Springer

Description

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.

Content

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

Preface

The preface can be downloaded as pdf-file.

Sample Chapter

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

Reviews

First edition:

  • 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.

Second edition:

  • 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.