Re: [R] cointegrating regression

From: Adrian Trapletti (adrian@olsen.ch)
Date: Fri 16 Feb 2001 - 18:33:36 EST

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Message-ID: <3A8CE5E0.65EC90D5@olsen.ch>

> Date: Thu, 15 Feb 2001 15:48:38 +0100
> From: "Fredrik Berchtold"
> Subject: [R] cointegrating regression
>
> Hi all,
> Can I run a cointegrating regression, for example
> delta Xt=a1(Yt-1-cXt-1)+E1t
> and
> delta Yt=-b1(Yt-1-cXt-1)+E2t
> with R were
> Xt and Yt are non stationary time series at t
> a,b,c are parameters and E1t and E2t are error terms at t.
> Yt-Xt is stationary
> Any suggestions are welcome.
> Best regards,
> /fb
>

E.g., you can do that in three steps:
1. Test if x and y are cointegrated, e.g., using po.test() in tseries.
2. If cointegrated, run the regression r<-lm(y~x).
3. let z<-ts.union(diff(x),diff(y)) and xreg<-residuals(r),
xreg<-xreg[1:(length(xreg)-1)]
Run arima0(z,xreg=xreg,order=c(var.order,0,0)).

This corresponds to the so called Engle-Granger two-step procedure.

best
Adrian

--
Dr.  Adrian Trapletti,  Olsen  &  Associates Ltd.
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