WiSo-Graduate School UHH: Applied univariate and multivariate time series analysis

Institution: Graduate School at Faculty of Business, Economics and Social Sciences – Universität Hamburg

Lecturer: Prof. Dr. Ulrich Fritsche (WiSo-Fakultät, UHH)

Schedule:
Di., 21.02.2017, 09:00 – 17:00 Uhr
Mi., 22.02.2017, 09:00 – 15:00 Uhr
Do., 23.02.2017, 09:00 – 17:00 Uhr
Fr., 24.02.2017, 09:00 – 15:00 Uhr

Place: Universität Hamburg, further information in Geventis

Registration: You can register for the course until 30.09.2016 (13 Uhr) via Geventis

Course description:
Roadmap:

  1. Basics: Difference Equations, Solutions, Lag Operators
  2. Stationary Time-Series Models: ARMA (p,q), ACF/PACF, Box-Jenkins
  3. Identification Problems in Macroeconometrics
  4. Models with Trend: Dickey-Fuller-Test, Structural Change, Panel UnitRoot tests
  5. Cointegration and Error-Correction Models
  6. Some Non-linear Time-Series Models

Lernziel:

Students will be enabled to apply macro econometric techniques to avariety of cases. Students are encouraged to bring their own problems and data sets to analyze them in the course.Students will be enabled to use the software RATS.

Vorgehen:

The course is a mixture of lectures, practical exercises and programmingRATS code and own empirical work.

Literatur:

Basic References:

  • @1: Enders (2010), ch. 1;Kirchgässner, Wolters (2007), ch. 1.
  • @2: Enders (2010), ch. 2;Kirchgässner, Wolters (2007), ch. 2.
  • @3: Favero (2001), ch. 3, ch.4, ch. 6; Kirchgässner, Wolters (2007), ch. 4; Enders (2010)3, ch. 5.
  • @4: Enders (2010), ch. 4;Kirchgässner, Wolters (2007), ch. 5.
  • @5: Enders (2010), ch. 6;Kirchgässner, Wolters (2007), ch. 6.
  • @6: Enders (2010), ch. 7.

Books:

  • Walter Enders (2010): Applied Econometric Time Series, 3rd edition,Wiley.
  • Carlo A. Favero (2001): Applied Macroeconometrics, Oxford UniversityPress.
  • Gebhard Kirchgässner, JürgenWolters (2007): Introduction to Modern Time Series Analysis, Springer.
  • RATS: www.estima.com

Zusätzliche Hinweise zu Prüfungen:

Students will work on empirical projects (either own projects or tasks defined in the course). A written documention of the empirical project will be graded.