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RE: st: RE: Robust instrumental variable regression

From   Nick Cox <[email protected]>
To   "'[email protected]'" <[email protected]>
Subject   RE: st: RE: Robust instrumental variable regression
Date   Fri, 14 Jan 2011 16:35:15 +0000

In addition to other comments, I'd advise against basing anything much on -rreg-. 

The help file has it right: -rreg- is "one version of robust regression". When -rreg- was written the method seemed a good all-round flavour of robust regression, but it is doubtful whether it now looks like _the_ method of choice to anyone in 2011. 

If you ever used -rreg- for real, you'd be obliged to explain it and defend the choice in any serious forum. 

"I used robust regression" means virtually nothing. There are probably hundreds of ways to do robust regression (quite apart from what robustness means). 

"I used -rreg- as implemented in Stata" counts for little outside this community. 

"I used robust regression as codified by Li (1985)" obliges you to explain why you didn't use something more recent (to fad- and fashion-followers) or something else that someone else fancies for some reason of their own. The literature would keep you busy indefinitely. 

Li, G. 1985. Robust regression. In Exploring Data Tables, Trends, and Shapes, ed. D. C. Hoaglin, F. Mosteller, and
J. W. Tukey, 281-340. New York: Wiley.

Outliers could be handled in many different ways. Considering transformations on one or more variables is another way to do that. Wonder whether a linear structure makes sense scientifically is yet another. 

[email protected] 

Maarten buis

--- Ramiro H. Gálvez asked:
> I am using stata 11 and I'm having problems with outliers
> in a 2SLS instrumental variable regression. Is there any
> implementation in stata equivalent to rreg for
> instrumental variable regression (like rivregress)?

--- On Fri, 14/1/11, Jan Bryla answered:
> > Could using the vce(robust) option when performing
> > -ivregress- potentially solve you problem?

No, -vce(robust)- is robust in a very different sense than
-rreg-. When thinking of robust in terms of -rreg- you
worry about the effect of outliers on the point estimates.
Robust in the sense of -vce(robust)- has to do with the
influence of deviations from model assumption on the 
standard error. 

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