Econometrics II - Time Series Analysis

The aim of the course is to enhance the students' capability to analyze economic time series data. It should help the participants to understand the concepts underlying some widely used univariate and multivariate time series models and to carry out their own empirical research by applying such models to economic questions.

Topics covered by the course include: stationary autoregressive moving average (ARMA) models, unit roots in ARMA models, vector autoregressive (VAR) models, (co-)integrated systems of time series, vector error-correction (VEC) models, structural VAR and structural VEC models, state-space models and the Kalman filter, regime switching models, dynamic panel models with large time dimension.

Literature: Hamilton (1994): Time Series Analysis, Princeton University Press; Lütkepohl (2006): New Introduction to Multiple Time Series Analysis, Springer Verlag; Greene (2008): Econometric Analysis, Pearson Education.