auch auf das eigenständige empirische Arbeiten in Praktika vor.
Aufbau des Kurses:
Ökonometrisches Arbeiten, Streudiagramme, Modell, Parameter, Schätzen und Testen
Einfaches lineares Regressionsmodell (Kleinstquadrateschätzung OLS, R², t-Statistiken)
Multiples lineares Regressionsmodell (R², Modellauswahl, F-Statistiken, Multikollinearität)
Gebräuchliche Spezifikationstests (Durbin-Watson u.a.)
Leistungsfeststellung durch schriftliche Teilprüfung während des Semesters (midterm, 50%) und schriftlichen Abschlusstest (50%) am Ende des Semesters.
040787
UK Applied Time Series Analysis
UK, 2
hours per week
Time
and location:
Monday, 16:30–18:30 Seminarraum 1 Hohenstaufengasse
9 1.Stock
First
meeting: Monday,
October 5, 2009
Course description: This course focuses on time-series analytic methods that are
empirically relevant in current economics. Two main issues are:
Linear models for stationary variables
(definitions of stationarity, correlogram,
ARMA model, information criteria)
Models for difference-stationary variables
(integration and cointegration, Dickey-Fuller test,
Johansen procedure)
All
methods will be illustrated through empirical examples and printouts obtained
using econometric software.
The definition of the UK course requires the
course grade to be based on two or more partial elements. A suggestion would be
to organize a written test before Christmas (50% weight) and additionally ask
participants to work out a small empirical project using time-series methods
(50% weight). The empirical project may be elaborated in groups of up to three
persons and can be presented in class in January. The written version will be
graded and should be in by January 31. The definitive organization will be
convened in the first units and may also depend on the number of participants.
Participants
are assumed to have some basic knowledge of econometric methods.
A
time-series textbook popular with economists is Hamilton: "Time Series
Analysis" (Princeton). A clear presentation of the basic issues is
also contained in Brockwell and Davis:
"Introduction to Time Series and Forecasting" (Springer).
040789
UK Non-linear Time Series Analysis
UK, 2
hours per week
Time
and location:
Tuesday, 9:00–11:00, Seminarraum 2, Hohenstaufengasse
First
meeting: Tuesday,
October 6, 2009
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):
Threshold models (SETAR, threshold autoregressions)
ARCH and GARCH models (conditional heteroskedasticity)
Bilinear models
The first course units are
devoted to a short introduction and repetition of linear time-series models,
comparable to Chapter 2 of the Fan & Yao textbook, then the basic features
of the three classes above are addressed. A written test should close this part
of the course and carries 50% of the grade.
The remaining 50% of the
course grade are based on contributions by participants, typically in the shape
of a smaller working project that applies methods of nonlinear time-series
analysis. An alternative suggestion would be a presentation of a topic related
to nonlinear time series that could not be covered in the course otherwise. All
projects should be presented before class and their written versions should be
handed in by January 31, 2010.
Participants
are assumed to have some basic knowledge of econometric and time-series
methods.