--- On Tue, 1/9/09, amatoallah ouchen wrote:
> the tobit model with friction is based on the limited
> dependant variable (LDV) model of Tobin (1958) and Rosett
> (1959). here is the model
>
> y*t = xtb + et
>
>
> yt = y*t - a1 if y*t< a1
> yt=0 if a1<y*t< a2
> yt = y*t- a2 if y*t> a2
>
> y*t is the latent variable
>
> with a1< 0 and a2>0
> and e i.i.d, residuals of the estimation with
> variance sj^2. The parameters b, a1 a2 and s are
> solved by maximising a log-likelihood function.
I have two thoughts:
1) If the a's are known than you should be able to
use -intreg- to fit this model. I am a bit worried
about estimating the a's. First, it seems to me
highly improbable that the data contains enough
information to reliably estimate these parameters
(other than a1 is largest observed y less than 0
and a2 is the smallest observed y more than 0).
Second, in many cases we already have a good idea
about what these values may be, either from the
questionair design or by looking at the observed
y-s, so why not use this information. So I would
just fix these at reasonable values, and use
-intreg-.
2) When I am creating a program using -ml- and it
doesn't converge the problem has always been an
error my likelihood function (a bracket in the
wrong place, a lost minus sign, etc.), and never
in the starting values. I realize that not
everybody is as sloppy as I am, but it is an
indication about what may be going on.
Hope this helps,
Maarten
Ps. The Statalist FAQ explicitly askes everybody
to give full references and not just author-year
references. The reason is that this list is read
by people from many different disciplines, and
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with with a name-year reference) are completely
unknown to the rest of the world.
--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://www.maartenbuis.nl
--------------------------
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