Thank you for the kind replies from Nick Cox and Kit Baum. Somehow I received your messages just now (not only yours but also all messages from statalist).
The estimation method that I have in mind is the "minimum distance estimation" since I do not want to assume a parametric form for the error terms. So, neither "ml" nor "nl" seem to be helpful. Are there any other ways?
Hyeok
----- Original Message -----
From: Kit Baum <[email protected]>
Date: Saturday, June 2, 2007 5:09 am
Subject: st: Re: estimation of nonlinear simultaneous equations system
To: [email protected]
> Feiveson's FAQ deals with the solution of nonlinear equations
> which
> evaluate to scalars. What is asked below is how you estimate a set
> of
> stochastic equations where each LHS is a vector. Stata's -nl- does
>
> not really deal with that. If you were willing to make
> distributional
> assumptions on the error covariance matrix, you could use -ml- and
> do
> it with FIML.
>
>
> Kit Baum, Boston College Economics and DIW Berlin
> http://ideas.repec.org/e/pba1.html
> An Introduction to Modern Econometrics Using Stata:
> http://www.stata-press.com/books/imeus.html
>
>
> On May 31, 2007, at 2:33 AM, statalist-digest wrote:
>
> > Presumably you are aware of
> >
> > FAQ . . . . . . . . . Using Stata to solve a system of
> > nonlinear equations
> > . . . . . . . . . . . . . . . . . . . . . . . . . . . .
> A.
> > H. Feiveson
> > 10/05 How can I use Stata to solve a system of nonlinear
> > equations?
> > http://www.stata.com/support/faqs/lang/nl.html
> >
> > Your problem is very general given no specification of F or G
> and
> > the fact
> > that you want some flexibility over error structure. Nor do you
> say
> > how
> > you expect or want to estimate the equations.
> >
> > Nick
> > [email protected]
> >
> > Hyeok Jeong
> >
> >> I would like to estimate a nonlinear simultaneous equation
> >> system using
> >> Stata, for example:
> >> Y1(t) = F[X1(t),X2(t); p] +U1(t)
> >> Y2(t) = G[X1(t),X2(t); p] +U2(t),
> >> where Y1 and Y2 are dependent variables, X1 and X2 are explanatory
> >> variables, U1 and U2 are possibly correlated error terms, and p
> is
> >> the
> >> vector of parameters to be estimated.
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
