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Re: st: RE: Pseudo Rsquared with IVPROBIT


From   "Martin Weiss" <Martin.Weiss1@gmx.de>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: Pseudo Rsquared with IVPROBIT
Date   Thu, 19 Mar 2009 16:36:20 +0100

<>

-ssc d fitstat- does not report any results after -ivprobit-, either, which is not a good sign...

HTH
Martin
-------- Original-Nachricht --------
> Datum: Thu, 19 Mar 2009 11:30:20 -0400
> Von: "Verkuilen, Jay" <JVerkuilen@gc.cuny.edu>
> An: statalist@hsphsun2.harvard.edu
> Betreff: st: RE: Pseudo Rsquared with IVPROBIT

> Sophia Rüster wrote:
> 
> 
> >>With my dataset I wish to use the regression method IVPROBIT (probit
> model
> with continuous endogenous regressor). The regression seems to work fine.
> However, no goodness-of-fit indicator is reported. I wondered whether it
> would be possible to calculate a pseudo-R² for example, whether this
> technically is not feasible or whether this would make no sense from an
> interpretational point of view.<<
> 
> Generally if Stata doesn't report something, there are reasons why.
> Usually this means that there is substantial controversy over interpretation. 
> 
> I don't know about -ivprobit- specifically but the general problem with
> defining pseudo-R^2 measures is the choice of reference model. In ordinary
> regression this is the no-regressors model, but as we all know, this can be a
> very poor reference, making a poorly functioning model look great (i.e.,
> have high R^2) even though it provides little utility. Regressions with
> lagged dependent variables are canonical examples of this. What may help you is
> if you can figure out a way to situate the models you fit between
> something that's too simple and too complex. For instance, maybe you're primarily
> interested in a subset of variables and have some other controls (and the
> instrument) that are in all models. Then the it makes sense to judge the
> performance of the variables of interest against the model with controls and
> the instrument. 
> 
> An alternative strategy is to use the information-theoretic model
> selection strategy discussed in books like Burnham and Anderson (2003):
> http://www.amazon.com/Selection-Multi-Model-Inference-Kenneth-Burnham/dp/0387953647/ref=pd_bbs_sr_1?ie=UTF8&s=books&qid=1237476507&sr=8-1
> 
> 
> 
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Martin Weiss
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