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Editors-in-chief: Bettina GrĂ¼n, Edzer Pebesma & Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
VAR, SVAR and SVEC Models: Implementation Within R Package vars | Pfaff | Journal of Statistical Software
Authors: Bernhard Pfaff
Title: VAR, SVAR and SVEC Models: Implementation Within R Package vars
Abstract: The structure of the package vars and its implementation of vector autoregressive, structural vector autoregressive and structural vector error correction models are explained in this paper. In addition to the three cornerstone functions VAR(), SVAR() and SVEC() for estimating such models, functions for diagnostic testing, estimation of a restricted models, prediction, causality analysis, impulse response analysis and forecast error variance decomposition are provided too. It is further possible to convert vector error correction models into their level VAR representation. The different methods and functions are elucidated by employing a macroeconomic data set for Canada. However, the focus in this writing is on the implementation part rather than the usage of the tools at hand.

Page views:: 43188. Submitted: 2007-05-07. Published: 2008-07-29.
Paper: VAR, SVAR and SVEC Models: Implementation Within R Package vars     Download PDF (Downloads: 43674)
Supplements:
vars_1.4-0.tar.gz: R source package bundle Download (Downloads: 3066; 455KB)
v27i04.R.zip: v27i04.R: R example code from the paper Download (Downloads: 3401; 1KB)

DOI: 10.18637/jss.v027.i04

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.