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 this link.

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.

- Schlittgen, Rainer, Bernhard Pfaff Analysis of Integrated
and Cointegrated Time Series with R,
*Allgemeines Statistisches Archiv*, 2006, 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., 2006,
Vol.
**26**(2). - Harvill, J.L. (2007), Analysis of Integrated and Cointegrated
Time Series with R,
*JASA*, 2007,**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.

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