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! -- 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.
How to transform OLS covariance matrix to White standard errors?
2 messages · Dunken, David Winsemius
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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