Applied Time Series Econometrics (Themes in Modern Econometrics Series)

Book Description
Time series econometrics is used for predicting future developments of variables of interest such as economic growth, stock market volatility or interest rates. A model has to be constructed, accordingly, to describe the data generation process and to estimate its parameters. Modern tools to accomplish these tasks are provided in this volume, which also demonstrates by example how the tools can be applied.


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Time series econometrics is a rapidly evolving field and the cointegration revolution in particular has had a substantial impact on applied analysis. This work sketches out the methods of time series econometrics to remind the reader of the ideas underlying them and to give sufficient background for empirical work. Unit root and cointegration analysis play a central part. Other topics include structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. A crucial component in empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created that allows readers to replicate the applications and conduct their own analyses.


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