Generally in the presence of heteroskedasticity of unknown form OLS
produces consistent estimates of your regression coefficients. The
estimates of standard errors are biased in the presence of
heteroskedasticity, White's procedure is a way of producing
consistent estimates of the standard errors. It does not change the
estimates of the coefficients. It does not change the residuals.
Patterns in your residuals may show up as heteroskedasticity when
tested but they may be an indication of wrong functional form or of
missing variables or of some other form of misspecification.
Best Regards
John
2009/2/10 Kishore <gladikish...@gmail.com>:
> Hi
> I am actually running the White test for correcting Heteroscedasticity. I
> used sandwich() & car(), however the output shows the updated t test of
> coefficients, with revised Standard Errors, however the estimates remained
> same. My problem is that the residuals formed a pattern in the original
> regression equation. After running the White's test, I got some new
> standard errors - but from here I didn't understand how to plot the
> residuals (or) how to correct the estimates?? Can some one direct me in
> this regard..
>
> Best,
>
> Kishore/..
> http://kaykayatisb.blogspot.com
>
> [[alternative HTML version deleted]]
>
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--
John C Frain
Trinity College Dublin
Dublin 2
Ireland
www.tcd.ie/Economics/staff/frainj/home.html
mailto:fra...@tcd.ie
mailto:fra...@gmail.com
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