Content
The course deals with econometric modelling, estimation, and testing of relationships and models for time series data with main focus on methods for handling non-stationary time series.
Necessary technical background will be established that includes introduction to stationarity and non-stationarity concepts, ARMA- and VAR-modelling, deterministic and stochastic trends, integrated and cointegrated variables, unit roots, identification and exogeneity. Consequences for estimation and interpretation of econometric models that may include non-stationary variables will be looked at. Both single relation methods and the multi-relation system approach will be discussed as well as statistical methods for estimating and determining the presence of one or more cointegrated relations among a set of economic time series.
In addition to discussing the importance of VAR-models for econometric modelling with special focus on autoregressive distributed lag- and error correction models, the course emphasizes applications concerning modelling, estimation, policy analysis and forecasting.
Literature
J.D. Hamilton, Time Series Analysis, Princeton University Press, 1994, Chapters, 1, 2, 3, 5.1-5.2, 10.1, 10.2, 10.5, 11, 15, 17.1-17.4, 17.6-17.8, 18.3, 19, 20
Supplementary reading:
W.H. Greene: Econometric Analysis, fourth edition. Prentice-Hall, 2003. Chapters 17.3-17.5, 18.1-18.4.
J. Johnston and J. DiNardo, Econometric Methods, McGraw-Hill, 1997, chapters: 7, 8, 9