Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to 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, allowing readers to replicate the applications and conduct their own analyses.

A demonstration of how time series econometrics can be used in economics and finance.

1. Initial tasks and overview 2. Univariate time series analysis 3. Vector autoregressive and vector error correction models 4. Structural vector autoregressive modeling and impulse responses 5. Conditional heteroskedasticity 6. Smooth transition regression modeling 7. Nonparametric time series modeling 8. The software JMulTi