The analysis of integrated and co-integrated time series can be considered as the main methodology employed in applied econometrics. This book not only introduces the reader to this topic but enables him to conduct the various unit root tests and co-integration methods on his own by utilizing the free statistical programming environment R. The book encompasses seasonal unit roots, fractional integration, coping with structural breaks, and multivariate time series models. The book is enriched by numerous programming examples to artificial and real data so that it is ideally suited as an accompanying text book to computer lab classes.

The second edition adds a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models. To analyze the interactions between the investigated variables, further impulse response function and forecast error variance decompositions are introduced as well as forecasting. The author explains how these model types relate to each other.

Ideally suited for computer labs: Econometric theory/methods and their implementation within R is exhibited Self-contained: The book can be used for self-study; code examples are elaborated Wide audience is addressed: Upper-undergraduate/Graduate students and practitioners Includes supplementary material: sn.pub/extras

Autorentext
Bernhard Pfaff studied economics at the universities of Göttingen, Germany; Davis, California; and Freiburg im Breisgau, Germany. He obtained a diploma and a doctorate degree at the economics department of the last one where he was employed as a research and teaching assistant. He has worked for many years as economist and quantitative analyst in research departments of financial institutions. Bernhard Pfaff is the author and maintainer of the contributed R package "urca".

Klappentext

This book is designed for self study. The reader can apply the theoretical concepts directly within R by following the examples.

Zusammenfassung
The book is enriched by numerous programming examples to artificial and real data so that it is ideally suited as an accompanying text book to computer lab classes.The second edition adds a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models.

Inhalt
Theoretical Concepts.- Univariate Analysis of Stationary Time Series.- Multivariate Analysis of Stationary Time Series.- Non-stationary Time Series.- Cointegration.- Unit Root Tests.- Testing for the Order of Integration.- Further Considerations.- Cointegration.- Single-Equation Methods.- Multiple-Equation Methods.