Dirk Eddelbuettel

English

Research Papers in Economics

JSS Journal of Statistical Software
April 2009, Volume 30, Book Review 5. http://www.jstatsoft.org/
Reviewer: Dirk Eddelbuettel
Debian Project
Analysis of Integrated and Cointegrated Time Series with R (2nd Edition)
Bernhard Pfa
Springer-Verlag, New York, NY, 2008.
ISBN 978-0-387-75966-1. 188 pp. USD 54.95.
http://www.pfaffikus.de/springer.html
Analysis of Integrated and Cointegrated Time Series with R (2nd Edition) by Bernhard Pfa
oers a rigorous introduction to unit roots and cointegration, along with numerous examples
in R to illustrate the various methods.
The book, now in its second edition, provides an overview of this active area of research in time
series econometrics. It manages to be thorough (using formal notation), yet remains applied
in its focus. A number of examples are discussed, often by using datasets from the origi-
nal publications. Code examples are provided throughout, frequently using the contributed
packages urca and vars by the same author.
The book is compromised of three parts that build on top of each other. The rst part,
entitled Theoretical Concepts, contains four chapters that review the mathematical back-
ground material. The reader is re-acquainted with the most important notations concerning
stationary time series, rst univariate and then multivariate series introducing vector autore-
gressive models (VAR) and structural vector autoregressive models (SVAR). The coverage of
the material is fairly technical at about the textbook level. Next, the background material
for non-stationary time series is discussed before a review of cointegration ends the rst part.
The second part is devoted to unit root testing. The ve standard tests|from the initial
approach by Dickey and Fuller to Phillips and Perron, followed by the methods of Elliot,
Rothenberg and Stock as well as Schmidt and Phillips before concluding with the test by
Kwiatkowski, Phillipp, Schmidt and Shin|are reviewed in some detail in the fth chapter
before the sixth chapter discusses related topics such as structural breaks and tests for seasonal
unit roots.
The third and nal part covers cointegration. It starts with a discussion of the single-equation
case and covers the two main approaches by Engle and Granger, and by Phillips and Ouliaris,
respectively. The main part of the chapter discusses multi-equation methods including vector
error correction models (VECM). The Johansen and Juselius maximum-likelihood approach
is covered is detail. Structural breaks and shifts in the data are discussed, as are structural
vector error correction models.2 Analysis of Integrated and Cointegrated Time Series with R (2nd Edition)
Overall, this books is a very welcome addition to the Use R! series as it provides a thorough
overview of unit root and cointegration methods. Pfa, as the author of urca and vars, the two
principal R packages in this area, provides the reader with both the theoretical and practical
tools to study and replicate the seminal works in the area, and to apply these methods to
new data sets. The second edition also adds new material on VAR and SVAR models which
strengthens the coverage of multivariate methods.
The only major shortcoming of the book may be its formal writing style which is too reminis-
cent of a lecture notes title. Additional case studies based on publicly available data sets could
have loosened up the presentation by providing application examples. Despite this omission,
the book can clearly be recommended to both researchers and practitioners in time series
econometrics.
Reviewer:
Dirk Eddelbuettel
Debian Project
Chicago, IL, United States of America
E-mail: edd@debian.org
URL: http://dirk.eddelbuettel.com/
Journal of Statistical Software http://www.jstatsoft.org/
published by the American Statistical Association http://www.amstat.org/
Volume 30, Book Review 5 Published: 2009-04-27
April 2009

Analysis of Integrated and Cointegrated Time Series with R (2nd Edition)

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Research Papers in Economics