R help - Aug 2010 - Fitting VAR and doing Johansen's cointegration test in R

Hi,

Could someone please tell me the R codes for fitting VAR(p) (Vector
Auto Regressive) models and doing the Johansen?s cointegration tests.

TIA
Aditya

Look at the econometrics and time series  Task wiew on the CRAN web site

John

On 23 August 2010 04:09, Aditya Damani <adicool4u at gmail.com>
wrote:
> Hi,
>
> Could someone please tell me the R codes for fitting VAR(p) (Vector
> Auto Regressive) models and doing the Johansen?s cointegration tests.
>
> TIA
> Aditya
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>


-- 
John C Frain
Economics Department
Trinity College Dublin
Dublin 2
Ireland
www.tcd.ie/Economics/staff/frainj/home.html
mailto:frainj at tcd.ie
mailto:frainj at gmail.com

Am 23.08.2010 05:09, schrieb Aditya Damani:
> Hi,
>
> Could someone please tell me the R codes for fitting VAR(p) (Vector
> Auto Regressive) models and doing the Johansen?s cointegration tests.
>
> TIA
> Aditya
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
Just feeling like doing some homework for free...

require(vars)
require(urca)
reps <- 1000 # length of time series
A <- matrix(NA,nrow=reps,ncol=3)
colnames(A) <- c("a","b","c")
A[1,] <- rnorm(3) # starting values
for(i in 2:reps){# generate time series
A[i,] <- c(0.1+0.2*i+0.7*A[i-1,1]+0.1*A[i-1,2]+0.1*A[i-1,3]+rnorm(1),
            0.5+0.1*i+0.6*A[i-1,2]-0.2*A[i-1,1]-0.2*A[i-1,3]+rnorm(1),
            0.9+0.2*i+A[i-1,3]+0.1*A[i-1,1]+0.15*A[i-1,2]+rnorm(1)
           )
}
(a.ct <- ur.df(A[,"a"],type="trend"))
(b.ct <- ur.df(A[,"b"],type="trend"))
(c.ct <- ur.df(A[,"c"],type="trend"))

VARselect(A,type="both")
var.p1 <- VAR(A,1,type="both")
summary(var.p1)
jo <- ca.jo(A)
summary(jo)


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