<p><br/></p><p>Analysis of Integrated and Cointegrated Time Series with R (2nd_2008)&nbsp; 2008 Springer</p><p>Preface to the Second Edition</p><p>A little more than two years have passed since the first edition. During this<br/>time, R has gained further ground in the domain of econometrics. This is witnessed<br/>by the 2006 useR! conference in Vienna, where many sessions were<br/>devoted entirely to econometric topics, as well as the Rmetrics workshop at<br/>Meielisalp 2007. A forthcoming special issue of the Journal of Statistical Software<br/>will be devoted entirely to econometric methods that have been implemented<br/>within R. Furthermore, numerous new packages have been contributed<br/>to CRAN and existing ones have been improved; a total of more than 1200<br/>are now available. To keep up with these pleasant changes, it is therefore necessary<br/>not only to adjust the R code examples from the first edition but also<br/>to enlarge the book’s content with new topics.</p><p>However, the book’s skeleton and intention stays unchanged, given the<br/>positive feedback received from instructors and users alike. Compared with<br/>the first edition, vector autoregressive (VARs) models and structural vector<br/>autoregressive (SVARs) models have been included in an entire new chapter<br/>in the first part of the book. The theoretical underpinnings, definitions, and<br/>motivation of VAR and SVAR models are outlined, and the various methods<br/>that are applied to these kinds of models are illustrated by artificial data sets.<br/>In particular, it is shown how swiftly different estimation principles, inference,<br/>diagnostic testing, impulse response analysis, forecast error variance decomposition,<br/>and forecasting can be conducted with R. Thereby the gap to vector<br/>error-correction models (VECMs) and structural vector error-correction<br/>(SVEC) models is bridged. The former models are now introduced more thoroughly<br/>in the last chapter of the first part, and an encompassing analysis in<br/>the context of VEC/SVEC modeling is presented in the book’s last chapter.<br/>As was the case for the first edition, all R code examples presented can be<br/>downloaded from <a href="http://www.pfaffikus.de">http://www.pfaffikus.de</a>.</p><p></p>