[R-SIG-Finance] Granger Causality Test
markleeds at verizon.net
markleeds at verizon.net
Thu Aug 14 00:01:05 CEST 2008
i think your two statements deserve separate answers.
granger causailty is only used ( as far as i know ) in the context of
deciding on which variables in a previusly estimated VAR cause another
in the granger sense. ( defined in Lutkepohl ) . But, since it's a n
already estimated VAR, you should have already decided whether the
series under study needed to be differenced or not in order that the VAR
estimation is done on variables that are stationary.
So, granger causality doesn't really have much to do with stationarity,
I don't think, because that should have been worked out during the
estimation fo the VAR.
in the 70's before cointegration was discovered, people used to
difference time series variables in order to make them stationary (
for example , if they were prices, they would make them differenced
prices ). but, it was realized that, if one did this, then the
information about levels of the
series was lost and it was always felt that there must be a better
approach so the levels info was not abruptly discarded.
then, engle and granger figured out in the early 80's that there were
cases where two variables could be non-stationary and yet
the regression of the two on each other could still be valid
statistically ( cointegration ). So, they were able to figure out a way
keep the levels in the specification by rewriting the regression
relationship in the form of an error correction model. This was then
extended beyond the
bivariate case to what is called a vector-error correction model ( VECM
) which is like a VAR but slightly different and I couldn't do the
description of a VECM justice even if i tried so I won't.
There is a lot of econometrics literautre in this area that talks about
this in a much more eloquent way than I could.
Some good books in order of increasing difficulty ( atleast to me ).
Zivot ( S+Finmetrics book )
To me, Hamilton and Lutkpohl are similar in difficulty and require a
larger time investment than the others. Enders is the most basic but it
gives nice intuition and is good for an intro. Zivot is more general in
that it covers various time series topics but also provides a brief but
nice discussion on the topics above.
On Wed, Aug 13, 2008 at 5:23 PM, Hsiao-nan Cheung wrote:
> I have some question that whether only stationary series could do
> Causality Test. Is there any exception?
> Since I��ve found somewhere that to make a time series stationary, the
> differential series may has little economic meaning.
> Hsiao-nan Cheung
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