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RE: st: Statistical tests under heteroskedasticity
From
Cameron McIntosh <[email protected]>
To
STATA LIST <[email protected]>
Subject
RE: st: Statistical tests under heteroskedasticity
Date
Tue, 15 May 2012 17:23:19 -0400
Indeed, that is exactly the argument presented in:
Freedman, D.A. (2006). On the So-Called “Huber Sandwich Estimator” and “Robust Standard Errors”. The American Statistician, 60(4), 299-302. http://www.stat.berkeley.edu/~census/mlesan.pdf
Cam
> From: [email protected]
> To: [email protected]
> Date: Tue, 15 May 2012 10:09:49 -0500
> Subject: Re: st: Statistical tests under heteroskedasticity
>
> .
>
> I think it is important (for people like me) to remember to tack on to the end of this correct statement:
>
> (1) provided the model for the expectations (means, for linear regression) is approximately correct, and
> (2) provided the sample size is large enough
>
> The vce(robust) option is not going to help a poor model, or a model missing important covariates.
>
> If desired, Stata provides more conservative robust options (vce(hc3)) for linear regression with smaller samples.
>
> > <>
> > On May 15, 2012, at 2:33 AM, Lukas wrote:
> >
> > > I use Stata 11.2 and I want to run several statistical tests to analyse my regression results. In my regression, I use the -robust- option but now I became aware, that heteroskedasticity invalidates my statistical tests such as hypothesis tests as well.
> > >
> > > Is there a way to run the -ttest- and -testparm- commands under heteroskedasticity without invalidating their results?
> >
> > Calculating robust standard errors -- or more properly, a robust VCE -- 'robustifies' all computations done with that VCE, including t-tests and F-tests. So if the only departure from i.i.d. errors is heteroskedasticity, the 'robust' option makes all subsequent test, testparm, lincom, etc. valid.
> >
> > Kit
>
>
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