The analysis of integrated and co-integrated time series can be considered as the main methodology employed in applied econometrics. The 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. Within the second edition a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models have been added. To analyze the interactions between the investigated variables, further impulse response function and forecast error variance decompositions are introduced as well as forecasting have been included too. 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 R code examples for the first and second edition can be downloaded by following the links in the Examples section on this page. These R code examples are primarily based on the packages urca and vars.

This book was the first in
Springer's *Use R!* series and is now available in
its second edition. Aside from the other channels, the book can
directly be ordered from the publisher by following the link as
shown by the cover image on the top right.

The table of content can be downloaded as pdf-file.

The preface can be downloaded as pdf-file.

The second chapter is made available as a complimentary pdf-file and can be accessed from here.

The R code examples included in the first edition can be downloaded from here and the ones included in the second edition are made available by following this link.

__First edition:__

- Schlittgen, Rainer (2006), "Bernhard Pfaff Analysis of Integrated
and Cointegrated Time Series with R", Allgemeines Statistisches
Archiv , Vol.
**90**(3), 486-487. - O'Brian, C.M. (2006), "Analysis of Integrated and Cointegrated
Time Series with R", Publication of the International Statistical
Institute, Short Book Reviews, editor: Herzberg, A.M.,
Vol.
**26**(2). - Harvill, J.L. (2007), "Analysis of Integrated and Cointegrated
Time Series with R", JASA,
**102**(477), 389-90. - Reviews of the Week, 26, November 16, 2007, "Bernhard Pfaff Analysis of Integrated and Cointegrated Time Series with R", reprinted from Journal of Applied Statistics, October 2007.

__Second edition:__

- Eddelbuettel, D. (2009), "Analysis of Integrated and Cointegrated
Time Series with R (2nd Edition)", Journal of Statistical Software,
**30**(5), 1-2, URL: JSS. - Scott, D.J. (2009), "Analysis of Integrated and Cointegrated Time Series with R, Second Edition", International Statistical Review, 77(1), 164-165.

The errata of the first edition is provided as pdf-file and likewise the corrections for the second edition can be accessed by following this link.