st: Re: Re: RE: Nonlinear IV estimation in STATA

["Elaine Tan" <elaine.tan@econ.hku.hk>]

Hi - Information that I left out earlier: B measures size of market demand, 
A is maximum willingness to pay.

Hope this clarifies things. Many thanks, Elaine


----- Original Message ----- 
From: "Elaine Tan" <elaine.tan@econ.hku.hk>
To: <statalist@hsphsun2.harvard.edu>
Sent: Saturday, April 29, 2006 11:43 AM
Subject: st: Re: RE: Nonlinear IV estimation in STATA



> Thanks - the demand function is modelled as:
>
> Q = B(A-P)^2
>
> rewritten as: lnQ = lnB + 2 ln(A-P) + u
>
> So the function is nonlinear in A. I think I need nonlinear IV regression 
> to estimate A?
>
> (I have modelled the demand function as linear [Q=B(A-P)] and log-linear - 
> these estimations were done using ivreg2)
>
> I would like to use Amemiya's least-distance method (or Jorgensen's 
> estimator), but I don't know how to ask stata to do it.
>
> Any help will be much appreciated, Elaine
>
>
> ----- Original Message ----- 
> From: "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>
> To: <statalist@hsphsun2.harvard.edu>
> Sent: Saturday, April 29, 2006 5:55 AM
> Subject: st: RE: Nonlinear IV estimation in STATA
>
>
>
> > Elaine,
> >
> > > -----Original Message-----
> > > From: owner-statalist@hsphsun2.harvard.edu
> > > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Elaine Tan
> > > Sent: 28 April 2006 02:45
> > > To: statalist@hsphsun2.harvard.edu
> > > Subject: st: Nonlinear IV estimation in STATA
> > >
> > > Hi, I would like to estimate a quadratic demand function with
> > > endogenous price-sq on the RHS that is instrumented by a few
> > > variables. Can someone please help me do nonlinear IV
> > > regressions on STATA?
> > I'm not sure I understand.  It sounds like your model is nonlinear in
> > variables but linear in parameters.  If so, then you don't need
> > nonlinear IV.  Standard linear IV will work just fine, so long as you
> > have instruments for your price-sq term.  But perhaps my description of
> > the model is incorrect.
> >
> > --Mark
> >
> > > Many thanks. Elaine Tan
> > >
> > >
> > >
> > >
> > >
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