Re: st: 3SLS / Three Stage with heteroscedasticity robust errors

[John Antonakis <john.antonakis@unil.ch>]

Hi Mark:

The help file mentions too:

cmp is appropriate for two types of models: 1) those in which a truly 
recursive data-generating process is posited;
   and 2) those in which there is simultaneity, but instruments allow 
the construction of a recursive set of equations,
   as in two-stage least squares, that can be used to consistently 
estimate structural parameters in the final stage. In
   the first case, cmp is a full-information maximum likelihood (FIML) 
estimator, and all estimated parameters are
   structural. In the latter, it is a limited-information (LIML) 
estimator, and only the final stage's coefficients are
   structural, the rest being reduced-form parameters. What matters for 
the validity of cmp is that the system of
   equations is recursive, whether or not the model is.

Note, the presentation of Roodman (on page 12):

http://www.stata.com/meeting/dcconf09/dc09_roodman.ppt

What do you make of this?

Best,
J.


____________________________________________________

Prof. John Antonakis
Associate Dean Faculty of Business and Economics
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland

Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305

Faculty page:
http://www.hec.unil.ch/people/jantonakis&cl=en

Personal page:
http://www.hec.unil.ch/jantonakis
____________________________________________________



On 09.09.2009 18:00, Schaffer, Mark E wrote:
> Wiebke, John,
>
>   
> > -----Original Message-----
> > From: owner-statalist@hsphsun2.harvard.edu 
> > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> > John Antonakis
> > Sent: Wednesday, September 09, 2009 4:52 PM
> > To: statalist@hsphsun2.harvard.edu
> > Subject: Re: st: 3SLS / Three Stage with heteroscedasticity 
> > robust errors
> >
> > Hi:
> >
> > Use Roodman's cmp. It allows you to estimate systems of 
> > equations using 
> > ML with heteroskedastic robust SEs. Do -ssc install cmp-.
> >     
>
> Good suggestion, and hopefully Wiebke's problem is recursive.  From the
> -cmp- help file:
>
> "Recursive" means, however, that cmp can only fit sets of equations with
> clearly defined stages, not ones with simultaneous causation. A and B
> can be modeled determinants of C and C a determinant of D--but D cannot
> be a modeled determinant of A, B, or C.
>
> Cross fingers!
>
> --Mark
>
>   
> > HTH,
> > J.
> >
> > Roodman, D. (2008). Cmp: Stata module to implement conditional 
> > (recursive) mixed process estimator. 
> > http://ideas.repec.org/c/boc/bocode/s456882.html.
> >
> > ____________________________________________________
> >
> > Prof. John Antonakis
> > Associate Dean Faculty of Business and Economics
> > University of Lausanne
> > Internef #618
> > CH-1015 Lausanne-Dorigny
> > Switzerland
> >
> > Tel ++41 (0)21 692-3438
> > Fax ++41 (0)21 692-3305
> >
> > Faculty page:
> > http://www.hec.unil.ch/people/jantonakis&cl=en
> >
> > Personal page:
> > http://www.hec.unil.ch/jantonakis
> > ____________________________________________________
> >
> >
> >
> > On 09.09.2009 17:47, Wiebke Schlanbusch wrote:
> >     
> > > Dear Statalist-ers,
> > >
> > > for my diploma thesis I want to estimate a simultaneous 
> > >       
> > equations model with different data samples using -reg3-. I 
> > tested all my single equations on heteroscedasticity using 
> > -ivreg2- for the equations and -ivhettest- for the test. Some 
> > of my equations turn out to be heteroscedastic and other 
> > not... Therefore I would like to estimate the 3SLS models 
> > using robust errors, which is not implemented. Someone 
> > suggested to programm it in Stata, but unfortunately my 
> > programming skills are not worth mentioning nor do I have the 
> > programming manual. This is why I am asking if anyone ever 
> > did this "robust errors three stage"-programming and might be 
> > so kind to help me with the code. 
> >     
> > > (I am currently using Stata 10.1)
> > >
> > > Kind regards,
> > > Wiebke Schlanbusch
> > >
> > >
> > >       
> > >
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>
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