[R] How to transform OLS covariance matrix to White standard errors?

[Dunken]

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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