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)
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.