Time Series Analysis (previously: Econometrics I)

Time I: 
Monday, 02:00pm to 04:00pm
Time II: 
Tuesday, 12:00pm to 02:00pm
Venue I: 
Spandauer Straße 1, room 22; Empirical Tutorials take place at room 025 (Mon)
Venue II: 
Spandauer Straße 1, room 203

The course aims at providing the basic concepts and methods for analysing time series data. The focus is on univariate modelling tools. The lecture begins with classical components models. Then we cover different types of stochastic processes like ARIMA and GARCH models, deal with the unit root methodology and procedures for forecasting as well as for the specification, estimation and validation of models. Multivariate extensions are demonstrated, with emphasis on vector autoregressive (VAR) processes and its application in causality and impulse response analyses. Nonstationary systems with integrated and cointegrated variables will also be treated.

In the tutorials the time series methods are applied to empirical data. We will intensively make use of econometric software packages. A deeper insight into advanced methods and additional topics is offered by means of assignments, empirical studies and/or literature reviews.

- Hamilton (1994). Time Series Analysis. Princeton, University Press.
- Schlittgen/Streitberg (2001). Zeitreihenanalyse. Oldenburg Verlag, München.
- Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer
Verlag, Heidelberg.
Exam: written exam (90 min)

Spring 2017
Humboldt-Universität zu Berlin
End date of the whole course: 
Tuesday, July 18, 2017 - 2:00pm