R help - May 2012 - How to transform OLS covariance matrix to White standard errors?

Hi!

I am working with a regression of a log-log model that suffers from
heteroskedasticity. I have calculated the "White standard errors". I
would
like to use these "White standard errors" in a RESET test instead of
the
originally OLS standard errors calculated by the regression. How can I
transform the covariance matrix of a model?


labmodel2 <- lm(formula = log(L) ~ log(W) + log(K) + log(Y), data=labordat)
sumlabmodel2 <- summary(labmodel2)
sumlabmodel2

coeftest(labmodel2,vcov=vcovHC(labmodel2,type="HC0"

That is, I want to replace vcov with vcovHC in labmodel2 to perform a RESET
test with the robust White standard errors.

Can anyone help?

Thank you!



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On May 26, 2012, at 3:09 AM, Dunken wrote:
> Hi!
>
> I am working with a regression of a log-log model that suffers from
> heteroskedasticity. I have calculated the "White standard
errors". I
> would
> like to use these "White standard errors" in a RESET test instead
of
> the
> originally OLS standard errors calculated by the regression. How can I
> transform the covariance matrix of a model?
>
>
> labmodel2 <- lm(formula = log(L) ~ log(W) + log(K) + log(Y),  
> data=labordat)
> sumlabmodel2 <- summary(labmodel2)
> sumlabmodel2
>
> coeftest(labmodel2,vcov=vcovHC(labmodel2,type="HC0"
>
> That is, I want to replace vcov with vcovHC in labmodel2 to perform  
> a RESET
> test with the robust White standard errors.
Have your read? :

"Econometric Computing with HC and HAC Covariance Matrix Estimators",
Achim Zeileis
http://www.jstatsoft.org/v11/i10/

>
> Can anyone help?
>
> Thank you!
>
>
>
> --
> View this message in context:
http://r.789695.n4.nabble.com/How-to-transform-OLS-covariance-matrix-to-White-standard-errors-tp4631432.html
> Sent from the R help mailing list archive at Nabble.com.
>
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